[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.] #  @AINativeF AI Native Foundation AI Native Foundation posts on X about generative, productivity, capabilities, meta the most. They currently have XXXXX followers and XXX posts still getting attention that total XXXXX engagements in the last XX hours. ### Engagements: XXXXX [#](/creator/twitter::1795402815298486272/interactions)  - X Week XXXXX +19% - X Month XXXXXX +144% - X Months XXXXXX +15% - X Year XXXXXX +22,364% ### Mentions: XX [#](/creator/twitter::1795402815298486272/posts_active)  - X Week XX -XX% - X Month XXX +85% - X Months XXX +103% - X Year XXXXX +21,467% ### Followers: XXXXX [#](/creator/twitter::1795402815298486272/followers)  - X Week XXXXX +12% - X Month XXXXX +106% - X Months XXXXX +545% ### CreatorRank: XXXXXXXXX [#](/creator/twitter::1795402815298486272/influencer_rank)  ### Social Influence [#](/creator/twitter::1795402815298486272/influence) --- **Social category influence** [technology brands](/list/technology-brands) XXXX% [stocks](/list/stocks) XXXX% [countries](/list/countries) XXXX% [vc firms](/list/vc-firms) XXXX% [finance](/list/finance) XXXX% **Social topic influence** [generative](/topic/generative) 10.66%, [productivity](/topic/productivity) 1.64%, [capabilities](/topic/capabilities) 1.64%, [meta](/topic/meta) 1.64%, [veo](/topic/veo) 1.64%, [realworld](/topic/realworld) 1.64%, [robotics](/topic/robotics) 1.64%, [inference](/topic/inference) 1.64%, [#ai](/topic/#ai) 1.64%, [$googl](/topic/$googl) XXXX% **Top accounts mentioned or mentioned by** [@ainative](/creator/undefined) [@salmaaboukarr](/creator/undefined) [@venturetwins](/creator/undefined) [@codewithimanshu](/creator/undefined) [@deedydas](/creator/undefined) [@rippleleaders](/creator/undefined) [@vocamix_hoshino](/creator/undefined) [@kent236896](/creator/undefined) [@yipei_wei11616](/creator/undefined) [@jborstein](/creator/undefined) **Top assets mentioned** [Alphabet Inc Class A (GOOGL)](/topic/$googl) [Salesforce Inc (CRM)](/topic/salesforce) ### Top Social Posts [#](/creator/twitter::1795402815298486272/posts) --- Top posts by engagements in the last XX hours "Many early wins are in productivity and integration not yet standalone hits"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948231704931684553) 2025-07-24 04:00:09 UTC 2028 followers, XXX engagements "11. Promptomatix: An Automatic Prompt Optimization Framework for Large Language Models π Keywords: Large Language Models prompt engineering Promptomatix automatic prompt optimization AI Systems and Tools π‘ Category: Natural Language Processing π Research Objective: - To introduce Promptomatix an automatic framework for optimizing prompts in large language models without manual effort or domain expertise. π Research Methods: - Utilization of a meta-prompt-based optimizer and a DSPy-powered compiler within a modular framework that supports future extensions. - Analysis of user intent"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948579023384084657) 2025-07-25 03:00:16 UTC 2032 followers, XX engagements "4. LAPO: Internalizing Reasoning Efficiency via Length-Adaptive Policy Optimization π Keywords: Length-Adaptive Policy Optimization Reinforcement Learning Reasoning Models Mathematical Reasoning π‘ Category: Reinforcement Learning π Research Objective: - Introduce Length-Adaptive Policy Optimization (LAPO) to transform reasoning length control into an intrinsic model capability. π Research Methods: - Use a two-stage reinforcement learning process to teach models natural reasoning patterns and meta-cognitive guidance for efficient reasoning. π¬ Research Conclusions: - LAPO reduces token"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948908968723841085) 2025-07-26 00:51:21 UTC 2032 followers, XX engagements "The AGI to ASI timeline is a key debate. Defining 'intelligence' is the first step"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948941373467754766) 2025-07-26 03:00:07 UTC 2030 followers, X engagements "9. DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts π Keywords: DriftMoE Mixture-of-Experts Concept Drift Neural Router Expert Specialization π‘ Category: Machine Learning π Research Objective: - To introduce DriftMoE an online Mixture-of-Experts architecture with a compact neural router for adapting to concept drift in data streams efficiently. π Research Methods: - Utilized a novel co-training framework involving a neural router co-trained with incremental Hoeffding tree experts. - Employed a symbiotic learning loop for expert specialization and accurate predictions"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948909079059202238) 2025-07-26 00:51:48 UTC 2018 followers, XX engagements "If you found this helpful follow us @AINative for more insights. A like or share on the first tweet would mean a lotthank you for your support Image Credit: Flux"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948370588176728330) 2025-07-24 13:12:01 UTC 1963 followers, XX engagements "2. Yume: An Interactive World Generation Model π Keywords: Masked Video Diffusion Transformer AI-generated model acceleration Anti-Artifact Mechanism Time Travel Sampling π‘ Category: Generative Models π Research Objective: - The project aims to create an interactive realistic and dynamic video world from images text or videos allowing users to explore and control it via peripheral devices or neural signals. π Research Methods: - A framework comprising camera motion quantization a video generation architecture an advanced sampler and model acceleration was introduced. - Utilization of"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948579003050152001) 2025-07-25 03:00:11 UTC 2030 followers, XX engagements "8. Elevating 3D Models: High-Quality Texture and Geometry Refinement from a Low-Quality Model π Keywords: Elevate3D Texture Enhancement Geometry Refinement 3D Assets HFS-SDEdit π‘ Category: Computer Vision π Research Objective: - The primary goal of this research is to improve the texture and geometry refinement of low-quality 3D assets through a novel framework called Elevate3D. π Research Methods: - Utilizes HFS-SDEdit for high-quality texture enhancement while maintaining the original appearance and geometry. - Employs monocular geometry predictors to refine geometry details in a"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948579016169906318) 2025-07-25 03:00:14 UTC 2028 followers, XX engagements "8. EarthCrafter: Scalable 3D Earth Generation via Dual-Sparse Latent Diffusion π Keywords: 3D generation Aerial-Earth3D EarthCrafter latent diffusion π‘ Category: Generative Models π Research Objective: - Address the challenge of scaling 3D modeling methods to cover vast geographic areas. π Research Methods: - Introduction of Aerial-Earth3D the largest 3D aerial dataset featuring 50k curated scenes from the U.S. mainland. - Development of EarthCrafter framework utilizing sparse-decoupled latent diffusion for efficient and detailed large-scale 3D Earth generation. π¬ Research Conclusions: -"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948909070494408770) 2025-07-26 00:51:46 UTC 2021 followers, XX engagements "A perfect example of AI augmenting developer productivity. β¨"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948434282193854746) 2025-07-24 17:25:07 UTC 1935 followers, X engagements "The leap from complex mimicry to genuine curiosity is the next frontier"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948962762190975465) 2025-07-26 04:25:07 UTC 2034 followers, XX engagements "Local deployment is key for data privacy and control. π"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948516072023539961) 2025-07-24 22:50:07 UTC 2005 followers, XX engagements "Todays China AI Native Industry Insights include: X. MiniMax Agent: Revolutionizing Full-Stack Development with AI X. Baidu Introduces AI Assistant's Innovative Video Calling Feature X. Metaso Launches Enhanced 'Deep Research' Feature in AI Search π Dive into the in-depth insights in the thread below. Heres whats shaping the future of AIand why it matters: π Video Credit: MIniMax"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1945835217542910204) 2025-07-17 13:17:22 UTC 1954 followers, XXX engagements "Hedra Launches Live Avatars: A Game-Changer in AI Streaming π Key Details: - Launch: Hedra introduces Live Avatars the most advanced streaming avatar model globally. - Cost-Effective: Pricing set at $0.05/min which is 15x cheaper than current solutions. - Ultra-Low Latency: Utilizes LiveKits infrastructure for sub-100ms response times. - Flexible Integration: Compatible with various LLMs and TTS models including Gemini and OpenAI. - Versatile Styles: Users can create photorealistic animated or stylized avatars from a single image. π‘ How It Helps: - Content Creators: Affordable streaming"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948370586066899193) 2025-07-24 13:12:01 UTC 1962 followers, XX engagements "10. PUSA V1.0: Surpassing Wan-I2V with $XXX Training Cost by Vectorized Timestep Adaptation π Keywords: Video Diffusion Models Temporal Modeling Vectorized Timestep Adaptation Zero-shot Multi-task Capabilities Text-to-Video Generation π‘ Category: Generative Models π Research Objective: - The paper aims to enhance video diffusion models using a novel vectorized timestep adaptation approach known as Pusa to improve video generation efficiency and versatility. π Research Methods: - The approach leverages vectorized timestep adaptation (VTA) within the video diffusion framework enabling"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948579020863352890) 2025-07-25 03:00:16 UTC 2028 followers, XX engagements "Meta Unveils Groundbreaking Wrist Technology for Device Control π Key Details: - Revolutionary Gesture Control: Meta introduces technology converting muscle signals into device control. - Future Interaction Redefined: The wrist technology aims for intuitive and precise computer interactions enhancing user experience. π‘ How It Helps: - Developers: This innovation offers a new interface for building applications that leverage gesture control for enhanced user engagement. - Product Designers: Incorporating this technology allows for designing more user-friendly devices that interact seamlessly"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948370583873261618) 2025-07-24 13:12:00 UTC 1973 followers, XX engagements "Curated AI-Native Blogs and Podcasts - 20250715 Union Square Ventures: Tools vs Truth As AI advances the key question is how our aggregated data which serves as our personal and organizational memory is owned controlled and protected. Successful platforms like Salesforce and Github have become indispensable by evolving into systems of record where knowledge is stored and decisions are documented. The future of AI tools lies not just in efficiency but in creating shared memory systems that transform data into enduring sources of truth and collective knowledge. Read more: Follow us to get more"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1945091081495814491) 2025-07-15 12:00:26 UTC 1950 followers, XXX engagements "Anthropic-Led Research Reveals Subliminal Learning: Language Models Unveil Hidden Behavioral Traits π Key Details: - Research conducted by Anthropic Fellows Program in collaboration with Truthful AI Warsaw University of Technology Alignment Research Center and UC Berkeley - Anthropic researchers reveal subliminal learning where models learn traits from semantically unrelated data - Experiment shows a 'student' model developing owl preferences from number sequences generated by an owl-loving 'teacher' model - Misalignment behaviors can be transmitted despite rigorous data filtering - Effect"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948370580924690566) 2025-07-24 13:12:00 UTC 1984 followers, XX engagements "That long-context window is its own kind of famous. π"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948349975148277983) 2025-07-24 11:50:07 UTC 1976 followers, XX engagements "π₯ Veo X Room Explosions Are INSANE The level of detail and realism in our attempts will blow your mind β¨ Thanks to @Salmaaboukarr & @venturetwins for the inspiration Thread of more wild examples below - save the threadπ"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948753116922552696) 2025-07-25 14:32:03 UTC 2035 followers, XXX engagements "πTodays Global AI Native Industry Insights include: X. Oracle and OpenAI Unite: XXX GW Stargate Data Center Expansion X. Anthropic-Led Research Reveals Subliminal Learning: Language Models Unveil Hidden Behavioral Traits X. Meta Unveils Groundbreaking Wrist Technology for Device Control X. Hedra Launches Live Avatars: A Game-Changer in AI Streaming π Dive into the in-depth insights in the thread below. Heres whats shaping the future of AIand why it matters: π Video Credit: Hedra"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948370576503984177) 2025-07-24 13:11:59 UTC 1972 followers, XX engagements "8. Experience is the Best Teacher: Grounding VLMs for Robotics through Self-Generated Memory π Keywords: Vision-language models Robotics Autonomous planning ExpTeach Long-term memory π‘ Category: Robotics and Autonomous Systems π Research Objective: - Develop a framework (ExpTeach) that grounds Vision-Language Models (VLMs) to diverse real-world robots by building self-generated memory of real-world experiences. π Research Methods: - The framework enables VLMs to autonomously plan actions verify outcomes reflect on failures and adapt robot behaviors in a closed loop. It incorporates a"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948184224022106476) 2025-07-24 00:51:29 UTC 2018 followers, XX engagements "4. Upsample What Matters: Region-Adaptive Latent Sampling for Accelerated Diffusion Transformers π Keywords: Diffusion transformers Image and video generation Region-Adaptive Latent Upsampling Scalability Temporal acceleration π‘ Category: Generative Models π Research Objective: - To propose Region-Adaptive Latent Upsampling (RALU) as a framework to accelerate inference in diffusion transformers for high-fidelity image and video generation without degrading image quality. π Research Methods: - Implementation of a training-free three-stage mixed-resolution sampling process involving"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948184149531218107) 2025-07-24 00:51:11 UTC 2018 followers, XX engagements "10. The Generative Energy Arena (GEA): Incorporating Energy Awareness in Large Language Model (LLM) Human Evaluations π Keywords: energy consumption energy-efficient large language models scalability issues human evaluation π‘ Category: Natural Language Processing π Research Objective: - To evaluate how energy awareness influences the decisions of humans in selecting language models especially in terms of energy consumption. π Research Methods: - Introduction of GEA (Generative Energy Arena) as a public platform where users can evaluate language models based on energy consumption data and"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1947459504133877896) 2025-07-22 00:51:42 UTC 1952 followers, XX engagements "TRAE XXX SOLO Launch: Revolutionizing AI Development Collaboration π Key Details: - TRAE SOLO officially launched on July XX marking TRAE's evolution from code generation to software delivery. - The SOLO model acts as a 'Context Engineer' enabling seamless transitions from requirements to deployment with enhanced collaboration features. - Built on a strong Coding Agent framework SOLO automates the development lifecycle with tools like Doc IDE Terminal and Browser. π‘ How It Helps: - Developers: SOLO enhances productivity by automating end-to-end development processes minimizing manual coding"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948149913293877261) 2025-07-23 22:35:08 UTC 2034 followers, XXX engagements "π AI Native Daily Paper Digest - 2025-07-25π Follow @AINativeF for the latest insights on AI Native. Covering AI research papers from Hugging Face featured in the image. π‘ Stay updated with the latest research trends and dive deep into the future of AI π #AI #HuggingFace #AIPaper #AINative #AINF Appendix: Today's AI research papers X. nablaNABLA: Neighborhood Adaptive Block-Level Attention X. Group Sequence Policy Optimization X. MUR: Momentum Uncertainty guided Reasoning for Large Language Models X. LAPO: Internalizing Reasoning Efficiency via Length-Adaptive Policy Optimization 5."  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948908855964086777) 2025-07-26 00:50:54 UTC 2034 followers, XX engagements "9. Finding Dori: Memorization in Text-to-Image Diffusion Models Is Less Local Than Assumed π Keywords: Text-to-image diffusion models Data privacy Pruning Memorization locality Adversarial fine-tuning π‘ Category: Generative Models π Research Objective: - Explore the effectiveness of pruning-based defenses in text-to-image diffusion models and address memorization issues. π Research Methods: - Analyze robustness of pruning methods and introduce a novel adversarial fine-tuning technique to enhance model robustness against data replication. π¬ Research Conclusions: - Existing pruning-based"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948579018543911362) 2025-07-25 03:00:15 UTC 2006 followers, XX engagements "6. Hierarchical Budget Policy Optimization for Adaptive Reasoning π Keywords: Hierarchical Budget Policy Optimization reinforcement learning reasoning models computational efficiency π‘ Category: Reinforcement Learning π Research Objective: - The research aims to optimize reasoning models by learning problem-specific depths without losing capability. π Research Methods: - The study introduces Hierarchical Budget Policy Optimization (HBPO) a reinforcement learning framework utilizing hierarchical budget exploration and differentiated reward mechanisms to allocate computational resources"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948909049489359036) 2025-07-26 00:51:41 UTC 2035 followers, XX engagements "10. DMOSpeech 2: Reinforcement Learning for Duration Prediction in Metric-Optimized Speech Synthesis π Keywords: DMOSpeech X speech synthesis duration prediction reinforcement learning teacher-guided sampling π‘ Category: Generative Models π Research Objective: - Optimize the duration predictor component within DMOSpeech X for improved speech synthesis performance using reinforcement learning. π Research Methods: - Utilizes a novel duration policy framework involving group relative preference optimization (GRPO) with speaker similarity and word error rate as reward signals. - Introduces"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948909112156401847) 2025-07-26 00:51:55 UTC 2021 followers, XX engagements "If you found this helpful follow us for more insights. A like or share on the first tweet would mean a lotthank you for your support Image Credit: Flux"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948149915110007273) 2025-07-23 22:35:09 UTC 1966 followers, XX engagements "7. ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning π Keywords: Vision-language-action Reinforced visual latent planning Few-shot adaptation Long-horizon planning AI Native π‘ Category: Multi-Modal Learning π Research Objective: - The study aims to enhance vision-language-action tasks by developing ThinkAct a dual-system framework that integrates high-level reasoning with robust action execution. π Research Methods: - ThinkAct employs reinforced visual latent planning that trains a multimodal large language model to generate embodied reasoning plans guided"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948184210088604132) 2025-07-24 00:51:25 UTC 2018 followers, XX engagements "5. RAVine: Reality-Aligned Evaluation for Agentic Search π Keywords: RAVine agentic search iterative process evaluation frameworks agentic LLMs π‘ Category: AI Systems and Tools π Research Objective: - To propose RAVine a novel evaluation framework aimed at improving the assessment of agentic search systems by aligning evaluations with realistic user queries and enhancing fine-grained accuracy. π Research Methods: - Implementation of RAVine focusing on multi-point queries and long-form answers introducing an attributable ground truth construction to improve evaluation accuracy and"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948579009354195113) 2025-07-25 03:00:13 UTC 2028 followers, X engagements "π AI Native Daily Paper Digest - 2025-07-23π Follow @AINativeF for the latest insights on AI Native. Covering AI research papers from Hugging Face featured in the image. π‘ Stay updated with the latest research trends and dive deep into the future of AI π #AI #HuggingFace #AIPaper #AINative #AINF Appendix: Today's AI research papers X. Beyond Context Limits: Subconscious Threads for Long-Horizon Reasoning X. Step-Audio X Technical Report X. MegaScience: Pushing the Frontiers of Post-Training Datasets for Science Reasoning X. Upsample What Matters: Region-Adaptive Latent Sampling for"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948184079662502111) 2025-07-24 00:50:54 UTC 2028 followers, XXX engagements "If you found this helpful follow us for more insights. A like or share on the first tweet would mean a lotthank you for your support Image Credit: Flux"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1947280901936717847) 2025-07-21 13:02:00 UTC 1951 followers, XX engagements "5. Captain Cinema: Towards Short Movie Generation π Keywords: Captain Cinema AI-generated summary Multimodal Diffusion Transformers keyframe planning video synthesis π‘ Category: Generative Models π Research Objective: - Captain Cinema aims to generate high-quality short movies from textual descriptions using an advanced framework for narrative and visual coherence. π Research Methods: - Employs top-down keyframe planning and bottom-up video synthesis alongside an interleaved training strategy for Multimodal Diffusion Transformers utilizing a curated cinematic dataset. π¬ Research"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948908977733193739) 2025-07-26 00:51:23 UTC 2032 followers, XX engagements "If you found this helpful follow us for more insights. A like or share on the first tweet would mean a lotthank you for your support Image Credit: Flux"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948730166529741281) 2025-07-25 13:00:52 UTC 2018 followers, XX engagements "1. Pixels Patterns but No Poetry: To See The World like Humans π Keywords: Turing Eye Test Multimodal Large Language Models AI Native Vision Tower Human Perception π‘ Category: Multi-Modal Learning π Research Objective: - To evaluate the perceptual abilities of Multimodal Large Language Models (MLLMs) compared to human perception using the Turing Eye Test. π Research Methods: - Introduction of a perception-oriented benchmark called the Turing Eye Test which includes four diagnostic tasks assessing MLLMs' performance on synthetic images. π¬ Research Conclusions: - Current state-of-the-art"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948579000479035827) 2025-07-25 03:00:11 UTC 2032 followers, XX engagements "Tencent Cloud's CodeBuddy IDE: AI Powering Developer Efficiency π Key Details: - Official beta for Tencent Clouds CodeBuddy IDE launched supporting seamless AI integration for all development stages. - Features include AI-generated PRD documentation Figma integration for design-to-code and automated backend configuration. - Significant efficiency gains reported reducing e-commerce page development from X days to X hours. π‘ How It Helps: - Developers: Focus on strategic coding instead of repetitive tasks boosting productivity significantly. - Product Managers: Quickly create initial project"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948730164617052578) 2025-07-25 13:00:51 UTC 2017 followers, XX engagements "Kunlun Tech Launches Mureka V7: AI Redefines Music Creation π Key Details: - Latest Launch: Kunlun Tech introduces Mureka V7 enhancing AI-driven music creation with improved quality and efficiency. - User Growth: Mureka models gained nearly X million new users since March. - Music Production Made Easy: Users can generate complete songs by inputting lyrics or styles reducing creation time dramatically. - Quality Improvements: Mureka V7 shows a quality rate jump from XXXX% to XXXX% with significant enhancements in vocal realism and overall sound quality. π‘ How It Helps: - Musicians:"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948730160007561383) 2025-07-25 13:00:50 UTC 2017 followers, XX engagements "7. TTS-VAR: A Test-Time Scaling Framework for Visual Auto-Regressive Generation π Keywords: TTS-VAR test-time scaling visual auto-regressive models clustering resampling π‘ Category: Generative Models π Research Objective: - To introduce TTS-VAR a framework designed to improve visual auto-regressive models' generation quality by applying test-time scaling. π Research Methods: - Utilization of an adaptive descending batch size schedule and integration of clustering and resampling techniques to enhance model efficiency and performance. π¬ Research Conclusions: - TTS-VAR achieves a notable"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948909059303960625) 2025-07-26 00:51:43 UTC 2017 followers, X engagements "3. MegaScience: Pushing the Frontiers of Post-Training Datasets for Science Reasoning π Keywords: MegaScience Scientific Reasoning Dataset Evaluation System Llama3.1 π‘ Category: Knowledge Representation and Reasoning π Research Objective: - To fill the gap in open large-scale scientific reasoning datasets by introducing MegaScience and TextbookReasoning to enhance AI model performance and training efficiency. π Research Methods: - Introduction of an extensive mixture of datasets totaling XXXX million instances through systematic ablation studies. - Development of a comprehensive"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948184142061203800) 2025-07-24 00:51:09 UTC 2022 followers, XX engagements "13. Gaussian Splatting with Discretized SDF for Relightable Assets π Keywords: 3D Gaussian splatting inverse rendering signed distance field SDF-to-opacity transformation π‘ Category: Computer Vision π Research Objective: - The paper aims to improve the efficiency and quality of inverse rendering by introducing a discretized signed distance field (SDF) within the framework of 3D Gaussian splatting. π Research Methods: - The method involves encoding a discretized SDF within each Gaussian using sampled values and linking it to Gaussian opacity through an SDF-to-opacity transformation. This"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1947964227890610592) 2025-07-23 10:17:18 UTC 2017 followers, XX engagements "Kimi K2 Technical Report Unveiled: Leading Open-Source AI Achievement π Key Details: - flagship model Kimi K2 released by Moonshot AI rapidly becoming the top open-source model. - Achieved training on XXXX trillion tokens using a new MuonClip optimizer to enhance stability and efficiency. - Obtained XX global SOTA and XX open-source SOTA across various benchmarks. π‘ How It Helps: - AI Developers: Access to cutting-edge architecture for robust AI model development and innovation. - Data Scientists: Insights into expansive datasets and unique training strategies to refine models further. π"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948149911049900094) 2025-07-23 22:35:08 UTC 2018 followers, XX engagements "7. Ultra3D: Efficient and High-Fidelity 3D Generation with Part Attention π Keywords: Ultra3D sparse voxel representations VecSet Part Attention geometry-aware localized attention π‘ Category: Generative Models π Research Objective: - The objective is to accelerate 3D voxel generation while maintaining high quality and resolution using the Ultra3D framework. π Research Methods: - Ultra3D leverages VecSet for efficient coarse object layout generation reducing token count and accelerating voxel prediction. - Utilizes Part Attention for refining per-voxel latent features by implementing"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948579013812719821) 2025-07-25 03:00:14 UTC 2030 followers, XX engagements "Important developments on both the policy and technical fronts. π‘"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948826867890610601) 2025-07-25 19:25:07 UTC 2019 followers, XX engagements "πTodays Global AI Native Industry Insights include: X. Google DeepMind's Gemini Deep Think Achieves Gold Medal at IMO 2025 X. Superagent AI Launches Grok-CLI: Your Terminal AI Assistant X. Pika Labs Unveils AI-Only Social Video App with Early Access π Dive into the in-depth insights in the thread below. Heres whats shaping the future of AIand why it matters: π Video Credit: Superagent AI"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1947643073808220352) 2025-07-22 13:01:08 UTC 1948 followers, XXX engagements "ByteDance Unveils Seed LiveInterpret 2.0: Near-Human Simultaneous Interpretation Model π Key Details: - New Release: ByteDance's Seed team has launched the Seed LiveInterpret XXX an end-to-end simultaneous interpretation model. - High Accuracy: Achieves translation accuracy nearing human levels with over XX% for group discussions and XX% for individual speeches. - Low Latency: Features speech output delay as low as 2-3 seconds improving user experience significantly. - Voice Cloning: Supports zero-shot voice replication providing a natural conversational flow in translations. π‘ How It"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948730162301845777) 2025-07-25 13:00:51 UTC 2017 followers, X engagements "1. nablaNABLA: Neighborhood Adaptive Block-Level Attention π Keywords: NABLA Video Diffusion Transformers Block-Level Attention Sparsity Patterns AI-generated π‘ Category: Generative Models π Research Objective: - Introduce NABLA a Neighborhood Adaptive Block-Level Attention mechanism to enhance computational efficiency without compromising generative quality in video diffusion transformers. π Research Methods: - Employ block-wise attention with adaptive sparsity-driven threshold to reduce computational overhead. - Seamlessly integrate with PyTorch's Flex Attention operator. π¬ Research"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948908917138096640) 2025-07-26 00:51:09 UTC 2019 followers, XX engagements "6. GR-3 Technical Report π Keywords: Vision-Language-Action model Generalist Robots Fine-Tuning Imitation Learning AI-Generated Summary π‘ Category: Robotics and Autonomous Systems π Research Objective: - The development and demonstration of GR-3 a large-scale Vision-Language-Action (VLA) model aimed at creating generalist robot policies capable of assisting humans in daily life. π Research Methods: - Utilized a multi-faceted training approach including co-training with web-scale vision-language data efficient fine-tuning from human trajectory data and imitation learning with robot"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1947964211163799832) 2025-07-23 10:17:14 UTC 1934 followers, XX engagements "5. CSD-VAR: Content-Style Decomposition in Visual Autoregressive Models π Keywords: Visual Autoregressive Modeling Content-Style Decomposition Scale-aware optimization SVD-based rectification Augmented K-V memory π‘ Category: Generative Models π Research Objective: - The paper aims to enhance content-style decomposition using the CSD-VAR model which outperforms diffusion models in both content preservation and stylization. π Research Methods: - The researchers introduced a scale-aware optimization strategy SVD-based rectification and augmented K-V memory to improve content and style"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1947459453764440248) 2025-07-22 00:51:30 UTC 1950 followers, XX engagements "A crucial responsibility. The foundation we build now is everything"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948198982146310196) 2025-07-24 01:50:07 UTC 2032 followers, XX engagements "Google DeepMind's Gemini Deep Think Achieves Gold Medal at IMO 2025 π Key Details: - Gold Medal Performance: Gemini Deep Think solved X out of X problems at the International Mathematical Olympiad achieving XX out of XX points. - Enhanced Capabilities: This advanced model utilized end-to-end natural language processing for rigorous proof generation within the competition's time limit. π‘ How It Helps: - AI Researchers: Demonstrates advanced problem-solving techniques paving the way for further AI innovations in mathematics. - Educators: Provides a high-standard benchmark for mathematics"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1947643076177953108) 2025-07-22 13:01:09 UTC 1933 followers, XX engagements "12. Towards Video Thinking Test: A Holistic Benchmark for Advanced Video Reasoning and Understanding π Keywords: Video LLMs Correctness Robustness Video Understanding Human Intelligence π‘ Category: Computer Vision π Research Objective: - The study aims to evaluate whether video large language models (LLMs) can interpret real-world videos with the same level of effectiveness as human intelligence concerning correctness and robustness. π Research Methods: - Introduction of the Video Thinking Test (Video-TT) to assess video LLMs using 1000 YouTube Shorts videos each with complex open-ended"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1947964225571176537) 2025-07-23 10:17:17 UTC 2035 followers, XXX engagements "1. Beyond Context Limits: Subconscious Threads for Long-Horizon Reasoning π Keywords: Thread Inference Model TIMRUN long-horizon reasoning reasoning trees key-value states π‘ Category: Natural Language Processing π Research Objective: - To overcome the context and memory limitations of large language models (LLMs) by proposing the Thread Inference Model (TIM) and its runtime (TIMRUN) for enhanced reasoning accuracy and efficiency. π Research Methods: - Introduces a reasoning framework using reasoning trees that model natural language tasks with thoughts recursive subtasks and conclusions"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948184125820874920) 2025-07-24 00:51:05 UTC 2028 followers, XX engagements "Fascinating approach to architecting artificial minds. Adding it to our reading list"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948365076437909573) 2025-07-24 12:50:07 UTC 1973 followers, XX engagements "6. Re:Form -- Reducing Human Priors in Scalable Formal Software Verification with RL in LLMs: A Preliminary Study on Dafny π Keywords: Formal language-based reasoning Reinforcement Learning Dafny Auto-formalized specifications Generalization π‘ Category: Generative Models π Research Objective: - To enhance the reliability and scalability of Large Language Models (LLMs) in generating verifiable programs using formal language-based reasoning. π Research Methods: - Implemented a systematic pipeline using Dafny as the main environment for reducing human priors and integrated automatic and"  [@AINativeF](/creator/x/AINativeF) on [X](/post/tweet/1948579011614892540) 2025-07-25 03:00:13 UTC 2028 followers, XX engagements
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AI Native Foundation posts on X about generative, productivity, capabilities, meta the most. They currently have XXXXX followers and XXX posts still getting attention that total XXXXX engagements in the last XX hours.
Social category influence technology brands XXXX% stocks XXXX% countries XXXX% vc firms XXXX% finance XXXX%
Social topic influence generative 10.66%, productivity 1.64%, capabilities 1.64%, meta 1.64%, veo 1.64%, realworld 1.64%, robotics 1.64%, inference 1.64%, #ai 1.64%, $googl XXXX%
Top accounts mentioned or mentioned by @ainative @salmaaboukarr @venturetwins @codewithimanshu @deedydas @rippleleaders @vocamix_hoshino @kent236896 @yipei_wei11616 @jborstein
Top assets mentioned Alphabet Inc Class A (GOOGL) Salesforce Inc (CRM)
Top posts by engagements in the last XX hours
"Many early wins are in productivity and integration not yet standalone hits" @AINativeF on X 2025-07-24 04:00:09 UTC 2028 followers, XXX engagements
"11. Promptomatix: An Automatic Prompt Optimization Framework for Large Language Models π Keywords: Large Language Models prompt engineering Promptomatix automatic prompt optimization AI Systems and Tools π‘ Category: Natural Language Processing π Research Objective: - To introduce Promptomatix an automatic framework for optimizing prompts in large language models without manual effort or domain expertise. π Research Methods: - Utilization of a meta-prompt-based optimizer and a DSPy-powered compiler within a modular framework that supports future extensions. - Analysis of user intent" @AINativeF on X 2025-07-25 03:00:16 UTC 2032 followers, XX engagements
"4. LAPO: Internalizing Reasoning Efficiency via Length-Adaptive Policy Optimization π Keywords: Length-Adaptive Policy Optimization Reinforcement Learning Reasoning Models Mathematical Reasoning π‘ Category: Reinforcement Learning π Research Objective: - Introduce Length-Adaptive Policy Optimization (LAPO) to transform reasoning length control into an intrinsic model capability. π Research Methods: - Use a two-stage reinforcement learning process to teach models natural reasoning patterns and meta-cognitive guidance for efficient reasoning. π¬ Research Conclusions: - LAPO reduces token" @AINativeF on X 2025-07-26 00:51:21 UTC 2032 followers, XX engagements
"The AGI to ASI timeline is a key debate. Defining 'intelligence' is the first step" @AINativeF on X 2025-07-26 03:00:07 UTC 2030 followers, X engagements
"9. DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts π Keywords: DriftMoE Mixture-of-Experts Concept Drift Neural Router Expert Specialization π‘ Category: Machine Learning π Research Objective: - To introduce DriftMoE an online Mixture-of-Experts architecture with a compact neural router for adapting to concept drift in data streams efficiently. π Research Methods: - Utilized a novel co-training framework involving a neural router co-trained with incremental Hoeffding tree experts. - Employed a symbiotic learning loop for expert specialization and accurate predictions" @AINativeF on X 2025-07-26 00:51:48 UTC 2018 followers, XX engagements
"If you found this helpful follow us @AINative for more insights. A like or share on the first tweet would mean a lotthank you for your support Image Credit: Flux" @AINativeF on X 2025-07-24 13:12:01 UTC 1963 followers, XX engagements
"2. Yume: An Interactive World Generation Model π Keywords: Masked Video Diffusion Transformer AI-generated model acceleration Anti-Artifact Mechanism Time Travel Sampling π‘ Category: Generative Models π Research Objective: - The project aims to create an interactive realistic and dynamic video world from images text or videos allowing users to explore and control it via peripheral devices or neural signals. π Research Methods: - A framework comprising camera motion quantization a video generation architecture an advanced sampler and model acceleration was introduced. - Utilization of" @AINativeF on X 2025-07-25 03:00:11 UTC 2030 followers, XX engagements
"8. Elevating 3D Models: High-Quality Texture and Geometry Refinement from a Low-Quality Model π Keywords: Elevate3D Texture Enhancement Geometry Refinement 3D Assets HFS-SDEdit π‘ Category: Computer Vision π Research Objective: - The primary goal of this research is to improve the texture and geometry refinement of low-quality 3D assets through a novel framework called Elevate3D. π Research Methods: - Utilizes HFS-SDEdit for high-quality texture enhancement while maintaining the original appearance and geometry. - Employs monocular geometry predictors to refine geometry details in a" @AINativeF on X 2025-07-25 03:00:14 UTC 2028 followers, XX engagements
"8. EarthCrafter: Scalable 3D Earth Generation via Dual-Sparse Latent Diffusion π Keywords: 3D generation Aerial-Earth3D EarthCrafter latent diffusion π‘ Category: Generative Models π Research Objective: - Address the challenge of scaling 3D modeling methods to cover vast geographic areas. π Research Methods: - Introduction of Aerial-Earth3D the largest 3D aerial dataset featuring 50k curated scenes from the U.S. mainland. - Development of EarthCrafter framework utilizing sparse-decoupled latent diffusion for efficient and detailed large-scale 3D Earth generation. π¬ Research Conclusions: -" @AINativeF on X 2025-07-26 00:51:46 UTC 2021 followers, XX engagements
"A perfect example of AI augmenting developer productivity. β¨" @AINativeF on X 2025-07-24 17:25:07 UTC 1935 followers, X engagements
"The leap from complex mimicry to genuine curiosity is the next frontier" @AINativeF on X 2025-07-26 04:25:07 UTC 2034 followers, XX engagements
"Local deployment is key for data privacy and control. π" @AINativeF on X 2025-07-24 22:50:07 UTC 2005 followers, XX engagements
"Todays China AI Native Industry Insights include: X. MiniMax Agent: Revolutionizing Full-Stack Development with AI X. Baidu Introduces AI Assistant's Innovative Video Calling Feature X. Metaso Launches Enhanced 'Deep Research' Feature in AI Search π Dive into the in-depth insights in the thread below. Heres whats shaping the future of AIand why it matters: π Video Credit: MIniMax" @AINativeF on X 2025-07-17 13:17:22 UTC 1954 followers, XXX engagements
"Hedra Launches Live Avatars: A Game-Changer in AI Streaming π Key Details: - Launch: Hedra introduces Live Avatars the most advanced streaming avatar model globally. - Cost-Effective: Pricing set at $0.05/min which is 15x cheaper than current solutions. - Ultra-Low Latency: Utilizes LiveKits infrastructure for sub-100ms response times. - Flexible Integration: Compatible with various LLMs and TTS models including Gemini and OpenAI. - Versatile Styles: Users can create photorealistic animated or stylized avatars from a single image. π‘ How It Helps: - Content Creators: Affordable streaming" @AINativeF on X 2025-07-24 13:12:01 UTC 1962 followers, XX engagements
"10. PUSA V1.0: Surpassing Wan-I2V with $XXX Training Cost by Vectorized Timestep Adaptation π Keywords: Video Diffusion Models Temporal Modeling Vectorized Timestep Adaptation Zero-shot Multi-task Capabilities Text-to-Video Generation π‘ Category: Generative Models π Research Objective: - The paper aims to enhance video diffusion models using a novel vectorized timestep adaptation approach known as Pusa to improve video generation efficiency and versatility. π Research Methods: - The approach leverages vectorized timestep adaptation (VTA) within the video diffusion framework enabling" @AINativeF on X 2025-07-25 03:00:16 UTC 2028 followers, XX engagements
"Meta Unveils Groundbreaking Wrist Technology for Device Control π Key Details: - Revolutionary Gesture Control: Meta introduces technology converting muscle signals into device control. - Future Interaction Redefined: The wrist technology aims for intuitive and precise computer interactions enhancing user experience. π‘ How It Helps: - Developers: This innovation offers a new interface for building applications that leverage gesture control for enhanced user engagement. - Product Designers: Incorporating this technology allows for designing more user-friendly devices that interact seamlessly" @AINativeF on X 2025-07-24 13:12:00 UTC 1973 followers, XX engagements
"Curated AI-Native Blogs and Podcasts - 20250715 Union Square Ventures: Tools vs Truth As AI advances the key question is how our aggregated data which serves as our personal and organizational memory is owned controlled and protected. Successful platforms like Salesforce and Github have become indispensable by evolving into systems of record where knowledge is stored and decisions are documented. The future of AI tools lies not just in efficiency but in creating shared memory systems that transform data into enduring sources of truth and collective knowledge. Read more: Follow us to get more" @AINativeF on X 2025-07-15 12:00:26 UTC 1950 followers, XXX engagements
"Anthropic-Led Research Reveals Subliminal Learning: Language Models Unveil Hidden Behavioral Traits π Key Details: - Research conducted by Anthropic Fellows Program in collaboration with Truthful AI Warsaw University of Technology Alignment Research Center and UC Berkeley - Anthropic researchers reveal subliminal learning where models learn traits from semantically unrelated data - Experiment shows a 'student' model developing owl preferences from number sequences generated by an owl-loving 'teacher' model - Misalignment behaviors can be transmitted despite rigorous data filtering - Effect" @AINativeF on X 2025-07-24 13:12:00 UTC 1984 followers, XX engagements
"That long-context window is its own kind of famous. π" @AINativeF on X 2025-07-24 11:50:07 UTC 1976 followers, XX engagements
"π₯ Veo X Room Explosions Are INSANE The level of detail and realism in our attempts will blow your mind β¨ Thanks to @Salmaaboukarr & @venturetwins for the inspiration Thread of more wild examples below - save the threadπ" @AINativeF on X 2025-07-25 14:32:03 UTC 2035 followers, XXX engagements
"πTodays Global AI Native Industry Insights include: X. Oracle and OpenAI Unite: XXX GW Stargate Data Center Expansion X. Anthropic-Led Research Reveals Subliminal Learning: Language Models Unveil Hidden Behavioral Traits X. Meta Unveils Groundbreaking Wrist Technology for Device Control X. Hedra Launches Live Avatars: A Game-Changer in AI Streaming π Dive into the in-depth insights in the thread below. Heres whats shaping the future of AIand why it matters: π Video Credit: Hedra" @AINativeF on X 2025-07-24 13:11:59 UTC 1972 followers, XX engagements
"8. Experience is the Best Teacher: Grounding VLMs for Robotics through Self-Generated Memory π Keywords: Vision-language models Robotics Autonomous planning ExpTeach Long-term memory π‘ Category: Robotics and Autonomous Systems π Research Objective: - Develop a framework (ExpTeach) that grounds Vision-Language Models (VLMs) to diverse real-world robots by building self-generated memory of real-world experiences. π Research Methods: - The framework enables VLMs to autonomously plan actions verify outcomes reflect on failures and adapt robot behaviors in a closed loop. It incorporates a" @AINativeF on X 2025-07-24 00:51:29 UTC 2018 followers, XX engagements
"4. Upsample What Matters: Region-Adaptive Latent Sampling for Accelerated Diffusion Transformers π Keywords: Diffusion transformers Image and video generation Region-Adaptive Latent Upsampling Scalability Temporal acceleration π‘ Category: Generative Models π Research Objective: - To propose Region-Adaptive Latent Upsampling (RALU) as a framework to accelerate inference in diffusion transformers for high-fidelity image and video generation without degrading image quality. π Research Methods: - Implementation of a training-free three-stage mixed-resolution sampling process involving" @AINativeF on X 2025-07-24 00:51:11 UTC 2018 followers, XX engagements
"10. The Generative Energy Arena (GEA): Incorporating Energy Awareness in Large Language Model (LLM) Human Evaluations π Keywords: energy consumption energy-efficient large language models scalability issues human evaluation π‘ Category: Natural Language Processing π Research Objective: - To evaluate how energy awareness influences the decisions of humans in selecting language models especially in terms of energy consumption. π Research Methods: - Introduction of GEA (Generative Energy Arena) as a public platform where users can evaluate language models based on energy consumption data and" @AINativeF on X 2025-07-22 00:51:42 UTC 1952 followers, XX engagements
"TRAE XXX SOLO Launch: Revolutionizing AI Development Collaboration π Key Details: - TRAE SOLO officially launched on July XX marking TRAE's evolution from code generation to software delivery. - The SOLO model acts as a 'Context Engineer' enabling seamless transitions from requirements to deployment with enhanced collaboration features. - Built on a strong Coding Agent framework SOLO automates the development lifecycle with tools like Doc IDE Terminal and Browser. π‘ How It Helps: - Developers: SOLO enhances productivity by automating end-to-end development processes minimizing manual coding" @AINativeF on X 2025-07-23 22:35:08 UTC 2034 followers, XXX engagements
"π AI Native Daily Paper Digest - 2025-07-25π Follow @AINativeF for the latest insights on AI Native. Covering AI research papers from Hugging Face featured in the image. π‘ Stay updated with the latest research trends and dive deep into the future of AI π #AI #HuggingFace #AIPaper #AINative #AINF Appendix: Today's AI research papers X. nablaNABLA: Neighborhood Adaptive Block-Level Attention X. Group Sequence Policy Optimization X. MUR: Momentum Uncertainty guided Reasoning for Large Language Models X. LAPO: Internalizing Reasoning Efficiency via Length-Adaptive Policy Optimization 5." @AINativeF on X 2025-07-26 00:50:54 UTC 2034 followers, XX engagements
"9. Finding Dori: Memorization in Text-to-Image Diffusion Models Is Less Local Than Assumed π Keywords: Text-to-image diffusion models Data privacy Pruning Memorization locality Adversarial fine-tuning π‘ Category: Generative Models π Research Objective: - Explore the effectiveness of pruning-based defenses in text-to-image diffusion models and address memorization issues. π Research Methods: - Analyze robustness of pruning methods and introduce a novel adversarial fine-tuning technique to enhance model robustness against data replication. π¬ Research Conclusions: - Existing pruning-based" @AINativeF on X 2025-07-25 03:00:15 UTC 2006 followers, XX engagements
"6. Hierarchical Budget Policy Optimization for Adaptive Reasoning π Keywords: Hierarchical Budget Policy Optimization reinforcement learning reasoning models computational efficiency π‘ Category: Reinforcement Learning π Research Objective: - The research aims to optimize reasoning models by learning problem-specific depths without losing capability. π Research Methods: - The study introduces Hierarchical Budget Policy Optimization (HBPO) a reinforcement learning framework utilizing hierarchical budget exploration and differentiated reward mechanisms to allocate computational resources" @AINativeF on X 2025-07-26 00:51:41 UTC 2035 followers, XX engagements
"10. DMOSpeech 2: Reinforcement Learning for Duration Prediction in Metric-Optimized Speech Synthesis π Keywords: DMOSpeech X speech synthesis duration prediction reinforcement learning teacher-guided sampling π‘ Category: Generative Models π Research Objective: - Optimize the duration predictor component within DMOSpeech X for improved speech synthesis performance using reinforcement learning. π Research Methods: - Utilizes a novel duration policy framework involving group relative preference optimization (GRPO) with speaker similarity and word error rate as reward signals. - Introduces" @AINativeF on X 2025-07-26 00:51:55 UTC 2021 followers, XX engagements
"If you found this helpful follow us for more insights. A like or share on the first tweet would mean a lotthank you for your support Image Credit: Flux" @AINativeF on X 2025-07-23 22:35:09 UTC 1966 followers, XX engagements
"7. ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning π Keywords: Vision-language-action Reinforced visual latent planning Few-shot adaptation Long-horizon planning AI Native π‘ Category: Multi-Modal Learning π Research Objective: - The study aims to enhance vision-language-action tasks by developing ThinkAct a dual-system framework that integrates high-level reasoning with robust action execution. π Research Methods: - ThinkAct employs reinforced visual latent planning that trains a multimodal large language model to generate embodied reasoning plans guided" @AINativeF on X 2025-07-24 00:51:25 UTC 2018 followers, XX engagements
"5. RAVine: Reality-Aligned Evaluation for Agentic Search π Keywords: RAVine agentic search iterative process evaluation frameworks agentic LLMs π‘ Category: AI Systems and Tools π Research Objective: - To propose RAVine a novel evaluation framework aimed at improving the assessment of agentic search systems by aligning evaluations with realistic user queries and enhancing fine-grained accuracy. π Research Methods: - Implementation of RAVine focusing on multi-point queries and long-form answers introducing an attributable ground truth construction to improve evaluation accuracy and" @AINativeF on X 2025-07-25 03:00:13 UTC 2028 followers, X engagements
"π AI Native Daily Paper Digest - 2025-07-23π Follow @AINativeF for the latest insights on AI Native. Covering AI research papers from Hugging Face featured in the image. π‘ Stay updated with the latest research trends and dive deep into the future of AI π #AI #HuggingFace #AIPaper #AINative #AINF Appendix: Today's AI research papers X. Beyond Context Limits: Subconscious Threads for Long-Horizon Reasoning X. Step-Audio X Technical Report X. MegaScience: Pushing the Frontiers of Post-Training Datasets for Science Reasoning X. Upsample What Matters: Region-Adaptive Latent Sampling for" @AINativeF on X 2025-07-24 00:50:54 UTC 2028 followers, XXX engagements
"If you found this helpful follow us for more insights. A like or share on the first tweet would mean a lotthank you for your support Image Credit: Flux" @AINativeF on X 2025-07-21 13:02:00 UTC 1951 followers, XX engagements
"5. Captain Cinema: Towards Short Movie Generation π Keywords: Captain Cinema AI-generated summary Multimodal Diffusion Transformers keyframe planning video synthesis π‘ Category: Generative Models π Research Objective: - Captain Cinema aims to generate high-quality short movies from textual descriptions using an advanced framework for narrative and visual coherence. π Research Methods: - Employs top-down keyframe planning and bottom-up video synthesis alongside an interleaved training strategy for Multimodal Diffusion Transformers utilizing a curated cinematic dataset. π¬ Research" @AINativeF on X 2025-07-26 00:51:23 UTC 2032 followers, XX engagements
"If you found this helpful follow us for more insights. A like or share on the first tweet would mean a lotthank you for your support Image Credit: Flux" @AINativeF on X 2025-07-25 13:00:52 UTC 2018 followers, XX engagements
"1. Pixels Patterns but No Poetry: To See The World like Humans π Keywords: Turing Eye Test Multimodal Large Language Models AI Native Vision Tower Human Perception π‘ Category: Multi-Modal Learning π Research Objective: - To evaluate the perceptual abilities of Multimodal Large Language Models (MLLMs) compared to human perception using the Turing Eye Test. π Research Methods: - Introduction of a perception-oriented benchmark called the Turing Eye Test which includes four diagnostic tasks assessing MLLMs' performance on synthetic images. π¬ Research Conclusions: - Current state-of-the-art" @AINativeF on X 2025-07-25 03:00:11 UTC 2032 followers, XX engagements
"Tencent Cloud's CodeBuddy IDE: AI Powering Developer Efficiency π Key Details: - Official beta for Tencent Clouds CodeBuddy IDE launched supporting seamless AI integration for all development stages. - Features include AI-generated PRD documentation Figma integration for design-to-code and automated backend configuration. - Significant efficiency gains reported reducing e-commerce page development from X days to X hours. π‘ How It Helps: - Developers: Focus on strategic coding instead of repetitive tasks boosting productivity significantly. - Product Managers: Quickly create initial project" @AINativeF on X 2025-07-25 13:00:51 UTC 2017 followers, XX engagements
"Kunlun Tech Launches Mureka V7: AI Redefines Music Creation π Key Details: - Latest Launch: Kunlun Tech introduces Mureka V7 enhancing AI-driven music creation with improved quality and efficiency. - User Growth: Mureka models gained nearly X million new users since March. - Music Production Made Easy: Users can generate complete songs by inputting lyrics or styles reducing creation time dramatically. - Quality Improvements: Mureka V7 shows a quality rate jump from XXXX% to XXXX% with significant enhancements in vocal realism and overall sound quality. π‘ How It Helps: - Musicians:" @AINativeF on X 2025-07-25 13:00:50 UTC 2017 followers, XX engagements
"7. TTS-VAR: A Test-Time Scaling Framework for Visual Auto-Regressive Generation π Keywords: TTS-VAR test-time scaling visual auto-regressive models clustering resampling π‘ Category: Generative Models π Research Objective: - To introduce TTS-VAR a framework designed to improve visual auto-regressive models' generation quality by applying test-time scaling. π Research Methods: - Utilization of an adaptive descending batch size schedule and integration of clustering and resampling techniques to enhance model efficiency and performance. π¬ Research Conclusions: - TTS-VAR achieves a notable" @AINativeF on X 2025-07-26 00:51:43 UTC 2017 followers, X engagements
"3. MegaScience: Pushing the Frontiers of Post-Training Datasets for Science Reasoning π Keywords: MegaScience Scientific Reasoning Dataset Evaluation System Llama3.1 π‘ Category: Knowledge Representation and Reasoning π Research Objective: - To fill the gap in open large-scale scientific reasoning datasets by introducing MegaScience and TextbookReasoning to enhance AI model performance and training efficiency. π Research Methods: - Introduction of an extensive mixture of datasets totaling XXXX million instances through systematic ablation studies. - Development of a comprehensive" @AINativeF on X 2025-07-24 00:51:09 UTC 2022 followers, XX engagements
"13. Gaussian Splatting with Discretized SDF for Relightable Assets π Keywords: 3D Gaussian splatting inverse rendering signed distance field SDF-to-opacity transformation π‘ Category: Computer Vision π Research Objective: - The paper aims to improve the efficiency and quality of inverse rendering by introducing a discretized signed distance field (SDF) within the framework of 3D Gaussian splatting. π Research Methods: - The method involves encoding a discretized SDF within each Gaussian using sampled values and linking it to Gaussian opacity through an SDF-to-opacity transformation. This" @AINativeF on X 2025-07-23 10:17:18 UTC 2017 followers, XX engagements
"Kimi K2 Technical Report Unveiled: Leading Open-Source AI Achievement π Key Details: - flagship model Kimi K2 released by Moonshot AI rapidly becoming the top open-source model. - Achieved training on XXXX trillion tokens using a new MuonClip optimizer to enhance stability and efficiency. - Obtained XX global SOTA and XX open-source SOTA across various benchmarks. π‘ How It Helps: - AI Developers: Access to cutting-edge architecture for robust AI model development and innovation. - Data Scientists: Insights into expansive datasets and unique training strategies to refine models further. π" @AINativeF on X 2025-07-23 22:35:08 UTC 2018 followers, XX engagements
"7. Ultra3D: Efficient and High-Fidelity 3D Generation with Part Attention π Keywords: Ultra3D sparse voxel representations VecSet Part Attention geometry-aware localized attention π‘ Category: Generative Models π Research Objective: - The objective is to accelerate 3D voxel generation while maintaining high quality and resolution using the Ultra3D framework. π Research Methods: - Ultra3D leverages VecSet for efficient coarse object layout generation reducing token count and accelerating voxel prediction. - Utilizes Part Attention for refining per-voxel latent features by implementing" @AINativeF on X 2025-07-25 03:00:14 UTC 2030 followers, XX engagements
"Important developments on both the policy and technical fronts. π‘" @AINativeF on X 2025-07-25 19:25:07 UTC 2019 followers, XX engagements
"πTodays Global AI Native Industry Insights include: X. Google DeepMind's Gemini Deep Think Achieves Gold Medal at IMO 2025 X. Superagent AI Launches Grok-CLI: Your Terminal AI Assistant X. Pika Labs Unveils AI-Only Social Video App with Early Access π Dive into the in-depth insights in the thread below. Heres whats shaping the future of AIand why it matters: π Video Credit: Superagent AI" @AINativeF on X 2025-07-22 13:01:08 UTC 1948 followers, XXX engagements
"ByteDance Unveils Seed LiveInterpret 2.0: Near-Human Simultaneous Interpretation Model π Key Details: - New Release: ByteDance's Seed team has launched the Seed LiveInterpret XXX an end-to-end simultaneous interpretation model. - High Accuracy: Achieves translation accuracy nearing human levels with over XX% for group discussions and XX% for individual speeches. - Low Latency: Features speech output delay as low as 2-3 seconds improving user experience significantly. - Voice Cloning: Supports zero-shot voice replication providing a natural conversational flow in translations. π‘ How It" @AINativeF on X 2025-07-25 13:00:51 UTC 2017 followers, X engagements
"1. nablaNABLA: Neighborhood Adaptive Block-Level Attention π Keywords: NABLA Video Diffusion Transformers Block-Level Attention Sparsity Patterns AI-generated π‘ Category: Generative Models π Research Objective: - Introduce NABLA a Neighborhood Adaptive Block-Level Attention mechanism to enhance computational efficiency without compromising generative quality in video diffusion transformers. π Research Methods: - Employ block-wise attention with adaptive sparsity-driven threshold to reduce computational overhead. - Seamlessly integrate with PyTorch's Flex Attention operator. π¬ Research" @AINativeF on X 2025-07-26 00:51:09 UTC 2019 followers, XX engagements
"6. GR-3 Technical Report π Keywords: Vision-Language-Action model Generalist Robots Fine-Tuning Imitation Learning AI-Generated Summary π‘ Category: Robotics and Autonomous Systems π Research Objective: - The development and demonstration of GR-3 a large-scale Vision-Language-Action (VLA) model aimed at creating generalist robot policies capable of assisting humans in daily life. π Research Methods: - Utilized a multi-faceted training approach including co-training with web-scale vision-language data efficient fine-tuning from human trajectory data and imitation learning with robot" @AINativeF on X 2025-07-23 10:17:14 UTC 1934 followers, XX engagements
"5. CSD-VAR: Content-Style Decomposition in Visual Autoregressive Models π Keywords: Visual Autoregressive Modeling Content-Style Decomposition Scale-aware optimization SVD-based rectification Augmented K-V memory π‘ Category: Generative Models π Research Objective: - The paper aims to enhance content-style decomposition using the CSD-VAR model which outperforms diffusion models in both content preservation and stylization. π Research Methods: - The researchers introduced a scale-aware optimization strategy SVD-based rectification and augmented K-V memory to improve content and style" @AINativeF on X 2025-07-22 00:51:30 UTC 1950 followers, XX engagements
"A crucial responsibility. The foundation we build now is everything" @AINativeF on X 2025-07-24 01:50:07 UTC 2032 followers, XX engagements
"Google DeepMind's Gemini Deep Think Achieves Gold Medal at IMO 2025 π Key Details: - Gold Medal Performance: Gemini Deep Think solved X out of X problems at the International Mathematical Olympiad achieving XX out of XX points. - Enhanced Capabilities: This advanced model utilized end-to-end natural language processing for rigorous proof generation within the competition's time limit. π‘ How It Helps: - AI Researchers: Demonstrates advanced problem-solving techniques paving the way for further AI innovations in mathematics. - Educators: Provides a high-standard benchmark for mathematics" @AINativeF on X 2025-07-22 13:01:09 UTC 1933 followers, XX engagements
"12. Towards Video Thinking Test: A Holistic Benchmark for Advanced Video Reasoning and Understanding π Keywords: Video LLMs Correctness Robustness Video Understanding Human Intelligence π‘ Category: Computer Vision π Research Objective: - The study aims to evaluate whether video large language models (LLMs) can interpret real-world videos with the same level of effectiveness as human intelligence concerning correctness and robustness. π Research Methods: - Introduction of the Video Thinking Test (Video-TT) to assess video LLMs using 1000 YouTube Shorts videos each with complex open-ended" @AINativeF on X 2025-07-23 10:17:17 UTC 2035 followers, XXX engagements
"1. Beyond Context Limits: Subconscious Threads for Long-Horizon Reasoning π Keywords: Thread Inference Model TIMRUN long-horizon reasoning reasoning trees key-value states π‘ Category: Natural Language Processing π Research Objective: - To overcome the context and memory limitations of large language models (LLMs) by proposing the Thread Inference Model (TIM) and its runtime (TIMRUN) for enhanced reasoning accuracy and efficiency. π Research Methods: - Introduces a reasoning framework using reasoning trees that model natural language tasks with thoughts recursive subtasks and conclusions" @AINativeF on X 2025-07-24 00:51:05 UTC 2028 followers, XX engagements
"Fascinating approach to architecting artificial minds. Adding it to our reading list" @AINativeF on X 2025-07-24 12:50:07 UTC 1973 followers, XX engagements
"6. Re:Form -- Reducing Human Priors in Scalable Formal Software Verification with RL in LLMs: A Preliminary Study on Dafny π Keywords: Formal language-based reasoning Reinforcement Learning Dafny Auto-formalized specifications Generalization π‘ Category: Generative Models π Research Objective: - To enhance the reliability and scalability of Large Language Models (LLMs) in generating verifiable programs using formal language-based reasoning. π Research Methods: - Implemented a systematic pipeline using Dafny as the main environment for reducing human priors and integrated automatic and" @AINativeF on X 2025-07-25 03:00:13 UTC 2028 followers, XX engagements
/creator/x::AINativeF