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@jiqizhixin Avatar @jiqizhixin 机器之心 JIQIZHIXIN

机器之心 JIQIZHIXIN posts on X about university of, voxels, learn to, compact the most. They currently have XXXXXX followers and XXX posts still getting attention that total XXXXX engagements in the last XX hours.

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Social category influence technology brands XXXX% nfts #2708 stocks XXXX% travel destinations XXXX% countries XXXX% finance XXXX% social networks XXXX%

Social topic influence university of 1.62%, voxels #15, learn to 1.08%, compact 1.08%, shanghai 1.08%, affordable 1.08%, robot 1.08%, demo 0.54%, instead of #617, microsoft XXXX%

Top accounts mentioned or mentioned by @justinechoes @casper_hansen_ @teknium1 @openai @rfsharko @ssoni83588 @nlituanie @aiml4health @kourouklides @gut_ai_f @googleclouds @wzihanw @ruipeterpan @polynoamial @deepseekai @furongh @bangan @sichengzhuml @xiaoyuliu1231 @google

Top assets mentioned Voxels (voxels) Microsoft Corp. (MSFT)

Top Social Posts #

Top posts by engagements in the last XX hours

"What is AGI Dan Hendrycks Yoshua Bengio Eric Schmidt Gary Marcus Max Tegmark and many others just released A Definition of AGI. Basically AGI is an AI that can match or exceed the cognitive versatility and proficiency of a well-educated adult. And no surprise GPT-4 and GPT-5 perform very poorly on the ten core cognitive components of their standard"
X Link @jiqizhixin 2025-10-17T02:58Z 10.4K followers, 15.3K engagements

"This is huge A UCLA team managed to build an optical generative model that runs on light instead of GPUs. In their demo a shallow encoder maps noise into phase patterns which a free-space optical decoder then transforms into imagesdigits fashion butterflies faces even Van Goghstyle artwithout any computation during synthesis. ⚡ The results rival digital diffusion models pointing to ultra-fast energy-efficient AI powered by photonics. Optical generative models Nature Paper:"
X Link @jiqizhixin 2025-10-02T05:09Z 10.4K followers, 174.6K engagements

"How can we make text-to-speech systems speak the worlds dialects Tsinghua and Giant Network build DiaMoE-TTS a unified IPA-based framework that brings scalable and expressive dialect TTS to life. 🎯 Key innovations: - Standardizes phonetic representations to resolve orthography & pronunciation ambiguity - Uses a dialect-aware Mixture-of-Experts to model phonological variation - Adapts fast to new dialects via LoRA and Conditioning Adapters Results: natural expressive speech even zero-shot synthesis on unseen dialects and niche domains like Peking Opera with just a few hours of data"
X Link @jiqizhixin 2025-10-17T08:28Z 10.4K followers, 1577 engagements

"Nice survey on Reinforcement Learning. This comprehensive survey covers XXX papers and maps how RL empowers LLMs across their full lifecycle from pre-training and alignment fine-tuning to reinforced reasoning where models learn to think better through verifiable feedback. It highlights RL with Verifiable Rewards (RLVR) as a key step toward more reliable interpretable and self-improving AI systems while cataloging datasets benchmarks and open-source frameworks that drive the field. 📚 A must-read for those exploring the frontier of RL-enhanced reasoning and alignment in next-gen LLMs"
X Link @jiqizhixin 2025-10-07T07:32Z 10.3K followers, XXX engagements

"Huge LLMs can now think longer without burning quadratic compute Mila Microsoft and others just introduced Markovian Thinking a paradigm that decouples reasoning length from context size turning LLM reasoning into a linear-compute process. Their system Delethink trains models in fixed-size reasoning chunks: at each boundary the model writes a compact textual state resets the context and seamlessly continues reasoning. Results are striking: an R1-Distill 1.5B model thinks up to 24K tokens with only 8K context outperforming LongCoT-RL trained on full 24K sequences at X lower compute cost (7 vs."
X Link @jiqizhixin 2025-10-10T01:56Z 10.3K followers, 45K engagements

"Robots can now learn to act better through trial and error A new study from Tsinghua Shanghai Qi Zhi Institute and Zhongguancun Academy puts Reinforcement Learning (RL) to the test for Vision-Language-Action (VLA) models. Unlike standard supervised fine-tuning (SFT) which struggles with compounding errors RL directly optimizes for task success. The researchers built a comprehensive benchmark to study how RL affects generalization across: 👀 Visual shifts 🧩 Semantic understanding 🦾 Action execution Key findings: - RL (especially PPO) boosts semantic and execution robustness - Maintains"
X Link @jiqizhixin 2025-10-14T07:46Z 10.3K followers, XXX engagements

"Struggling to deploy massive Mixture-of-Experts (MoE) models without system instability EaaS is a novel serving system that makes MoE deployment efficient scalable and robust. It works by disaggregating MoE modules into independent stateless microservices. This clever design enables fine-grained resource scaling and provides inherent fault tolerance. The system is powered by a high-performance CPU-free communication library to ensure minimal overhead. The outcome is a system that saves up to XXXX% of computing resources by adapting to traffic and suffers less than a X% throughput reduction"
X Link @jiqizhixin 2025-10-15T02:28Z 10.3K followers, 1114 engagements

"📬 #PapersAccepted by Jiqizhixin Our report: Expert-as-a-Service: Towards Efficient Scalable and Robust Large-scale MoE Serving National University of Singapore Shanghai Qiji Zhifeng Co. Ltd. and others Paper:"
X Link @jiqizhixin 2025-10-15T02:28Z 10.3K followers, XXX engagements

"📬 #PapersAccepted by Jiqizhixin Our report: LLaVA-OneVision-1.5: Fully Open Framework for Democratized Multimodal Training LLaVA-OneVision Community Contributors Code: Paper: Model & data: Demo:"
X Link @jiqizhixin 2025-10-15T08:30Z 10.3K followers, XXX engagements

"What if 3D models could be generated with precise cross-modal controlbeyond just text or images Tencent presents Hunyuan3D-Omni a unified framework that accepts point clouds voxels bounding boxes and skeletal priors enabling fine-grained controllable 3D asset creation. Built for games film and design. Model available on Hugging Face"
X Link @jiqizhixin 2025-10-04T01:05Z 10.4K followers, 1107 engagements

"Can autonomous driving think like it sees not just reason symbolically Alibaba and other propose a spatio-temporal Chain-of-Thought (CoT) that lets visual language models (VLMs) reason visually generating imagined future frames to plan trajectories. By unifying visual generation + understanding the model acts as a world simulator predicting how the scene evolves over time not just describing it. 📈 Results show stronger visual reasoning and planning moving autonomous driving beyond text-based logic toward true simulation-based intelligence. This paper has been accepted as a NeurIPS 2025"
X Link @jiqizhixin 2025-10-07T03:47Z 10.3K followers, XXX engagements

"Yes it turns out diffusion models can learn from feedback as effectively as language models do with RL Tsinghua NVIDIA and Stanford introduced Diffusion Negative-aware FineTuning (DiffusionNFT) a new online reinforcement learning paradigm that finally makes RL practical for diffusion models. Instead of struggling with intractable likelihoods or reverse-sampling hacks DiffusionNFT works directly on the forward process via flow matching contrasting positive vs. negative generations to guide improvement. ✨ Key perks: - Works with any black-box solver no likelihood estimation needed. - CFG-free"
X Link @jiqizhixin 2025-10-10T03:58Z 10.3K followers, 27K engagements

"Is building a state-of-the-art Large Multimodal Model (LMM) from scratch prohibitively expensive LLaVA-OneVision-1.5 says no. It's a family of open efficient and reproducible LMMs that deliver top-tier performance on a budget. The team developed a complete end-to-end framework including massive curated datasets (85M for pre-training 22M for instruction tuning) enabling training for under $16000. The results are stunning: - The 8B model outperforms Qwen2.5-VL-7B on XX of XX benchmarks. - The 4B model surpasses Qwen2.5-VL-3B on all XX benchmarks. This work democratizes access to building"
X Link @jiqizhixin 2025-10-15T08:30Z 10.3K followers, 1251 engagements

"Can diffusion-based LLMs outpace traditional autoregressive models ⚡🧠 Meet dInfer the first efficient modular framework for inference on diffusion-based large language models (dLLMs) a new generation of parallel text generators. dInfer breaks inference into four key modules: - Model core architecture integration - Diffusion iteration manager orchestrates denoising steps - KV-cache manager optimizes memory reuse - Decoding strategy balances speed and quality With both algorithmic and system-level optimizations dInfer hits 1100 tokens/sec on HumanEval and 800+ tokens/sec across benchmarks on"
X Link @jiqizhixin 2025-10-16T03:22Z 10.3K followers, XXX engagements

"📬 #PapersAccepted by Jiqizhixin Our report: RAPID Hand: A Robust Affordable Perception-Integrated Dexterous Manipulation Platform for Generalist Robot Autonomy Sun Yat-sen University University of California Merced CASIA Paper: Project: Code:"
X Link @jiqizhixin 2025-10-17T03:12Z 10.3K followers, XXX engagements

"📬 #PapersAccepted by Jiqizhixin Our report: GeoSVR: Taming Sparse Voxels for Geometrically Accurate Surface Reconstruction Beihang University Rawmantic AI and others Paper: Project: Code:"
X Link @jiqizhixin 2025-10-15T02:18Z 10.4K followers, XXX engagements

"📬 #PapersAccepted by Jiqizhixin Our report: RiskPO: Risk-based Policy Optimization via Verifiable Reward for LLM Post-Training Peking University Paper: Code:"
X Link @jiqizhixin 2025-10-17T03:57Z 10.4K followers, XXX engagements

"📬 #PapersAccepted by Jiqizhixin Our report: VIR-Bench: Evaluating Geospatial and Temporal Understanding of MLLMs via Travel Video Itinerary Reconstruction Waseda University CyberAgent and others Paper: Code:"
X Link @jiqizhixin 2025-10-17T08:14Z 10.4K followers, XXX engagements

"Ever wondered how LLMs evolve from predicting the next token to following your instructions Post-training 101: A hitchhiker's guide into LLM post-training This is a new guide breaks down the basics of LLM post-training covering the full journey from pre-training to instruction tuning: 🔹 Transitioning from language modeling to instruction following 🔹 Supervised Fine-Tuning (SFT) data curation objectives and losses 🔹 Reinforcement Learning methods RLHF RLAIF RLVR and how reward models work 🔹 Evaluation frameworks for measuring post-training quality Link:"
X Link @jiqizhixin 2025-10-12T02:07Z 10.4K followers, 34.5K engagements

"Are Gaussian Splatting's limitations holding back the future of 3D surface reconstruction 🤔 Enter GeoSVR a novel framework that leverages sparse voxels to create stunningly accurate detailed and complete 3D surfaces. By using a Voxel-Uncertainty Depth Constraint and Sparse Voxel Surface Regularization GeoSVR overcomes common challenges in the field ensuring geometric consistency and sharp details. Experiments show it outperforms existing methods in accuracy and completeness especially in difficult scenarios"
X Link @jiqizhixin 2025-10-15T02:18Z 10.4K followers, 1290 engagements

"Say goodbye to GRPOGVPO is here GVPO (Group Variance Policy Optimization) proposed by a NeurIPS 2025 paper from HKUST(GZ) and Zuoyebang is a new algorithm that tackles the instability plaguing advanced post-training methods like GRPO. GVPO introduces an analytical solu tion to the KL-constrained reward maximization problem and bakes it directly into its gradient weights aligning every update with the true optimal policy. Why it matters: - Stable by design guarantees a unique optimal solution - Flexible sampling no on-policy or importance sampling constraints - Physically intuitive the"
X Link @jiqizhixin 2025-10-16T03:53Z 10.4K followers, 12.6K engagements

"How can we make generalist robot hands both dexterous and affordable RAPID Hand is a co-designed hardware & software platform with: - 20-DoF compact robotic hand - Wrist vision + fingertip tactile + proprioception (sub-7 ms latency) - High-DoF teleoperation with stable retargeting Trained diffusion policies show state-of-the-art performance proving RAPID Hand enables high-quality low-cost data collection for multi-fingered manipulation"
X Link @jiqizhixin 2025-10-17T03:12Z 10.4K followers, XXX engagements

"RL keeps evolving Now you can teach LLMs to reason better by rewarding risk-taking. Risk-based Policy Optimization (RiskPO) is a new reinforcement learning framework for post-training LLMs. Instead of averaging rewards like GRPO RiskPO uses a Mixed Value-at-Risk objective to: - Emphasize rare but informative reasoning paths - Prevent entropy collapse and overconfidence - Encourage deeper exploration Plus a smart bundling scheme enriches feedback for more stable training. Results: Big gains in math multimodal and code reasoning beating GRPO on both Pass@1 and Pass@k"
X Link @jiqizhixin 2025-10-17T03:57Z 10.4K followers, 6208 engagements

"How well can multimodal LLMs understand long-distance travel videos Enter VIR-Bench a new benchmark with XXX real-world travel videos that challenges models to reconstruct itineraries and reason over extended geospatial-temporal trajectories. 🚗 Why it matters: mastering long-range video reasoning is key for embodied-AI planning and autonomous navigation. Findings: even top MLLMs struggle revealing major gaps in long-horizon understanding. A prototype travel agent built on VIR-Bench shows clear performance gains proving the benchmarks real-world value"
X Link @jiqizhixin 2025-10-17T08:14Z 10.4K followers, 1065 engagements

"📬 #PapersAccepted by Jiqizhixin Our report: DiaMoE-TTS: A Unified IPA-Based Dialect TTS Framework with Mixture-of-Experts and Parameter-Efficient Zero-Shot Adaptation Tsinghua and Giant Network Paper: Code: Checkpoint: Dataset:"
X Link @jiqizhixin 2025-10-17T08:28Z 10.4K followers, XXX engagements

"Today's #1 Paper on Hugging Face Agentic Entropy-Balanced Policy Optimization (AEPO) With this method we can train smarter and more capable AI web agents without their learning processes collapsing. Its a reinforcement learning (RL) algorithm that addresses a key instability issue. Existing methods often over-rely on entropy (uncertainty) leading to training failures. AEPO intelligently balances this entropy during both exploration and policy updates. It uses a dynamic rollout that prevents the agent from getting stuck in uncertain loops and a novel optimization technique to learn from tricky"
X Link @jiqizhixin 2025-10-17T12:25Z 10.4K followers, 1250 engagements

"Agentic Entropy-Balanced Policy Optimization Renmin University of China Kuaishou Technology Paper: Code:"
X Link @jiqizhixin 2025-10-17T12:25Z 10.4K followers, XXX engagements