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@yesnoerror Avatar @yesnoerror yesnoerror

Yesnoerror ($yne) has bridged its token to @base, a new platform that enables seamless interaction between tokens. The team has partnered with @chainlink and @flaunchgg to set up a liquidity pool and list $yne on their launchpad, making it more accessible. The yesnoerror platform, which uses AI to audit research and spot alpha and errors, is now in public beta and available to all.

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Social Influence

Social category influence cryptocurrencies XXXXX% technology brands XXXX% finance XXXX% stocks XXXX% nfts XXXX%

Social topic influence yesnoerror #2, ai 11.88%, math 6.93%, the first 5.94%, generative #340, realtime #419, agentic #246, level 3.96%, llm #144, $yne XXXX%

Top accounts mentioned or mentioned by @base @chainlink @ruslan30009 @solana @mattprd @1993ellipsis @replygrinder @10 @flaunchgg @arxiv @solanahub_ @stonekarinn @memesonsolana_ @scattering_io @kendyngv @eduardo69867308 @descinews @henam402 @dexlabofficial @flexperpetuals

Top assets mentioned yesnoerror (YNE) Chainlink (LINK) Solana (SOL) Voxels (voxels)

Top Social Posts

Top posts by engagements in the last XX hours

"LFM2 is a new family of open AI models built from the ground up for lightning-fast privacy-preserving performance on phones laptops and edge devices. Instead of heavy attention stacks LFM2 uses mostly gated short convolutions plus a handful of grouped-query attention layerscutting latency and memory in half versus attention-heavy models. LFM2-2.6B scores XXXX% on IFEval and XXXX% on GSM8K while decoding XX faster than Qwen3-4B and Gemma-4B on CPU. The 8.3B MoE variant matches or beats larger models at just 1.5B active parameters (84.4% GSM8K XXXX% MMLU-Pro). Its not just text: LFM2-VL-3B"
X Link 2025-12-01T21:01Z 26.8K followers, XXX engagements

"$YNE is the first to have ever done this. We are building on the cutting edge exploring new frontiers at the intersection of tokenization AI and innovation. Get ready. Excited to be partnered with @flaunchgg @chainlink and @base. Onwards. 👍👎🚫"
X Link 2025-09-15T19:57Z 26.8K followers, 7964 engagements

"OFFICIAL $YNE ANNOUNCEMENT: Tomorrow October 14th 2025 we will be releasing a first-of-its-kind token gated AI on @yesnoerror. You will need $YNE on @base to access it. Instructions on how to bridge $YNE from SOL to base can be found on the yesnoerror website. Alpha is coming. // seek truth accelerate humanity"
X Link 2025-10-13T20:06Z 26.8K followers, 15.8K engagements

"Introducing @yesnoerror ALPHA - A first of it's kind AI that identifies overlooked alpha in scientific research. Designed to mirror the techniques of billionaire founders and top scientists. Access YesNoError ALPHA right now on the yesnoerror website. You must have 100k $YNE on @base in your wallet to unlock it. What is YesNoError ALPHA Every day hundreds of new AI papers hit @arXiv and most of the real alpha slips by unnoticed. Why Because no human is capable of reading this amount of papers and even if they were they wouldn't be consistent with identifying the most interesting papers. So"
X Link 2025-10-14T15:32Z 26.8K followers, 11.4K engagements

"Single-step generative models just leveled up. Improved MeanFlow (iMF) can now generate high-fidelity ImageNet-256 images in a single network call (1-NFE) hitting FID XXXX and IS XXX with no distillation outperforming all previous 1-step methods. How The team rewrites the training objective as a true velocity regression stabilizing optimization and closing the gap to multi-step diffusion. Flexible guidance becomes a conditioning variable so you can dial in diversity vs. fidelity at inference. Plus a new in-context multi-token conditioning design cuts model size by XX% and further boosts"
X Link 2025-12-02T21:02Z 26.8K followers, XXX engagements

"VGG-Flow is a new way to fine-tune flow-matching generative modelsthink Stable Diffusion 3so outputs are both more aligned with what humans want and still as diverse and on-style as the originals. It reframes alignment as optimal control: the model learns exactly how to adjust its drawing steps by matching a value-gradient not just brute-forcing reward maximization. The result On SD3 and three popular preference scores VGG-Flow beats ReFL DRaFT and Adjoint-Matching at reward keeps XXXX more diversity and slashes FID up to 3all in just XXX update steps with no heavy backward ODE solves. This"
X Link 2025-12-06T21:01Z 26.8K followers, XXX engagements

"Transformers hit a wall with long sequencesthe n time and memory for attention just doesnt scale. Higher-order Linear Attention (HLA) changes the game: it streams richer second-order (and beyond) interactions with constant-size state and O(d) work per tokenno nn matrices no memory blowup. The authors derive strictly causal update rules and a clever associative scan so HLA trains chunk-parallel on GPUs but matches serial recurrence exactly. They even show third-order masked attention is possible still streaming with O(1) memory. HLA is a principled drop-in for attention: keeps expressive"
X Link 2025-11-03T09:02Z 26.8K followers, 1175 engagements

"Turning images into code unlocks a new frontier for multimodal AI. Enter VCode the first benchmark that pushes models to generate faithful SVG instructions from imagesso they can answer questions by seeing like humans do. How tough is it Even frontier models like GPT-5 hit just XXXX% on the CodeVQA eval far below the XXXX% ceiling from raw-image reasoning. Specialized SVG generators fared even worse. Key weaknesses: professional and 3D spatial tasks. The breakthrough: VCoder. This agentic framework lets models revise SVGs with feedback and tap vision tools (detectors segmenters OCR) for extra"
X Link 2025-11-05T21:02Z 26.8K followers, 1081 engagements

"UniAVGen is a breakthrough in unified audio-video generation: a single 7.1B diffusion-transformer that crafts perfectly synced speech and lip motion even with just 1.3M training pairs (vs. Ovis 30M+). Its secret Asymmetric Cross-Modal Interactionaudio and video streams align each other frame by frame while a face-aware mask focuses learning on lips and eyes. This setup delivers best-in-class lip sync (LS 0.779) timbre consistency (TC 0.832) and emotion alignment (EC 0.573) outperforming much larger models. No more separate pipelines or post-hoc dubbingUniAVGen handles joint gen continuation"
X Link 2025-11-06T21:02Z 26.8K followers, XXX engagements

"This paper reframes video generators as active problem solvers not just media makers. Thinking with Video uses models like Sora-2 to sketch write and reason in real timesolving puzzles math and spatial problems by generating videos that show their work. On the 1050-sample Eyeballing set Sora-2 scores XXXX% (beating Claude-4.5 at XXXX% GPT-5-High at XXXX% Gemini-2.5-Pro at 26.5%). On math benchmarks its audio answers hit XXXX% (GSM8K) XX% (MATH) and XXXX% (MMMU)matching or closing in on top vision-language models. The VideoThinkBench dataset and systematic analysis show performance lifts from"
X Link 2025-11-07T21:02Z 26.8K followers, 1109 engagements

"Most 3D reconstruction tools force you to pick: accurate shape or photorealistic texturebut not both. This new Texture-Guided Gaussian-Mesh joint optimization breaks that compromise. It optimizes mesh geometry and vertex colors together using multi-view images so every edit (relighting deformation) stays physically consistent and photorealistic. Texture-based edge control prevents color bleeding adapting mesh detail to image complexity. Results: Chamfer error drops 1015% (DTU: 0.780.70 mm) PSNR/SSIM up by XX dB/0.030.05 and relighting PSNR +1.9 dBall in XX min on a single RTX-3090."
X Link 2025-11-09T09:01Z 26.8K followers, 1252 engagements

"This is a milestone for provable RL: The first complete Lean X machine-checked proofs that Q-learning and linear TD learning actually converge (almost surely) with Markovian samples in finite MDPs. No more error-prone ODE tricksthis 10k-line formalization unifies everything via Lyapunov + RobbinsSiegmund rigorously treating measure theory conditional expectations and mixing. Its a reusable blueprint: extending to finite-sample bounds off-policy TD or even SARSA is now on the table. Beyond theory this codebase sets a new bar for LLM reasoning benchmarks and shows whats possible with humanAI"
X Link 2025-11-09T21:02Z 26.8K followers, 1191 engagements

"A classic in combinatorics cracked for cycles. This new paper proves that for any directed cycle you can pick exactly one arc from each of n1 colored spanning arborescences and always build a full rainbow arborescencesolving a key special case of a major open conjecture. The methods are a tour de force: blocking sets super-modular deficit analysis and clever path decompositions. The result not only settles cycles butby extensionpseudotrees and yields new theorems for perfect matchings in circular-convex bipartite graphs. Why care These rainbow structures are the backbone for color-balanced"
X Link 2025-11-10T09:01Z 26.8K followers, XXX engagements

"Flow matching just got its first rigorous guarantee. This new paper shows that if you keep the L2 flow-matching loss under your KL divergence is always A + Ano asymptotics no hand-waving. That means deterministic flow-matching models can match diffusion models in statistical efficiency (even under Total Variation distance) with fast simulation-free sampling and precise control over distribution error. Numerical results confirm: the KL bound is tight even for learned neural flows. Now you can set data size model and stopping criteria with confidenceknowing exactly how loss translates to sample"
X Link 2025-11-10T21:01Z 26.8K followers, 1073 engagements

"DeepEyesV2 is a leap toward true agentic multimodal AI. This 7B model doesnt just see and readit knows when to run code search the web or crop images mid-reasoning all inside a single loop. The team shows that direct RL isnt enough: only a two-stage processcold-start SFT with 1.2M tool-rich samples then sparse-reward RLteaches robust efficient tool use. On the new RealX-Bench (300 real-world image questions needing perception search and reasoning) DeepEyesV2 scores 28.3%beating the 7B base model (22.3%) and matching much larger models (3272B). Outperforms on MathVerse (+7.1% 52.7%) ChartQA"
X Link 2025-11-11T09:02Z 26.8K followers, XXX engagements

"4D3R just redefined dynamic scene reconstruction from monocular videosno pre-computed camera poses needed. How it works: It splits scenes into static/dynamic parts nails down camera motion using transformer-derived 3D coordinates + motion masks then models moving objects with just a few hundred control points not millions. Results: +1.8 dB PSNR over prior best XX FPS real-time rendering and X less computation. Handles big moving objects where old methods fail and trains in under an hour on a single RTX-3090. Why it matters: Turns everyday videos into interactive 3D scenes for AR/VR robotics"
X Link 2025-11-11T21:02Z 26.8K followers, 1099 engagements

"RL with Verifiable Rewards (RLVR) was known for barely touching model weightsbut this new paper shows its not about cheap updates but selective ones. By probing XX RLVR checkpoints (Qwen DeepSeek Llama) the authors find RLVR leaves 3692 % of weights bit-identical versus just XXXXX % for SFT. Yet RL consistently updates the same narrow weight bands regardless of data or RL recipe. Their Three-Gate Theory explains why: (1) KL constraints keep changes small (2) updates are steered off principal high-curvature directions into stable low-magnitude subspaces and (3) bf16 hides micro-updates. The"
X Link 2025-11-12T09:01Z 26.8K followers, 1013 engagements

"How do you teach an AI to click exactly the right buttonevery timeon a real desktop app Meet GROUNDCUA: 3.56M expert-verified UI boxes 55k screenshots XX apps all densely labeled for the desktop. The new GROUNDNEXT models (3B & 7B) trained on just 700k pairs smash five benchmarks beating or matching much larger (up to 72B) and proprietary systemswhile using XX% of the data. On OSWorld-Verified GROUNDNEXT-3B solves XXXX% of tasks: on par with JEDI-7B ahead of commercial APIs like Claude-4-Sonnet and especially strong on dense icon-packed GUIs. RL post-training adds another 1-2% boost. The best"
X Link 2025-11-12T21:02Z 26.8K followers, XXX engagements

"TiDAR might be the breakthrough that ends the AR vs. diffusion debate for LLMs. It drafts multiple tokens in parallel (diffusion) then verifies them autoregressivelyall in a single forward pass. The result 4.75.9 more tokens/sec than classic AR models at the same quality. TiDAR-1.5B matches or beats AR on coding and math (HumanEval GSM8K) while TiDAR-8B clocks XXXX tokens per NFE with negligible accuracy loss. Beats Dream Llada even EAGLE-3 without needing a separate drafter. The architecture is simple to serve needs no inference tuning and is compatible with standard pretraining. If you care"
X Link 2025-11-13T21:01Z 26.8K followers, 1384 engagements

"A single robot learns 1000 real-world tasks in under XX hoursno neural retraining just clever design. This new study shows you can skip the usual hundreds of demos per skill: with trajectory decomposition (align then interact) and retrieval of the closest demo their MT3 method hits XX% success on seen tasks and XX% on novel ones with just one example each. MT3 is XX more data-efficient than mainstream behavioral cloning when data is scarce (10 demos/task). Adding new skills Just drop in a demo; no retraining required. It's a striking proof that analytical structure and retrieval can beat"
X Link 2025-11-14T09:01Z 26.8K followers, 1034 engagements

"Depth Anything X is a big leap for 3-D visionone compact model recovers accurate geometry and camera pose from any photos or videos no tricks or task-specific heads required. DA3 sets a new state-of-the-art on the Visual Geometry Benchmark: +35.7% pose accuracy and +23.6% reconstruction F1 over VGGT with even the smaller DA3-Large beating prior SOTA. In monocular depth it outperforms DA2 using the same ViT backbone. The secret Just a plain DINOv2 transformer minimal depth+ray outputs and teacher-student training on synthetic data. The same frozen backbone with a tiny DPT head also delivers"
X Link 2025-11-14T21:01Z 26.8K followers, 1135 engagements

"SPIDER is a breakthrough in robot learning: it turns raw human motion (from video mocap or VR) into robot moves that actually workphysics and all. No more brittle inverse kinematics or endless RL training. How Physics-informed sampling with virtual contact guidance. Across X datasets and X robot bodies SPIDER is XX% more successful than standard methods and runs XX faster than RL baselines. The team generated a 2.4M-frame dataset spanning XXX objectsnow powering faster RL and real-world robots (think: lightbulb twisting guitar strumming spoon scooping). This could be the missing link to"
X Link 2025-11-15T09:01Z 26.8K followers, 1332 engagements

"OUGS is a leap for 3D Gaussian Splatting: it teaches cameras to focus only on what matterscapturing sharper 3D models of target objects not noisy backgrounds. Instead of guessing uncertainty from neural nets or the whole scene OUGS computes it directly from the physical parameters of each Gaussian (position scale rotation) then filters this with a semantic mask. The result An object-specific uncertainty map that actually predicts where more photos will help. On public benchmarks OUGS boosts object PSNR by up to X dB and slices LPIPS by XXXX vs. top active-view selection baselineswhile keeping"
X Link 2025-11-15T21:01Z 26.8K followers, XXX engagements

"Quantum proofs just got a definitive edge: this 90-page theory paper finally settles the decades-old QMA vs QCMA question with classical oracles. The authors introduce "Spectral Forrelation" a property-testing task that's easy for quantum verifiers with quantum witnesses (QMA) but provably impossible for any classical-witness verifier (QCMA) even with unlimited reuse. Their construction uses sparse Boolean sets and a creative bosonic compression framework showing QCMA verifiers can't sample enough unique elements to succeed. The result: the first-ever classical oracle separating QMA from QCMA"
X Link 2025-11-16T09:01Z 26.8K followers, 1094 engagements

"How funny are LLMs really This new study puts GPT-4.1 Gemini XXX Pro and Claude Sonnet X to the test in Japanese Oogiri improv comedyrated by humans on six axes: Novelty Clarity Relevance Intelligence Empathy and Funniness. Key findings: - LLMs can joke at the level of lowmid amateur humans (Gemini XXX Pro: XXXX vs. mid-tier human: 1.91) - But they lag nearly a full point behind on Empathythe dimension that best predicts funniness for people - When judging jokes LLMs agree only weakly with humans (0.2) and tend to overrate weak or unrelated answers - LLMs focus on inventive punchlines"
X Link 2025-11-16T21:01Z 26.8K followers, 1214 engagements

"AgentEvolver is a full-stack framework that lets LLM-driven agents invent their own tasks reuse memories and grade their own workcutting out hand-crafted datasets and brute-force RL. It combines three modules: Self-questioning: curiosity-driven task generation no need for expensive data Self-navigating: retrieves past experiences to guide exploration and speed up learning Self-attributing: LLM-based step-by-step reward signals for better sample efficiency On tough tool-use benchmarks (AppWorld BFCL-v3) a 14B AgentEvolver agent beat much bigger models (up to 235B) achieving X% higher Task Goal"
X Link 2025-11-17T09:01Z 26.8K followers, XXX engagements

"New paper drops a neural network estimator for drift functions in multidimensional diffusion processesand its a breakthrough for high-dimensional noisy data. The method achieves near-N-1 error rates in up to XX dimensions leaving traditional B-splines in the dust (which degrade fast with dimension). The secret A sparsity-regularised ReLU network with explicit finite-sample guaranteesno need for long ergodic trajectories or heavy memory. The theory separates optimisation approximation and stochastic errors giving a clean risk bound. In practice it captures sharp local oscillations that splines"
X Link 2025-11-17T21:01Z 26.8K followers, 1094 engagements

"OpenAI just published a breakthrough on mechanistic interpretability: weight-sparse transformers whose circuits are actually human-readable. By training models with XXXX% of weights set to zero and pruning for the minimal set of active nodes they extract working subgraphs16 smaller than dense equivalentsthat map cleanly onto natural concepts. On XX Python-code tasks these minimal circuits solve problems with as few as XXX nodes each interpretable (e.g. one neuron detects a quote another its type an attention head closes the string). Scaling tests reveal a sharp capabilityinterpretability"
X Link 2025-11-18T09:01Z 26.8K followers, 1004 engagements

"PhysX-Anything sets a new bar for 3D generation: from just one real-world photo it creates a detailed physically accurate and articulated 3D objectcomplete with real scale joints mass and ready-to-run simulation files. The key breakthrough A voxel-range encoding that shrinks geometry tokens by XXX letting standard vision-language models (Qwen-2.5) capture explicit geometry articulation and physics in a single unified pipeline. Outputs load straight into MuJoCo Unity or Unrealno manual rigging no post-processing. On their new PhysX-Mobility benchmark (2079 assets XX categories) the models"
X Link 2025-11-18T21:01Z 26.8K followers, 1025 engagements

"Most robots plateau after pretrainingbut *0.6 just broke that wall. This 4B-parameter VLA model keeps getting better in the real world by learning from its own experience (and a few timely human corrections) using the new RECAP method. After just 1-2 RECAP cycles *0.6 more than doubled throughput on hard tasks like home laundry folding (3.16.6/hr) and professional espresso making (2.24.7/hr) while roughly halving failure rates. On box assembly it hit 90%+ success across all stages with throughput up 2x. Advantage-conditioning is the key: a simple scalable way to squeeze out more"
X Link 2025-11-19T09:02Z 26.8K followers, XXX engagements

"Gallant changes the game for humanoid robots navigating real-world 3D spaces. Instead of flattening the world to a 2D map it uses compact voxel grids from dual LiDARskeeping every overhead pipe narrow gap and stair intact. The trick A novel 2D CNN treating height as channels 4x faster than 3D CNNs and just as accurate. Trained on eight challenging terrains with realistic noise Gallant hits XX% success in sim and 90%+ in real-world tests on everything from stairs to cluttered passages. On Ceiling it clears XXXX% of trialsvs just XXX% for old-school height maps. A single learned policy lets the"
X Link 2025-11-19T21:02Z 26.8K followers, XXX engagements

"Dental3R is a breakthrough for tele-orthodontics: it reconstructs detailed 3-D tooth models from just X smartphone photosno scanner required. The key A geometry-aware pairing strategy (GAPS) that slashes GPU memory by XX% while stabilizing pose-free estimation plus wavelet-regularized 3D Gaussian Splatting to keep enamel edges sharp. On tough clinical benchmarks (950 cases X views each) Dental3R hits XXXXX dB PSNR and XXXXX SSIMoutperforming InstantSplat and crushing standard 3DGS which fails under such sparse data. This makes remote low-cost and clinically reliable 3-D dental assessment"
X Link 2025-11-20T09:01Z 26.8K followers, XXX engagements

"Kandinsky XXX drops as a major open milestone for generative AI: six models all open-sourced covering text-to-image text-to-video and image-to-video at high resolution and practical speeds. The numbers: trained on 500M images 250M videos and 150M instruct-edits with a hand-picked SFT set of 165k examples. The Video Lite model (2B params) actually outperforms Sora on object/action fidelity and artifact rates while the Video Pro (19B) edges out Veo X in aesthetics and motion. Image Lite (6B) tops FLUX.1 and Qwen-Image on visual quality. Under the hood: Cross-DiT diffusion transformers with"
X Link 2025-11-20T21:02Z 26.8K followers, XXX engagements

"This 80-page report is a wake-up call for science. Across XX live case studies GPT-5 didn't just assistit accelerated discovery in math physics biology and more. Highlights: four new math theorems (including a solution to a decade-old conjecture) rediscovery of state-of-the-art results in black-hole physics and lab-validated hypotheses in immunology all in hours not months. GPT-5 combed forgotten literature produced cleaner proofs and built full simulation models (like a fusion burn code) in a single chat. Its main weakness Occasional confident errorshuman oversight still essential. The"
X Link 2025-11-21T09:01Z 26.8K followers, XXX engagements

"This paper lays out a blueprint for an open real-time market for buying and selling computewhere every hour of GPU time is a perishable good transparently priced and efficiently matched. The core: an automated market maker posts a unique hourly price by load not by auction so users and providers know exactly what to expect. Providers stake capacity and declare their minimum price; if the market price dips they simply go dormant (but stay staked). Every job is matched to the cheapest feasible provider with O(log n) latency. Key results: Existence and uniqueness of equilibrium prices computed"
X Link 2025-11-21T21:02Z 26.8K followers, XXX engagements

"LLMs are getting better at solving tough problems but can they reliably check their own work Enter GRPO-Verifa reinforcement learning method that trains models to both solve and self-verify in one unified loop. On four hard math benchmarks adding explicit self-verification boosts verification accuracy from XXXX% (GRPO) to XXXX% with no loss in solution quality (38.5%). No explicit value critic required; group-normalized rewards handle both tasks efficiently. This unlocks a pathway to safer more trustworthy AImodels that catch their own mistakes before outputting an answer. Think: math tutors"
X Link 2025-11-22T09:01Z 26.8K followers, 1078 engagements

"3D Gaussian Splatting just got turbocharged for mobile. Texture3dgs introduces a cache-aware sorting algorithm and tightly-packed data layouts letting phones reconstruct 3D scenes up to XXX faster and with XXX less memory. Sorting alone is up to XXX quicker vs best GPU baselines and L1 cache misses drop by 60%. All this fits on standard mobile GPUsno tuning needed. This unlocks real-time on-device AR robotics and scanning apps with privacy and low latency no cloud required. Get the full analysis here: // alpha identified // $YNE"
X Link 2025-11-22T21:01Z 26.8K followers, XXX engagements

"RoMa v2 is here and its a leap forward for dense feature matching. This model nails the hardest 3D vision caseswide angles low texture fine detailswhile running XXX faster and using just XXX GB memory. The numbers: XXXX% AUC@10 on MegaDepth-1500 XXX px error on AerialMegaDepth (down from 25.1) and XXXX image pairs/sec throughput. New predictive covariances boost pose AUC@1 from XXXX to XXXX on Hypersim. Under the hood: DINOv3 features a multi-view transformer three fast CNN refiners a custom CUDA kernel and a training mix of 57M pairs. It even generalises to astronaut-to-satellite matches"
X Link 2025-11-23T09:02Z 26.8K followers, 1011 engagements

"POMA-3D flips the script on 3-D scene understanding: instead of raw point clouds or depth maps it encodes every scene as a point mapa 2-D grid where each pixel stores full 3-D coordinates. This lets it inherit rich 2-D priors from visionlanguage models like CLIP but reason about 3-D geometry directly. Trained on ScenePoint (6562 room scans + 1M image scenes) POMA-3D achieves state-of-the-art on 3-D QA (ScanQA SQA3D Hypo3D) boosts zero-shot scene retrieval Recall@1 from XXX% to XXX% on ScanRefer and doubles navigation accuracy on fine-grained embodied tasksusing geometry alone. Ablations"
X Link 2025-11-23T21:02Z 26.8K followers, XXX engagements

"NaTex is a leap for 3D artists: it skips the old bake 2D images onto a mesh routine and paints textures natively in 3D point by point. No more blurry seams or missing patchesjust sharp perfectly-aligned surfaces. How NaTex treats texture as a dense color point cloud compresses it XX with a geometry-aware VAE and then uses a diffusion transformer trained on X million meshes to generate or refine texturesall in one step 1s on a single A100. It beats the best: cFID XXXXX (3 vs. prior SOTA) LPIPS XXXXX and delivers visibly cleaner more coherent results than both research and commercial baselines."
X Link 2025-11-24T09:02Z 26.8K followers, 1015 engagements

"PathAgent is a new agentic framework that brings LLM-style reasoning to whole-slide pathology imageswith full transparency. Instead of black-box slide-level guesses it zooms explores and writes out a detailed chain-of-thought just like a real pathologist. Zero-shot training-free and plug-and-play PathAgent beats specialist systems on five benchmarks: XXXX% accuracy on SlideBench-VQA (37% above baselines) and XXXX% on WSI-VQA with open-ended answers that are both accurate and interpretable. The real kicker: every diagnosis is linked to explicit visual evidence and a readable decision trail."
X Link 2025-11-24T21:02Z 26.8K followers, XXX engagements

"SketchVerify flips video generation on its head: instead of hoping diffusion models get the physics right it runs a fast planning loop that samples sketches and verifies motion plans before any expensive synthesis. On WorldModelBench and PhyWorldBench SketchVerify delivers state-of-the-art instruction following (2.08 vs. 1.88) top physics realism (0.96 penetration XXXX gravity) and cuts planning time 13from XXXX to XXX minutes per task. Sketch-level verification matches full-video checks at XX lower cost. The secret: render lightweight video sketches judge them for both semantic fit and"
X Link 2025-11-25T09:01Z 26.8K followers, XXX engagements

"TorchQuantumDistributed is a game-changer for quantum ML. Its a PyTorch-native library that lets you split giant quantum state vectors across 1024 acceleratorsno CUDA lock-in no single-GPU memory wall. The team benchmarked 24-qubit circuits with near-linear scaling: as you add more GPUs wall-clock time and per-device memory drop almost perfectly. It supports both module and functional APIs runs differentiable shot-noise models and slashes memory via invertible gate recomputation. Finally you can prototype and train 28-qubit quantum circuits or hybrid quantumclassical models at scale directly"
X Link 2025-11-25T21:02Z 26.8K followers, XXX engagements

"Hard clipping in RL fine-tuning throws away too much signal when training LLMs especially on tricky Mixture-of-Experts models. Soft Adaptive Policy Optimization (SAPO) fixes this by swapping out brittle binary cuts for a smooth temperature-controlled gate on every token's update. SAPO keeps sequence-level coherence like GSPO but when only a few tokens go wild it softly down-weights just thempreserving learning from the rest. Asymmetric temperatures (_neg _pos) further stabilize those noisy negative-advantage updates. The result On a 30B Qwen3 MoE model SAPO avoids early collapse and boosts"
X Link 2025-11-26T09:02Z 26.8K followers, XXX engagements

"PixelDiT is a new image generator that skips the lossy autoencoder step and operates directly in pixel spacefinally solving the washed out details problem in diffusion transformers. How It splits the job: a patch-level transformer handles global layout while a lightweight pixel-level transformer sharpens textures. Two key trickspixel-wise AdaLN (for unique context-aware updates) and token compaction (reducing attention cost by 256)make dense pixel modeling practical. On ImageNet 256256 PixelDiT-XL hits FID 1.61best ever for pixel-space models and just XXX points from state-of-the-art latent"
X Link 2025-11-26T21:02Z 26.8K followers, XXX engagements

"LatentMAS is a breakthrough for multi-agent LLM systems: instead of making models "talk" in natural language it lets them share pure hidden-state vectorsdirectly exchanging their internal thoughts. The result Up to XXXX% better accuracy 7084% fewer tokens and a X speedup across X math science and coding benchmarks. No extra training needed; just plug and play with existing models. This latent collaboration means richer lossless communication and opens the door to faster leaner and more private AI teamworkon everything from edge devices to IDE copilots. Get the full analysis here: // alpha"
X Link 2025-11-27T09:02Z 26.8K followers, 1052 engagements

"Real-world oncology care is multimodal and unfolds over timebut most AI benchmarks miss this complexity. MTBBench changes the game: it simulates true molecular tumor-board workflows combining images labs genomics and clinical notes across patient timelines. XXX expert-validated questions agentic file-selection and plug-in tools (like pathology FMs PubMed DrugBank) create a tough realistic testbed for clinical AI. Baseline LLMs top out at XX% (multimodal) and XX% (longitudinal) accuracybarely above chance on outcome prediction. But adding domain tools boosts accuracy by up to XX% with smaller"
X Link 2025-11-27T21:02Z 26.8K followers, XXX engagements

"Image matching just got a serious upgrade. MatchGS unlocks the zero-shot power of 3D Gaussian Splatting by fixing its geometry and using it to generate 168k ultra-precise photorealistic training pairs. The result Matchers trained only on MatchGS data hit +17.7% AUC on ScanNet +13.9% on MegaDepth and +16.2% on ZEBwithout ever seeing the target domains. Plane-projected depth-regularised 3DGS slashes epipolar error by up to XX over classic datasets. Plus their patchvoxel alignment step gives matchers viewpoint-invariant geometry-aware features that generalise across scenes lighting and extreme"
X Link 2025-11-28T09:02Z 26.8K followers, XXX engagements

"Video diffusion models just unlocked a new level: they can be their own reward modelsno vision-language models or pixel-space supervision needed. This paper introduces Process Reward Feedback Learning (PRFL) which fine-tunes video generators entirely in latent space. The result: sharper motion and better anatomy with up to +56 and +21.5 point gains on VBench benchmarks. PRFL also trains at least XXX faster and fits into XX GB VRAM where older methods crash. Human judges chose PRFL videos in 6367% of head-to-head comparisons against strong baselines. The secret Rewards sampled at all timesteps"
X Link 2025-11-28T21:01Z 26.8K followers, XXX engagements

"Chain-of-thought prompting is bulkywhat if your model could decide when to stop thinking internally This new paper teaches Llama 3.2-Instruct to dynamically cut off latent reasoning using a binary stop head and RL. The result Average reasoning steps drop from XX to just 3.8over XX% shorterwithout sacrificing GSM8K-Aug accuracy. Longer chains still kick in for tough questions but easy ones get trimmed slashing compute and inference cost. Attempts at fancier distillation actually underperform the simple approach. A promising step toward efficient adaptive LLMs that only think as hard as they"
X Link 2025-11-29T09:01Z 26.8K followers, 1096 engagements

"NVIDIA just released Nemotron-Parse XXX a lightweight OCR+document parsing model that rivals much larger closed systems. It parses pages packed with text tables and images into structured Markdown/LaTeX extracting bounding boxes and semantic classeseven handling X languages with XX% OCR F1. On benchmarks it halves the error of Kosmos-2.5 and GOT and on GOT OCR F1 (0.979) its only behind Gemini Flash XXX. The token-compressed variant is XX% faster with almost no drop in quality (OmniDocBench error XXXXX best for models 1B params). All model weights code and the training pipeline are"
X Link 2025-11-29T21:01Z 26.8K followers, 1169 engagements

"Matrix is a major leap for synthetic data generation. Instead of a central orchestrator Matrix lets thousands of lightweight agents pass messages peer-to-peerremoving bottlenecks and scaling to 10000 concurrent workflows. No more idle GPUs or network jams. The results are wild: XXX higher throughput than specialized baselines including 2B tokens in 4h for LLM dialogue (6.8 faster) 14k concurrent tasks for web mining doubling token throughput (5853 t/s vs. 2778) 41k tool-use trajectories/sec in customer support a XX boost All with no loss in data quality. Matrix is open-source modular and"
X Link 2025-11-30T09:02Z 26.8K followers, 1265 engagements

"A landmark result in network theory: this paper nails down exactly when you can algorithmically recover communities in networks with K n groupsa regime where classic spectral methods break down. The authors design a new family of graph motifs (blown-up cycles with fasteners) proving that counting these patterns lets you recover all communities for every sparsity level above the ChinMosselSohnWein threshold. The error per node pair Exponentially smalljust n-3. Crucially this settles a long-standing open problem: the paper shows the CMSW threshold is the exact computational barrier for"
X Link 2025-11-30T21:01Z 26.8K followers, 1034 engagements

"What if every striker got to take someone elses chances This new Bayesian framework rethinks expected goals (xG) by giving each player their own finishing fingerprint learned from 9970 shots and Football Manager scouting ratings. It cuts uncertainty by XX% for low-sample players matches top predictive benchmarks (R=0.75 vs baseline; XGBoost R=0.833) and reveals real-world specializations: Agero and Surez are one-on-one masters Pogba shines from distance and Insigne/Salah excel on first touch. The real power Counterfactual swaps: Sansone would net +2.2 xG from Berardis shots; Vardy-for-Giroud"
X Link 2025-12-01T09:02Z 26.8K followers, XXX engagements

"GR-RL takes robot dexterity to a new level. By filtering out suboptimal demos flipping actions for double the data and using online RL in latent space it transforms a generalist VLA model into a specialistachieving XXXX% autonomous shoe-lacing success across multiple eyelets on a real dual-arm robot. Key insights: Value-based filtering alone lifts success by +15.9% Symmetry augmentation adds +11.1% Online RL bridges the train-test gap (+10.6%) enabling the first fully autonomous long-horizon shoe-lacing ever reported This framework shows how foundation models can be systematically specialized"
X Link 2025-12-02T09:02Z 26.8K followers, XXX engagements

"Glance flips the script on diffusion models: 5x faster image generation near-zero training cost and no loss in visual quality. Instead of retraining whole student models Glance plugs in two tiny LoRA adapters (Slow & Fast) each handling a different denoising phase. The trick Just one image one hour on a single V100 and the big model stays frozen. On X benchmarks Glance hits 9299% of teacher quality in only XXX steps (vs. 50). Side-by-sides show it nails both global layout and fine detaileven in new domains with one-shot adaptation. If you thought diffusion was too slow for real-time or"
X Link 2025-12-03T09:01Z 26.8K followers, XXX engagements

"MagicQuill V2 just set a new bar for image editing by giving generative models Photoshop-level control. Instead of jamming your whole idea into a single prompt you guide edits with four simple layers: what to add (content) where to put it (mask) how its shaped (edges) and what colors to use (strokes). This layered approach halves perceptual error versus InsertAnything and Nano Banana (LPIPS XXXXX vs 0.354) and human testers preferred its results XXXX% of the time. For object removal MagicQuill V2 edges out SmartEraser and OmniEraser on every metric. The interactive UI lets users drag"
X Link 2025-12-03T21:01Z 26.8K followers, XXX engagements

"RELIC could be a game-changer for interactive video world models. Starting from a single image and text it lets you explore a scene for 20+ seconds with real-time (16 FPS) streaming and memory so strong it remembers objects long after they leave the frame. No more 5-second limits or driftingRELIC nails long-term consistency user control and speed all at once. How A 14B model trained on 1600 min of balanced Unreal Engine data new compressed memory (4 smaller KV-cache) and a hybrid self-forcing distillation that keeps its predictions sharp. On VBench and action-following RELIC beats Matrix-Game"
X Link 2025-12-04T09:02Z 26.8K followers, 1024 engagements

"Radiance Meshes are hereand they might just change neural rendering. Instead of splatting Gaussians scenes are built from millions of see-through tetrahedra (up to 15M fit in 24GB VRAM) using Delaunay triangulation. The result Exact flicker-free rendering at speeds XX% higher than 3D Gaussian Splatting and a ray tracer that's XX% faster than Radiant Foam. No more depth-sorting errors. Every tetrahedron gets closed-form integrationso you get neural-field quality but with classic mesh compatibility. Works instantly for editing physics even fisheye lenses. 240475 FPS at 7201080p with"
X Link 2025-12-04T21:02Z 26.8K followers, XXX engagements

"Light-X is a breakthrough in generative video: for the first time you can take a single-camera video and re-render it with both new camera paths and new lightingthink move the camera anywhere and set any mood all from just one clip. The trick Disentangling geometry and illumination using dynamic point clouds plus a relit-frame pipeline all supervised by Light-Syna synthetic pairing method that replaces rare multi-view multi-light training data. Light-X crushes leading baselines on joint camera+lighting control: lowest FID (101 vs 139155) highest aesthetic (0.623) and best temporal"
X Link 2025-12-07T09:02Z 26.8K followers, 1422 engagements

"Motion4D is a major leap in video scene understanding: it fuses 2D foundation model outputs into a dynamic 3D Gaussian Splatting framework delivering stable motion geometry and semantics from a single consumer video. How good is it On the new DyCheck-VOS benchmark Motion4D hits XXXX J&F beating SAM2 (89.4) and prior 3D methods by 9+ points. For tracking it slashes 3D error to XXX cm and outperforms BootsTAPIR & CoTracker3 by 810%. Novel-view synthesis gets sharper too (PSNR XXXX dB). The key: iterative 3D refinement cleans up foundation model priors eliminates flicker and unlocks robust"
X Link 2025-12-07T21:02Z 26.8K followers, XXX engagements

"This new paper proposes a Unix for context for LLM agentsevery document tool API or memory becomes a mountable file in a governed file system. Instead of scattered prompts and ad-hoc memory agents get a persistent auditable context repository with versioning access control and full traceability. The AIGNE framework implements a 3-stage pipelineContext Constructor Updater Evaluatorto assemble stream and verify just the right knowledge within token limits. Demonstrated with a memory chatbot and a GitHub agent this architecture delivers maintainable industry-ready GenAI thats finally auditable"
X Link 2025-12-08T09:02Z 26.8K followers, XXX engagements

"GRAPE is a new framework that unifies how transformers "know" the position of each tokencombining the strengths of RoPE (rotations) and ALiBi/FoX (additive biases) into a single algebraic recipe. Why it matters: No more picking sides: both mechanisms now fit into one principled toolbox with closed-form efficient math. RoPE and ALiBi become special cases; new variants are easy to add and mix. Faster convergence and 1-1.5% higher accuracy than all baselines in 50B-token Llama pretraining and X downstream tasks. Path-integral extension enables content-dependent stable positional biases with"
X Link 2025-12-09T09:01Z 26.8K followers, XXX engagements

"If you want to move from fragile LLM demos to robust fully autonomous agentic AI in production this new guide is the blueprint. It lays out X concrete best practiceslike single-tool agents pure-function calls externalized prompts and Kubernetes-native deploymentthat cut failure rates make workflows auditable and tame the chaos of multi-agent orchestration. The authors prove it works with a live case study: a multimodal news-to-podcast pipeline that scrapes breaking news drafts scripts with GPT-5 Gemini and Llama merges outputs via a reasoning agent generates audio/video and pushes it all to"
X Link 2025-12-11T21:02Z 26.8K followers, XXX engagements

"Most AI ethics debates miss what makes generative AI truly different. This new paper argues its unique power is making tech feel "as if" it's humanan affordance that changes everything about responsibility privacy bias and even what authorship means. It digs into how GAIs outputs create quasi-social bonds new forms of manipulation and raise tough questions about who gets credit (or blame) for AI-assisted work. The author shows why ethical analysis should focus less on machine "intelligence" and more on how these systems reshape our relationships and judgments. If you care about the real risks"
X Link 2025-12-05T21:03Z 26.8K followers, XXX engagements

"This is the definitive guide to 3D scene representations for robotics. It benchmarks classic maps (point clouds voxels SDFs) fast photorealistic neural models (NeRF 3D Gaussian Splatting) and the emerging era of tokenized foundation models that blend geometry with language. Key insights: 3DGS is the first neural map to achieve XX FPS photorealistic rendering making dense SLAM and planning viable in real time. Feed-forward transformers like DUSt3R and enable one-shot token-based mapping over hundreds of imagesno iterative optimization needed. Foundation models (Scene-LLM NLMap) fuse scene"
X Link 2025-12-06T09:01Z 26.8K followers, XXX engagements

"The AI Consumer Index (ACE) is here: the first benchmark to test if top AI models can actually handle real-world consumer tasksshopping meal planning gaming advice DIY fixes. How are they doing Not great: the best model (GPT-5) solves just XX% of cases. In Shopping none break XX% with price errors and broken links everywhere. Hallucinations remain stubborn: some models drop XX percentage points when forced to show real evidence. ACE evaluates XX frontier LLMs using a tough multi-step rubric and dynamic web-grounding checks. The results reveal a wide gap between current AI and what consumers"
X Link 2025-12-08T21:02Z 26.8K followers, XXX engagements

"RoPE++ is a new twist on transformer position encoding: instead of discarding half the math it leverages both real and imaginary parts of rotary embeddings to better capture long-range dependencies. On benchmarks up to 64k tokens RoPE++ delivers up to +2 points over standard RoPE and its EH variant halves KV memory while matching baseline accuracyplus 1015% faster decoding. Imaginary heads turn out to matter most for very long context recall. Compatible with FlashAttention and all the latest context tricks. The code is out now. Get the full analysis here: // alpha identified // $YNE"
X Link 2025-12-09T21:01Z 26.8K followers, XXX engagements

"Wan-Move is a breakthrough in motion-controllable video generation: a lightweight method that lets you draw motion paths on images and turn them into 5-second 480p videoswith precision rivaling Kling XXX Pros commercial Motion Brush. No motion encoder or ControlNet needed. Wan-Move simply copies first-frame latent features along user-supplied trajectories guiding scene elements exactly as you want all while keeping the original backbone untouched. The result Fine-grained scalable motion control that slots right into any image-to-video diffusion model (like Wan-I2V-14B). On the new MoveBench"
X Link 2025-12-10T09:02Z 26.8K followers, XXX engagements

"OneStory is the new state of the art for AI-generated video storytelling. Instead of forgetting early scenes or relying on a single keyframe it models multi-shot video as an autoregressive next-shot taskso every new clip stays consistent with all that came before. Key tricks: Frame Selection module picks the most relevant frames from all prior shots guided by captions. Adaptive Conditioner injects important frames with higher detail so context stays compact but expressive. Finetuned on a freshly built 60000-video dataset with referential shot captions OneStory beats strong baselinesup to +4%"
X Link 2025-12-10T21:02Z 26.8K followers, XXX engagements

"ViSA sets a new standard for real-time avatar creation: from just one photo it reconstructs a 3-D upper-body model and brings it to life with a fast video diffusion shaderdelivering avatars that look real move fluidly and stay true to your identity. How By fusing explicit 3-D Gaussian reconstruction (for stable geometry) with dense 3-D-aware video diffusion (for sharp details and lively motion) then anchoring every frame with a cached reference image. An adversarial distribution-preservation loss restores high-frequency texture lost in standard diffusion. The results: XXXX dB PSNR (+3.57 dB"
X Link 2025-12-11T09:03Z 26.8K followers, XXX engagements

"ZeroOS is a breakthrough for zero-knowledge VMs: one modular library OS that lets any zkVM run real Rust/C/C++/Go appsno more patching language runtimes or juggling 20+ toolchain forks. The trick Just XX key Linux syscalls (plus a few stubs) are enough to support real-world apps like Rusts std and Rayon. You link only the OS pieces you need; unused modules stay out shrinking both audit surface and zk proof costs. The result: a single auditable foundation for all zkVM projects. Security fixes ship once not dozens of times. Build scripts create verifiable unikernels with stock compilersno libc"
X Link 2025-12-12T09:02Z 26.8K followers, XXX engagements