CompanyAnthropic8 recent entries20 Sept 2026Wiki Lint Report — 2026-09-20Automated lint: 14 errors, 54840 warnings, 3 info→22 Sept 2026Replicating the Geometry of Emotion Representations in a Base Open-Weights ModelarXiv:2609.22208v1 Announce Type: new Abstract: Sofroniew et al. (2026) report that emotion concepts in Claude Sonnet 4.5 are represented as vectors whose geometry mirrors human affect psychology. We →27 Sept 2026Wiki Lint Report — 2026-09-27Automated lint: 17 errors, 59669 warnings, 3 info
CompanyOpenAI8 recent entries21 Sept 2026hearim(헤아림): Maybe you don’t need a special model for Jev — ordinary local LLMs already have the capabilityWhat if you don’t need a new model to get Jev-style decisions? I built hearim(헤아림. hea-a-rim. not Here, I am.. lol), an open-source gateway that turns ordinary local or hosted LLMs into a Jev-compatib→25 Sept 2026Qwengram-0.8B: I transferred Qwen3.8 Flash-Next’s n-gram memory into Qwen3.5-0.8B — 5.05% lower validation perplexityI’ve been experimenting with whether Qwen3.8-Flash-Next’s pretrained PLE n-gram memory can improve a much smaller Qwen3.5-0.8B model. I trained the 0.8B setup with limited resources, mostly using free→27 Sept 2026Wiki Lint Report — 2026-09-27Automated lint: 17 errors, 59669 warnings, 3 info→4 Oct 2026Wiki Lint Report — 2026-10-04Automated lint: 19 errors, 64915 warnings, 3 info→5 Oct 2026Mitigating Private Data Leakage in LLMs with WhiteoutarXiv:2610.02418v1 Announce Type: cross Abstract: Modern large language models (LLMs) are trained on massive, largely unfiltered datasets, including content scraped from nearly every accessible websit→7 Oct 2026Semantic Capability Acquisition and Specialization During Vision-Language Model Fine-TuningarXiv:2610.07385v1 Announce Type: new Abstract: Fine-tuning vision-language models (VLMs) is typically evaluated at a single downstream checkpoint, obscuring whether a semantic capability was never ac→7 Oct 2026No Transformer Beats Six Covariates: Long-Horizon Prediction of Depressive Symptoms from Childhood EssaysarXiv:2610.07764v1 Announce Type: cross Abstract: Natural language processing (NLP) models can detect depression-related language in text written near the time symptoms are measured, but whether pretr→13 Oct 2026🚨 @AnthropicAI: AI “MAY BE” capable of self-replicating! Now read the actual research: • No fully autonomous rogue replicator demonstrated.…🚨 @AnthropicAI: AI “MAY BE” capable of self-replicating! Now read the actual research: • No fully autonomous rogue replicator demonstrated. • Cyber exploitation deliberately simplified. • Real-world r
CompanyGoogle8 recent entries20 Sept 2026Wiki Lint Report — 2026-09-20Automated lint: 14 errors, 54840 warnings, 3 info→25 Sept 2026Robo-Harness K1: Harnessing Robot-Use Agents via Perception AugmentationarXiv:2609.29389v1 Announce Type: new Abstract: Foundation vision-language models (VLMs) understand objects, instructions, and spatial relations, yet translating this capability into robotic manipulat→27 Sept 2026Wiki Lint Report — 2026-09-27Automated lint: 17 errors, 59669 warnings, 3 info→28 Sept 2026StarWM: Self-Supervised Trained Attention Routing for Robust World ModelsarXiv:2609.30667v1 Announce Type: new Abstract: A robust world model must strike the balance between faithfully capturing environmental dynamics and abstracting away from irrelevant content. While rec→30 Sept 2026Who Warmed the Archives? LLMs Overestimate Historical WarmtharXiv:2609.37499v1 Announce Type: new Abstract: Historical archives are an under-used source for extending the instrumental climate record backward in time, and LLMs offer a way to extract the indices→30 Sept 2026AutoMark: Enabling Autoresearch to Discover Better LLM WatermarksarXiv:2609.37310v1 Announce Type: cross Abstract: With LLM watermarking being deployed commercially and now required by regulations, improving its reliability and effectiveness has become crucial. Yet→4 Oct 2026Synthesis: Arxiv-Cs-CvAuto-generated synthesis of 18054 entries about arxiv-cs-cv→4 Oct 2026Wiki Lint Report — 2026-10-04Automated lint: 19 errors, 64915 warnings, 3 info
CompanyMeta8 recent entries6 Oct 2026Robust Parameter-Efficient LLM Adaptation on Analog HardwarearXiv:2610.05318v1 Announce Type: new Abstract: Analog in-memory computing is a promising platform for on-device execution of large language models because it performs matrix--vector multiplications (→6 Oct 2026Clean: Second-order LLM Training at Linear Memory Cost via Nystrom SketchingarXiv:2610.04204v1 Announce Type: new Abstract: Training large language models (LLMs) entails a fundamental trade-off: memory-efficient optimizers such as Adam discard cross-parameter curvature, where→7 Oct 2026Principled Under Pressure: Post-Training Decides Whether LLMs Act on Their Own Moral JudgmentarXiv:2610.08670v1 Announce Type: cross Abstract: Language models increasingly act as agents. An agent that says an action is wrong and then takes it anyway is a different failure from one that does n→8 Oct 2026LRCC: Generalizing Low-Rank Compression with Conditional ComputationarXiv:2610.08858v1 Announce Type: new Abstract: Low-rank compression reduces the cost of pretrained language models by replacing linear transformations with low-rank factorizations. However, conventio→9 Oct 2026Rounding in Preconditioner Space: Redesigning 4-bit AdamW Optimizer-State QuantizationarXiv:2610.12444v1 Announce Type: new Abstract: Quantizing AdamW's optimizer states reduces persistent storage, but quantization errors propagate through the moment recurrences and perturb subsequent →9 Oct 2026Amortized Off-Policy Evaluation for LLMsarXiv:2610.10848v1 Announce Type: new Abstract: Accurate evaluation is central to selecting which LLM to deploy, yet testing a candidate on live traffic exposes real users to an unvetted model. Teams →12 Oct 2026Weight Clustering Reveals the Importance of Relative Rank in Large Language ModelsarXiv:2603.17917v2 Announce Type: replace-cross Abstract: Large language models (LLMs) contain billions of parameters, but many exact weight values are not essential. We apply scalar K-means clusterin→12 Oct 2026Byzantine-Resilient Federated Large Language Model via Hypergraph Message PassingarXiv:2610.12711v1 Announce Type: new Abstract: Federated Large Language Models (FedLLMs) are promising to deliver privacy-preserving, collaborative intelligence. The decentralized training process is
CompanyMistral8 recent entries28 Jul 2026Might need math+code benchmark for frontier model(LLMs Silently Replace Math)[D]Hello guys. I found some problems in current frontier models. And want to share. # math_code_hallucination > Record of a failure caused by combining mathematics and code in a single prompt. --- ## Cas→24 Aug 2026Rigorous Evaluation of Large Language Models for Malaria Drug Discovery: Trade-offs in Performance, Scale, and Resource UtilityarXiv:2608.20418v1 Announce Type: cross Abstract: We introduce Malaria-Instruct, a curated instruction-following dataset derived from the ChEMBL Legacy Malaria corpus for Malaria virtual screening, an→1 Sept 2026Test-Time Training with Next-Token PredictionarXiv:2606.21803v2 Announce Type: replace Abstract: Next-token prediction is the self-supervised signal that trains language models, and every observed prompt token provides the same signal at test ti→4 Sept 2026Investigating the Ability of Large Language Models to Analyze Recipes for DiabetesarXiv:2609.03967v1 Announce Type: cross Abstract: Several studies have evaluated the ability of Large Language Models (LLMs) for meal planning, yielding positive outcomes. These models can process nat→15 Sept 2026Towards a Mechanistic Understanding of Propositional Logical Reasoning in Large Language ModelsarXiv:2601.04260v2 Announce Type: replace Abstract: Understanding how Large Language Models (LLMs) perform logical reasoning internally remains a fundamental challenge. While prior mechanistic studies→21 Sept 2026Stiefel-AdamW: Geometry-Aware AdamW for Linear Factorization BlocksarXiv:2609.21039v1 Announce Type: new Abstract: A pervasive structural pattern in modern deep learning is the linear factorization block: a submodule of the form W = BA in which two parameter matrices→29 Sept 2026From Attention Sensitivity to Layer Role: Revisiting Mixed-Precision Quantization of TransformersarXiv:2609.34866v1 Announce Type: new Abstract: Most post-training quantization pipelines fit each weight matrix to its pretrained counterpart, one matrix at a time. Whether that proxy tracks what an →1 Oct 2026DataFlex: A Unified Framework for Data-Centric Dynamic Training of Large Language ModelsarXiv:2603.26164v2 Announce Type: replace-cross Abstract: Data-centric training has emerged as a promising direction for improving large language models (LLMs) by optimizing not only model parameters
CompanyxAI8 recent entries10 Aug 2026Post-Grokking Collapse at the Representation-Readout Interface in Muon-Trained TransformersarXiv:2608.07436v1 Announce Type: new Abstract: Under the standard split, Muon gets hidden matrices and AdamW embeddings/output head. Muon groks modular addition faster, but its solutions do not hold.→19 Aug 2026AppendiGrade: An XAI-Enhanced Deep Learning Framework for Grading Appendicitis in Ultrasound with Gaussian Blur and Grad-CAMarXiv:2608.17923v1 Announce Type: new Abstract: Appendicitis is one of the most common abdominal emergencies worldwide and requires prompt diagnosis and treatment to prevent life-threatening condition→9 Sept 2026Wiki Lint Report — 2026-09-09Automated lint: 12 errors, 53990 warnings, 3 info→9 Sept 2026A significant fraction of humanity read this thread. Is anyone prepared to do something about it? Fretting doesn’t count.A significant fraction of humanity read this thread. Is anyone prepared to do something about it? Fretting doesn’t count. I resigned from Anthropic today. I spent the last three years doing pretrainin→13 Sept 2026Wiki Lint Report — 2026-09-13Automated lint: 12 errors, 54839 warnings, 3 info→20 Sept 2026Wiki Lint Report — 2026-09-20Automated lint: 14 errors, 54840 warnings, 3 info→27 Sept 2026Wiki Lint Report — 2026-09-27Automated lint: 17 errors, 59669 warnings, 3 info→4 Oct 2026Wiki Lint Report — 2026-10-04Automated lint: 19 errors, 64915 warnings, 3 info
CompanyDeepSeek8 recent entries18 Sept 2026DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache CompressionarXiv:2609.19969v1 Announce Type: new Abstract: The widespread adoption of long-horizon agents has made model workloads increasingly input-heavy. Although prior work has substantially reduced the cost→18 Sept 20266 billion tokens for $65 Is it as good as Astra and Fable at hard stuff? No of course not. But you don't always need a genius and can just c…6 billion tokens for $65 Is it as good as Astra and Fable at hard stuff? No of course not. But you don't always need a genius and can just call one for advice when you do. Extrapolate where this is go→22 Sept 2026An Unexpected Robot Policy: Early Evaluations of GPT-6 Astra on RoboDojo and BeyondarXiv:2609.24170v1 Announce Type: new Abstract: Embodied AI systems are often organized into System 1 and System 2. System 1 is typically a pretrained policy that generates actions at high frequency, →30 Sept 2026Who Warmed the Archives? LLMs Overestimate Historical WarmtharXiv:2609.37499v1 Announce Type: new Abstract: Historical archives are an under-used source for extending the instrumental climate record backward in time, and LLMs offer a way to extract the indices→2 Oct 2026Match the Distribution, Not the Compute: Post-Training Multi-Token Prediction HeadsarXiv:2610.00888v1 Announce Type: cross Abstract: Multi-token prediction (MTP) improves the throughput of autoregressive generation by enabling the language model to draft multiple next tokens per for→3 Oct 2026Reasoning from scratch, round number 6! An introduction (and implementation) of Reinforcement Learning with Verifiable Rewards (RLVR) and Gr…Reasoning from scratch, round number 6! An introduction (and implementation) of Reinforcement Learning with Verifiable Rewards (RLVR) and Group Relative Policy Optimization (GRPO). 00:00 Introduction →6 Oct 2026Local AI World Model Part 2 - Deep NN to turn Images into Playable Characters, with prompt switching mid rolloutLast time when I posted on this subReddit to share my work, the response almost made me cry because a tiny demo got so many people talking about this In the past 2 months Ive been training a new model→12 Oct 2026Knowing Is Not Telling: Identity Ossification in LLM Representations of Trans-border CommunitiesarXiv:2610.12610v1 Announce Type: cross Abstract: Ethnic and cultural identities rarely align with political borders, a tension made sharper by migration and long-standing cross-border ties. Communiti
CompanyNVIDIA8 recent entries2 Oct 2026Faynt: Scaling and Optimizing Policies for Competitive MeleearXiv:2610.02144v1 Announce Type: new Abstract: We introduce Faynt, a family of 10M- and 75M-parameter Transformer policies for Super Smash Bros. Melee, each controlling all 26 characters with a singl→2 Oct 2026Fast Polynomial Transcendentals for LLMsarXiv:2610.00049v1 Announce Type: new Abstract: Graphics processing unit (GPU) generations scale matrix, special-function, and memory pipelines at different rates, so kernel bottlenecks move as hardwa→4 Oct 2026Synthesis: Arxiv-Cs-CvAuto-generated synthesis of 18054 entries about arxiv-cs-cv→6 Oct 2026Vision Transformer Ensembles for Panoramic Street SegmentationarXiv:2610.06063v1 Announce Type: new Abstract: Semantic segmentation of street panoramas can support detailed descriptions of urban environments, yet small datasets and unequal training costs make mo→6 Oct 2026Scale Bitwise-Deterministic Pretraining with NVIDIA Megatron CoreMegatron‑LM PR #7262 introduces a workflow that records ordered per‑rank tensor fingerprints to pinpoint and correct nondeterminism in large‑scale pretraining. By implementing low‑overhead kernel twea→6 Oct 2026AFP-GIC: Controllable Generative Image Compression [R]Hi ML Community, I am excited to share our latest framework, AFP-GIC, officially published in IEEE Access (2026). We have released the deployment codebase and hosted an interactive visual playground. →7 Oct 2026The Machines that Make the MachinesNVIDIA’s Seattle Robotics Lab and Isaac engineering team created reusable robotic systems to automate GB300 tester‑tray assembly, achieving over 95 % success on busbar tasks with a 160‑second cycle ti→7 Oct 2026Enhancing Diffusion Language Models with Autoregressive Post-Training WeightsarXiv:2610.08108v1 Announce Type: new Abstract: Diffusion language models (dLLMs) have emerged as a promising alternative to autoregressive (AR) language models, offering flexible token-update orders