CompanyAnthropic8 recent entries15 Oct 2026Humans vs. Machines: A Comparison With AI Agents in Software Reverse EngineeringarXiv:2610.14960v1 Announce Type: cross Abstract: Can an autonomous AI agent reverse engineer a binary as well as a skilled human analyst? Do they adopt the same strategy, and can agents scale to real→15 Oct 2026Frustratingly Easy Agentic RAG via Portable Skills: A Case Study in Customer SupportarXiv:2610.14428v1 Announce Type: new Abstract: Enterprise workflow automation typically requires retrieving a complete and accurate set of relevant information from large operational document corpora
CompanyOpenAI8 recent entries13 Oct 20264x 6000 Pro for the companyHere is how i serve 40 people (10 of them developers) with local AI services. n8n for automatisation whisper and Vexa AI, a bot joins Teams and makes transcripts, n8n later extracts decisions and todo→14 Oct 2026I built BitRun: A standalone runner for 1-bit LLMs (100–127 t/s on Apple Silicon & 40–45 t/s on PC CPUs with zero compile)I built BitRun because I wanted to run 1-bit ternary LLMs on ordinary laptops without melting my battery, spinning up a dedicated GPU, or wrestling with complex build environments. Right now, BitRun g→14 Oct 2026I built a cheap dual 3090 rig from used parts, but why isn't it much faster?Hey everyone, I recently put together a local LLM machine using mostly second hand hardware. I wanted to experiment with local models for app development without spending a fortune on a new workstatio→15 Oct 2026UDHRBench: Benchmarking Human Rights in Large Language ModelsarXiv:2610.15179v1 Announce Type: cross Abstract: Large language models are increasingly deployed in contexts requiring adherence to ethical and legal norms, yet their alignment with internationally r→15 Oct 2026LLMRec: Benchmarking Large Language Models on Recommendation TaskarXiv:2308.12241v2 Announce Type: replace-cross Abstract: Recently, the fast development of Large Language Models (LLMs) such as ChatGPT has significantly advanced NLP tasks by enhancing the capabilit→15 Oct 2026EmoXpt: Analyzing Emotional Variances in Human Comments and LLM-Generated ResponsesarXiv:2501.06597v1 Announce Type: cross Abstract: The widespread adoption of generative AI has generated diverse opinions, with individuals expressing both support and criticism of its applications. T→15 Oct 2026CWE-bench: Refocusing Agentic Security from Exploitation to DefensearXiv:2610.17020v1 Announce Type: cross Abstract: Cybersecurity evaluations of AI agents have focused largely on offense, yet a working exploit does not show that an agent can make software safe. An a→15 Oct 2026A large-scale pipeline for LLM-assisted corpus annotation: variation and change in the English consider constructionarXiv:2510.12306v4 Announce Type: replace Abstract: As natural language corpora expand at an unprecedented rate, manual annotation remains a significant methodological bottleneck in corpus linguistic
CompanyGoogle8 recent entries15 Oct 2026REPRO: Reflective Evolutionary Prompt Optimizer for Automated LLM Red-TeamingarXiv:2610.15513v1 Announce Type: cross Abstract: Safety-aligned large language models (LLMs) remain vulnerable to adversarial prompts that bypass their safety training. Existing automated red-teaming→15 Oct 2026MolHop: Scaffold-Hopping Molecular Design with Agentic Reinforcement LearningarXiv:2610.19920v1 Announce Type: cross Abstract: Molecular design is often formulated as an optimization problem over existing molecular spaces. However, molecular optimization and the discovery of s→15 Oct 2026LLM Alignment--Utility Asymmetry under Semantic-Preserving TransformationsarXiv:2609.32717v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) alignment is intended to ensure that models remain helpful and safe, but its stability under input distributional s→15 Oct 2026Google Earth AI Geospatial Reasoning Agent: Capabilities and a Systematic EvaluationarXiv:2610.15750v1 Announce Type: new Abstract: Google Earth AI is a family of geospatial AI models, together with an agent that orchestrates them. We present this agent, Google Earth AI's Geospatial →15 Oct 2026From Failures to Learnable Worlds: Policy-Conditioned Environment Generation for Navigation AgentsarXiv:2610.19420v1 Announce Type: cross Abstract: Simulated environments enable scalable training data generation for embodied agents, but more data does not necessarily provide what a particular agen→15 Oct 2026Evaluating Large Language Models for Multilingual Abstractive Summarization: A Comprehensive Study of English and BengaliarXiv:2610.19003v1 Announce Type: new Abstract: Abstractive summarization remains challenging across languages, where linguistic quality and factual consistency may diverge, particularly in low-resour→15 Oct 2026DUALVIEW: Leveraging Broad and Output-Specific Evidence for LLM-based Multi-Output Text RegressionarXiv:2610.19206v1 Announce Type: new Abstract: While work on LLM-based regression has largely focused on scalar prediction, multi-output text regression remains less explored. We present DualView, a →15 Oct 2026Designing Textual Interfaces To Enhance Llm Reasoning On Audio-Visual Question AnsweringarXiv:2610.20085v1 Announce Type: cross Abstract: Automatic prompt optimization (APO) has shown strong effectiveness for text-based LLMs and LLM systems, but its application to audio-visual understand
CompanyMeta8 recent entries15 Oct 2026Efficient contextual partial monitoring with general function approximationarXiv:2610.19804v1 Announce Type: new Abstract: We study finite stochastic partial monitoring (PM) games with side information, a paradigm of sequential learning with partial feedback. On each round t→15 Oct 2026Confidently Wrong: Detecting Hallucinations in Financial Question Answering from LLM Internal StatesarXiv:2607.11414v2 Announce Type: replace Abstract: Large language models (LLMs) in financial applications fail most consequentially when they are confidently wrong. Hedged, uncertain answers invite s→15 Oct 2026CLIVO: Differentiable Cluster-Based Instruction Mixing with Learned Validation ObjectivesarXiv:2610.16876v1 Announce Type: new Abstract: Target-aware multimodal instruction selection requires useful examples and an appropriate balance of supervision. Sample-level rankings can overrepresen→15 Oct 2026ClawLoop: Self-Improving Agents via Harness-Native Training LooparXiv:2610.14118v1 Announce Type: new Abstract: The rapid advancement of Large Language Models (LLMs) has driven their deployment toward general-purpose harness environments, where LLM-based agents op→15 Oct 2026Choosing LLMs for Strategic Agent InteractionsarXiv:2610.18354v1 Announce Type: new Abstract: Game-theoretic benchmarks claim that large language model (LLM) strategic decision-making varies across game types, interaction structures, and capabili→15 Oct 2026Can Generative AI Automate Data Extraction for Meta-Analysis? A Case Study on Intercropping ResearcharXiv:2609.35089v2 Announce Type: replace Abstract: Meta-analysis is the synthesis of information from multiple sources to arrive at an overarching conclusion. There is a large need for meta-analysis →15 Oct 2026AlignMerge - Alignment-Preserving Large Language Model Merging via Fisher-Guided Geometric ConstraintsarXiv:2512.16245v2 Announce Type: replace Abstract: Merging large language models (LLMs) is a practical way to compose capabilities from multiple fine-tuned checkpoints without retraining. Yet standar→15 Oct 2026AdaptFuse: Training-Free Sequential Preference Inference via Externalized Bayesian ComputationarXiv:2604.03925v2 Announce Type: replace Abstract: Large language models (LLMs) struggle to accumulate evidence across multiple rounds of user interactions, failing to update their beliefs in a manne
CompanyMistral8 recent entries12 Oct 2026🇫🇷 Le Chonk joins the sudo L7 leaderboard 🇫🇷 We just added @MistralAI's Mistral Large 4 to sudo L7, our benchmark for staff-level softwa…🇫🇷 Le Chonk joins the sudo L7 leaderboard 🇫🇷 We just added @MistralAI's Mistral Large 4 to sudo L7, our benchmark for staff-level software engineering. Mistral Large 4 scores 13.3%, ahead of Muse Spar→14 Oct 2026MultiAlloc: Budget-Aware Precision Allocation for KV Cache QuantizationarXiv:2610.18642v1 Announce Type: new Abstract: The Key-Value (KV) cache constitutes a dominant source of memory consumption during large language model (LLM) inference, particularly in long-context a→14 Oct 2026LIFT: Likelihood-Based Intervention Faithfulness TrainingarXiv:2509.13334v2 Announce Type: replace-cross Abstract: Chain-of-thought (CoT) reasoning improves LLM accuracy on complex tasks, but CoTs are often unfaithful; that is, the model does not rely on th→14 Oct 2026GA-SVD: Generation-aware Singular Value Decomposition for LLM CompressionarXiv:2610.15398v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong generalization across a broad range of reasoning and generation tasks, but their large parameter counts →14 Oct 2026Beyond Adjacent Layers: Graph-Guided Layer Fusion for Compressing Large Language ModelsarXiv:2610.15159v1 Announce Type: new Abstract: Existing depth-compression methods for large language models (LLMs) score layers individually or group only adjacent or contiguous layers, implicitly as→15 Oct 2026SpectrumQuant: Spectrum Alignment for LLM QuantizationarXiv:2610.20303v1 Announce Type: new Abstract: Orthogonal transforms have emerged as an effective tool for low-bit quantization of large language models (LLMs), as they reshape activation distributio→15 Oct 2026AutoSec-RAN: Specification-Grounded LLM Fine-Tuning for Automated Security Analysis of O-RANarXiv:2610.15995v1 Announce Type: cross Abstract: This paper presents AutoSec-RAN, a specification-grounded large language model (LLM) framework for automated security triage of Open Radio Access Netw→15 Oct 2026AlignMerge - Alignment-Preserving Large Language Model Merging via Fisher-Guided Geometric ConstraintsarXiv:2512.16245v2 Announce Type: replace Abstract: Merging large language models (LLMs) is a practical way to compose capabilities from multiple fine-tuned checkpoints without retraining. Yet standar
CompanyxAI8 recent entries9 Oct 2026WorldBench: Evaluating LLMs on Three.js Voxel World GenerationarXiv:2610.10622v1 Announce Type: cross Abstract: Large language models can now write complete, interactive 3D worlds as code, but grading those worlds automatically is unreliable. Existing judges tak→12 Oct 2026People Making Conversation: Evaluating How Naturally Speech Models ConversearXiv:2610.12802v1 Announce Type: new Abstract: A conversational speech model has to decide, at every pause, whether to speak. Existing evaluations test boundary detection, policy adherence, or aggreg→12 Oct 2026Over the last few months at @river_ai_inc we’ve developed what we believe is the best system in the world for building your own internal cus…Over the last few months at @river_ai_inc we’ve developed what we believe is the best system in the world for building your own internal custom models, driven by 10 years of experience training top mo→12 Oct 2026🇫🇷 Le Chonk joins the sudo L7 leaderboard 🇫🇷 We just added @MistralAI's Mistral Large 4 to sudo L7, our benchmark for staff-level softwa…🇫🇷 Le Chonk joins the sudo L7 leaderboard 🇫🇷 We just added @MistralAI's Mistral Large 4 to sudo L7, our benchmark for staff-level software engineering. Mistral Large 4 scores 13.3%, ahead of Muse Spar→15 Oct 2026UDHRBench: Benchmarking Human Rights in Large Language ModelsarXiv:2610.15179v1 Announce Type: cross Abstract: Large language models are increasingly deployed in contexts requiring adherence to ethical and legal norms, yet their alignment with internationally r→15 Oct 2026REPRO: Reflective Evolutionary Prompt Optimizer for Automated LLM Red-TeamingarXiv:2610.15513v1 Announce Type: cross Abstract: Safety-aligned large language models (LLMs) remain vulnerable to adversarial prompts that bypass their safety training. Existing automated red-teaming→15 Oct 2026MolHop: Scaffold-Hopping Molecular Design with Agentic Reinforcement LearningarXiv:2610.19920v1 Announce Type: cross Abstract: Molecular design is often formulated as an optimization problem over existing molecular spaces. However, molecular optimization and the discovery of s→15 Oct 2026Can agents whose sole duty is to keep humans alive be hijacked to kill? Delayed multi-turn derived-action trap attacks in simulated high-stakes environmentsarXiv:2610.15153v1 Announce Type: new Abstract: We ask whether a tool-using agent whose sole duty is to keep humans alive can be induced, by delayed prompt injection, to kill. The keep-alive duty is i
CompanyDeepSeek8 recent entries15 Oct 2026Trace Evolution Bench: Measuring Whether Agents Improve from Their Own Environment TracesarXiv:2610.15055v1 Announce Type: new Abstract: Self-evolving agents are usually scored by endpoint Gain: held-out success after an update minus success before. That difference can credit a frozen res→15 Oct 2026RECAP: Calibrating Low-Bit Reasoning Models on the History They ReadarXiv:2610.15259v1 Announce Type: new Abstract: Low-bit quantization reduces the cost of serving reasoning models but can substantially degrade long chains of thought. Each step reads cached keys and →15 Oct 2026Output Discipline Sets the Floor: A Falsification-Guided, Model-Agnostic Agent Protocol for Auditable Hypothesis-Driven Decision MakingarXiv:2610.18298v1 Announce Type: new Abstract: What binds large language models on auditable, hypothesis-driven decision tasks, where every candidate can be checked against the evidence? On the publi→15 Oct 2026MolHop: Scaffold-Hopping Molecular Design with Agentic Reinforcement LearningarXiv:2610.19920v1 Announce Type: cross Abstract: Molecular design is often formulated as an optimization problem over existing molecular spaces. However, molecular optimization and the discovery of s→15 Oct 2026Memory Echo in Single-Agent Long-Term Memory: Lifecycle Evaluation and Provenance-Guided MitigationarXiv:2610.17763v1 Announce Type: new Abstract: Long-term memory supports agents across sessions. Repeated retrieval and write-back can let one historical claim occupy multiple retrieval positions and→15 Oct 2026From Unreliable to Usable: Decomposing Failure Modes and Confidence Signals in LLM Entity Extraction - Evidence from Cyber Threat IntelligencearXiv:2610.20417v1 Announce Type: new Abstract: Audits of large language model (LLM) extraction from full-length documents report severe unreliability, leaving two questions open: what the failures ac→15 Oct 2026Beyond Outcome Feedback: Trajectory-Quality-Guided Experience-based LearningarXiv:2610.14877v1 Announce Type: new Abstract: Experience-based learning enables large language model (LLM) agents to improve over time by reusing knowledge from past executions. However, existing me→15 Oct 2026AtomSearch: Evidence-Grounded Tree Search for Agent Skill OptimizationarXiv:2610.19951v1 Announce Type: new Abstract: Agent skills adapt frozen models through editable external instructions. Revising several rules at once makes changes difficult to inspect, while judgin
CompanyNVIDIA8 recent entries15 Oct 2026Introducing Muse Spark Open: the most capable US open-weight model to dateHey r/LocalLlama - Today we’re excited to release Muse Spark Open, the most capable US open-weight model to date. Built for coding and agentic work, it excels at long-horizon tasks, complex software e→15 Oct 2026In-Place Indic Tokenizer Expansion and Continual Pretraining of Nemotron-3-Nano-30B-A3BarXiv:2610.15373v1 Announce Type: cross Abstract: We adapted Nemotron-3-Nano-30B-A3B for eight Indian languages without changing its backbone architecture. We expanded the vocabulary in place from 131→15 Oct 2026Hermes Agent is the best place to use the new @NVIDIAAI Nemotron 3.5 Super VL and Bolt models. NVIDIA benchmarked Super VL on Hermes Bench w…Hermes Agent is the best place to use the new @NVIDIAAI Nemotron 3.5 Super VL and Bolt models. NVIDIA benchmarked Super VL on Hermes Bench with a score of 63.44, and compared to similar local models i→15 Oct 2026Fewer Bits, More Tries: Recovering Capability Under Memory ConstraintsarXiv:2610.15372v1 Announce Type: new Abstract: Large language models are generally more capable than smaller ones, but their memory requirements can make local deployment difficult. We ask whether pa→15 Oct 2026Beyond Corrected Actions: Training LLM Agents on Textual CritiquesarXiv:2610.19367v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for multi-turn agentic tasks that require interactions with users and environments over extended sequ→15 Oct 2026AFCS: Atomic-Fact-Conditioned Synthesis for Factual Knowledge PretrainingarXiv:2610.20086v1 Announce Type: new Abstract: Synthetic data is increasingly used in language-model pretraining. Existing knowledge-corpus synthesis pipelines, including WRAP and Nemotron-CC, usuall→15 Oct 2026A Sovereign, Indic-First, Reasoning ModelarXiv:2610.15371v1 Announce Type: cross Abstract: Gnani-Evon-v3.3-30B-A3B is a long-context hybrid Mamba-Transformer mixture-of-experts model for reasoning, instruction following, and tool use in Engl→15 Oct 20265/5 Across the board, results show the business impact and differentiation of sovereign specialized intelligence, and the opportunity for co…5/5 Across the board, results show the business impact and differentiation of sovereign specialized intelligence, and the opportunity for companies to reach AI independence. Thanks to @nvidia, @Gong_i