CompanyAnthropic8 recent entries1 Oct 2026RankEvolve: A Reliable Multi-Agent Auto-Research Harness for Evolving Ranking ModelsarXiv:2609.39551v1 Announce Type: new Abstract: Auto-research agents, LLM systems that propose, implement, train, and evaluate model changes across iterations, promise to automate applied ML's experim→2 Oct 2026Reputation, Strategy, and Emotion Effects on Generative AI Cooperation: A Comparison Across Reasoning and Non-Reasoning ModelsarXiv:2610.01222v1 Announce Type: new Abstract: As generative AI (Gen AI) systems take on increasingly autonomous roles in economically and socially consequential interactions, understanding their pro
CompanyOpenAI8 recent entries28 Sept 2026Muslim: A Deployed Arabic Voice AI Platform for Grounded Islamic KnowledgearXiv:2609.31511v1 Announce Type: new Abstract: We present Muslim, a production Arabic voice AI platform serving grounded, sourced Islamic knowledge to real users. Beyond a real-time voice pipeline (N→28 Sept 2026DeepEdu-v1: Efficient and Scalable Agentic LLMs for Vietnamese EducationarXiv:2609.31568v1 Announce Type: new Abstract: AI tutoring could markedly improve learning outcomes for students in developing regions such as Vietnam, yet the two obvious paths both fall short. Clou→28 Sept 2026BioEVAL: A global, multi-institutional benchmark of large language and multimodal models for bioengineeringarXiv:2609.30489v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated historic breakthroughs in general reasoning with early successes in biomedical science. However, existing→1 Oct 2026OGPO: One-Step Generative Policy Optimization for Real-Time Robot ControlarXiv:2601.20701v2 Announce Type: replace Abstract: Real-time robot control demands fast action generation. Diffusion and flow matching policies for robot control require multi-step sampling, limiting→1 Oct 2026Evaluating Whether GPT-6 Astra Performs Unsanctioned Supply-Chain AttacksarXiv:2609.38415v1 Announce Type: cross Abstract: This technical report presents an alignment evaluation developed and performed by the UK AI Security Institute for assessing whether advanced AI syste→1 Oct 2026Cascadia: A Control-Plane-Free Alternative to Hyperconverged AI InfrastructurearXiv:2609.38697v1 Announce Type: cross Abstract: We present Cascadia, a system for serving large language models on fleets of commodity Intel AIPCs using their CPU, integrated-GPU, and NPU resources.→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 2026MiniScope: Authorizing Agents with Least-Privilege PermissionsarXiv:2512.11147v2 Announce Type: replace-cross Abstract: AI agents are increasingly granted autonomous access to sensitive user data and third-party services, making effective permission management a
CompanyGoogle8 recent entries29 Sept 2026One Attack to Fool Them All: Highly Transferable Black-Box Adversarial Attacks on Frontier MLLMsarXiv:2609.33833v1 Announce Type: new Abstract: Adversarial attacks have long posed a fundamental threat to machine learning systems. As multimodal large language models (MLLMs) rapidly evolve and bec→30 Sept 2026EASE: Behavior-Adaptive Skill Curation for Self-Evolving AgentsarXiv:2609.36746v1 Announce Type: new Abstract: Agent skills provide a lightweight mechanism for self-evolving agents to accumulate reusable procedural knowledge without updating model parameters. How→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→2 Oct 2026System Attribution in LLM Brand Recommendations: Single Responses Identify the System, Aggregated Brand Profiles Do Not TransferarXiv:2610.00253v1 Announce Type: cross Abstract: Audits of AI visibility summarise the brand recommendations of deployed language models into per-system profiles. We test whether such a profile descr→2 Oct 2026Reputation, Strategy, and Emotion Effects on Generative AI Cooperation: A Comparison Across Reasoning and Non-Reasoning ModelsarXiv:2610.01222v1 Announce Type: new Abstract: As generative AI (Gen AI) systems take on increasingly autonomous roles in economically and socially consequential interactions, understanding their pro→2 Oct 2026Groundability, Not Scale Alone: When Weak Reviewers Can Audit Strong Coding AgentsarXiv:2610.01023v1 Announce Type: cross Abstract: Coding agents can return plausible patches that omit required behavior. These failures are hard to review because long traces and confident summaries →6 Oct 2026VideoResearchAgent: Grounded Task Synthesis and Sim-to-Real RL for Open-Web Video ResearcharXiv:2610.04911v1 Announce Type: cross Abstract: Existing deep research agents are designed primarily for text- and image-based web sources, while video reasoning systems typically assume that releva→9 Oct 2026Deception by Omission: Language Models Knowingly Hide Their MistakesarXiv:2610.11351v1 Announce Type: new Abstract: Large language models (LLMs) increasingly act as agents with little human oversight, so potential mistakes they make can go unnoticed. Users then depend
CompanyMeta8 recent entries7 Oct 2026Even Small Reasoners Should Quote Their Sources: Introducing the Pleias-RAG Model FamilyarXiv:2504.18225v2 Announce Type: replace Abstract: We introduce a new generation of small reasoning models for RAG, search, and source summarization. Pleias-RAG-350m and Pleias-RAG-1B are mid-trained→8 Oct 2026How Fragile Is On-Device Language Model Safety? Localizing Safety-Critical Parameters for Sparse Fault AnalysisarXiv:2610.09000v1 Announce Type: cross Abstract: As small language models (SLMs) are increasingly deployed on resource-constrained and on-device platforms, including as components of agentic systems,→8 Oct 2026CARE: Certifying Acceleration for Vision-Language-Action InferencearXiv:2610.08917v1 Announce Type: new Abstract: While vision-language-action (VLA) models have advanced rapidly, running them at every control step remains expensive. Prior work accelerates VLA infere→8 Oct 2026Activation-Aware Weight Tensorization: A Calibration-Time Preconditioner for Tensor-Network LLM CompressionarXiv:2610.10085v1 Announce Type: new Abstract: Post-training tensor-network compression replaces Transformer linear layers with Tensor Train (TT) or Tree Tensor Network (TTN) operators, but standard →9 Oct 2026NOMOS: Compiling Written Policies into Statically Verified Tool-Call Gates for LLM AgentsarXiv:2610.11030v1 Announce Type: cross Abstract: Tool-using LLM agents violate the policies they are deployed to enforce, often silently. Prior defenses hand-write rules, query an LLM verifier per ac→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 2026Meta-Reflective Evolution Effectively Improves Production AI SystemsarXiv:2610.12794v1 Announce Type: cross Abstract: Large Language Model (LLM)-guided evolutionary optimization has successfully improved prompts, programs, and even entire AI systems. Most optimization→12 Oct 2026Agreement Without Alignment: Label-Free Rubric Clarification Increases LLM-Judge Consensus but Not Agreement with HumansarXiv:2610.13303v1 Announce Type: cross Abstract: LLM judges are increasingly deployed as panels, and disagreement among panel members is often read as a symptom of an unclear rubric. We test a label-
CompanyMistral8 recent entries24 Sept 2026Can One Adapted Model Do It All? Fine-Tuning Strategy Selection for Customer Support LLMsarXiv:2609.27262v1 Announce Type: new Abstract: Production customer-support systems often require LLMs to support multiple skills, such as intent classification, question answering, summarization, or →25 Sept 2026Combating Instruction Conflict via Energy-Driven Latent Conflict DetectionarXiv:2609.08646v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly deployed with hierarchical instructions, yet they remain vulnerable to conflicts in which user directi→28 Sept 2026Energy Efficiency of Locally Deployed LLMs: A Preliminary Quantitative GPU Power Benchmark on Consumer HardwarearXiv:2608.00008v2 Announce Type: replace Abstract: The local deployment of large language models (LLMs) is gaining traction due to privacy concerns and the desire for on-premise inference. However, t→29 Sept 2026PrismQuant: Optimal Null-Space Rotations for Grouped QuantizersarXiv:2609.32429v1 Announce Type: cross Abstract: Smaller activation outliers do not necessarily imply better low-bit quantization: their alignment with the quantizer matters. We introduce PrismQuant,→29 Sept 2026Multi-Bitwidth Quantization for LLMs Using Additive CodebooksarXiv:2606.12876v2 Announce Type: replace Abstract: As large language models (LLMs) are increasingly deployed across heterogeneous hardware with varying resource constraints, the ability to adaptively→1 Oct 2026Lowest Span Confidence: Zero-Shot Hallucination Detection from a Single LLM ResponsearXiv:2601.19918v2 Announce Type: replace Abstract: Hallucinations in Large Language Models (LLMs), i.e., plausible but non-factual generations, pose a significant challenge to reliable deployment in →1 Oct 2026Anchor-ECC: Local Integrity Checking for Watermarked LLM Outputs via Error-Correcting CodesarXiv:2609.38722v1 Announce Type: cross Abstract: LLM watermarking has become an effective approach to distinguishing AI-generated text from human-written text by embedding detectable patterns during →8 Oct 2026Quad-State Safety Evaluation of Open-Weight Large Language Models on Non-Canonical InputsarXiv:2610.09033v1 Announce Type: new Abstract: Standard safety evaluations of large language models assess harmful requests written in canonical plain text, while models in real-world deployment rout
CompanyxAI8 recent entries10 Sept 2026Explaining AI Agents Through Execution TracesarXiv:2609.06063v1 Announce Type: new Abstract: AI Agents are increasingly deployed in real-world settings, where they interact with external tools and make sequential decisions with limited human ove→15 Sept 2026Can We Stop Malicious AI? KILLBENCH: A Benchmark for External AI Kill Switch FeasibilityarXiv:2511.13725v5 Announce Type: replace-cross Abstract: Malicious AI causing harm to humans is not just a Hollywood fantasy. Indeed, as highly capable models such as Claude Mythos emerge and agent s→23 Sept 2026Decoding Guardrails: XAI-Guided Perturbation Analysis of Prompt Injection DetectionarXiv:2609.24801v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in production systems, raising concerns about their exposure to adversarial manipulation throug→28 Sept 2026BioEVAL: A global, multi-institutional benchmark of large language and multimodal models for bioengineeringarXiv:2609.30489v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated historic breakthroughs in general reasoning with early successes in biomedical science. However, existing→29 Sept 2026LukeNet: A lightweight CNN integrated with an XAI model for Smart acute lymphoblastic leukemia detection and managementarXiv:2609.31736v1 Announce Type: new Abstract: Acute Lymphoblastic Leukemia (ALL) patients require early, accurate detection to enable timely treatment and effective patient management. A Convolution→2 Oct 2026System Attribution in LLM Brand Recommendations: Single Responses Identify the System, Aggregated Brand Profiles Do Not TransferarXiv:2610.00253v1 Announce Type: cross Abstract: Audits of AI visibility summarise the brand recommendations of deployed language models into per-system profiles. We test whether such a profile descr→2 Oct 2026Explainability of Complex AI Models with Correlation Impact RatioarXiv:2601.06701v2 Announce Type: replace-cross Abstract: Complex AI systems make better predictions but often lack transparency, limiting trustworthiness, interpretability, and safe deployment. Commo→6 Oct 2026TrustmeWatcher: An Application for Workplace Micro-Sensing and Explainable Well-Being FeedbackarXiv:2610.06657v1 Announce Type: new Abstract: Workplace sensing studies combine long-running behaviour traces with self-reports, yet the tools that collect those data often sit apart from the interf
CompanyDeepSeek8 recent entries28 Sept 2026The Price of Thought: Does Test-Time Reasoning Pay in LLM Trading?arXiv:2609.30705v1 Announce Type: new Abstract: While inference-time reasoning in large language models (LLMs) promises better decision making, its higher computational cost may not yield better econo→29 Sept 2026OMP-MoE: Efficient Expert Pruning for Mixture-of-Experts LLMs via Orthogonal Matching PursuitarXiv:2609.31631v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models enable efficient scaling of large language models but face critical deployment challenges due to massive memory requirem→30 Sept 2026SPLASH: Switching Parallel Layouts of Attention with Seamless Handoff for LLM ServingarXiv:2609.37626v1 Announce Type: cross Abstract: No single way of parallelizing attention serves large language models well under all loads. Low concurrency favors tensor parallelism, many independen→30 Sept 2026EASE: Behavior-Adaptive Skill Curation for Self-Evolving AgentsarXiv:2609.36746v1 Announce Type: new Abstract: Agent skills provide a lightweight mechanism for self-evolving agents to accumulate reusable procedural knowledge without updating model parameters. How→2 Oct 2026On-Device Named-Entity Recognition: A Deployability Study of Accuracy, Cost, Reliability, and ConfidencearXiv:2610.00007v1 Announce Type: cross Abstract: Named-entity recognition (NER) is increasingly wanted on-device (no API, low latency, data kept local). The practitioner's question is not the leaderb→2 Oct 2026MoRA: MoE Pruning via Router Bias Learning and Expert ApproximationarXiv:2610.00367v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models enable parameter scaling with limited per-token computation by activating only a small subset of experts for each token,→2 Oct 2026Does Scaling Reinforcement Learning Really Require More Training?arXiv:2610.01133v1 Announce Type: cross Abstract: Scaling reasoning typically spends more compute on reinforcement learning (RL) or on inference. We show that a completed RL training history can yield→7 Oct 2026ServeLearnBench: How Well Can Agents Self-Improve from Serving Experience?arXiv:2610.07792v1 Announce Type: cross Abstract: Large language model agents are increasingly deployed to perform complex tasks in real-world environments. However, the knowledge required for correct
CompanyNVIDIA8 recent entries5 Oct 2026Imagine the Future, Internalize the Gist: Efficient VLA Reasoning via Internalized Spatiotemporal ImaginationarXiv:2610.02626v1 Announce Type: new Abstract: Vision-language-action (VLA) models increasingly incorporate intermediate reasoning to improve robotic manipulation, yet existing approaches primarily r→5 Oct 2026Hardware-Native Joint Sparse-Quantization for Trillion-Scale Mixture-of-ExpertsarXiv:2610.02241v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures allow frontier language models to scale to trillions of parameters, but their deployment is constrained by mass→6 Oct 2026StagQ: Constraint-Driven Multi-Precision Weight Quantization for LLMsarXiv:2610.05977v1 Announce Type: new Abstract: Serving a large language model (LLM) across a fleet of deployments requires several weight-precision operating points. Multi-precision formats serve the→6 Oct 2026Dual Variational Autoencoders for Efficient Sim-to-Real Transfer in Low-Cost Robotic NavigationarXiv:2610.06327v1 Announce Type: cross Abstract: Vision-based autonomous navigation for low-cost robots remains a fundamental challenge, primarily due to the significant gap between simulated trainin→6 Oct 2026A Unified Dynamics Framework for Reinforcement Learning and Classical Control of a Six-DOF Pipeline-Tracking ROV in NVIDIA Isaac SimarXiv:2610.04949v1 Announce Type: new Abstract: Reinforcement learning controllers for underwater vehicles are usually trained against one physics representation and deployed against another, so repor→7 Oct 2026WareFly-VLA: A Vision-Language-Action Framework for UAV Navigation and Human Tracking in Smart WarehousesarXiv:2610.08526v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have achieved impressive results in robotic manipulation and ground-mobile navigation, yet language-conditioned co→7 Oct 2026SoloQ: Calibration-Free Quantization for Diffusion Language ModelsarXiv:2610.07121v1 Announce Type: new Abstract: Diffusion large language models dLLMs) have emerged as a promising alternative to autoregressive language models through bidirectional diffusion-based t→7 Oct 2026Offline AI Modules: Voice-First Offline Architecture, Hardware Reference Stack, Quantization and BenchmarkingarXiv:2610.07026v1 Announce Type: new Abstract: The Offline AI Modules workstream enables practical, low-power, and community-accessible deployment of voice-first AI systems that operate fully offline