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  1. NVIDIA Blogchips
    NVIDIA Transforms European Retail, From Digital Discovery to Physical Operations

    European retailers are using open models and physical intelligence across use cases — from a commerce platform cutting inference costs by 90% to to a fulfillment center where collaboration of different robotic fleets is…

  2. NVIDIA Blogchips
    Pioneers Across Europe Deploy NVIDIA Earth-2 Open Models to Power Real-World Weather and Climate Prediction

    Weather forecasts shape more than daily plans; timely weather information is crucial for energy producers, insurers and transport operators to plan around changing conditions. A global forecast can show a storm taking sh…

  3. Guardian Technologypolicy
    AI firms say UK has a year to head off datacentre protests before construction is threatened

    Exclusive: Nvidia, Microsoft and Cisco taskforce urges ministers to offer areas greater benefits from tech infrastructure amid fears of US-style opposition AI companies have told ministers they have 12 months to head off…

  4. NVIDIA Blogresearch
    NVIDIA Open Models Power a New Wave of European Public Sector Projects

    Governments need modern solutions to serve the public while keeping sensitive information under their control. Open models provide a path forward, letting governments evaluate them, adapt them to local languages and publ…

  5. BBC Technologysafety
    UK working to identify exposure after global cyber-security warning

    Governments and companies are scrambling to protect their websites, as Amazon says it experienced attacks before the warning was made public.

  6. The Register AI + MLopen-source
    IBM CEO says open weight models are now irresistibly good and cheap on-prem

    90 percent of the performance at ten percent of the price, in just two or three racks, is hard to beat

  7. Guardian AIcommunity
    ‘I’d consider replacing one of my children’: Taika Waititi on robot kids, his cheese-o-meter and Klara and the Sun

    The director has turned Kazuo Ishiguro’s acclaimed novel about an ailing adolescent and her glitchy robot friend into a thought-provoking film. What do the pair think this story says about tech, love and grief? In the wi…

  8. arXiv cs.AIresearch
    A Small Model Asks Better: Fine-Tuning Query Clarification for Retrieval-Augmented Generation

    arXiv:2610.28686v1 Announce Type: new Abstract: Query clarification is essential for retrieval-augmented generation (RAG) systems that face ambiguous user queries. We consider multi-turn grounded conversational scenarios…

  9. arXiv cs.AIagents
    Scaling in Games: Continued Pre-Training For Embodied Agents In Diverse Virtual Worlds

    arXiv:2610.28698v1 Announce Type: new Abstract: Scaling data, diversity and model capacity has improved embodied learning in physical environments, where diverse experiences remain grounded in shared physical laws. Wheth…

  10. arXiv cs.AIresearch
    SpecEvo: Speculative Evolution with Large Language Models for Cost-Efficient Scientific Discovery

    arXiv:2610.28706v1 Announce Type: new Abstract: LLM-driven evolutionary search is a promising paradigm for scientific discovery, but existing methods remain costly and slow, often applying expensive reasoning uniformly w…

  11. arXiv cs.AIagents
    Automating ML for Science: Can Frontier Agents Climb Scientific Hills in the Wild?

    arXiv:2610.28763v1 Announce Type: new Abstract: Frontier coding agents are increasingly framed as end-to-end automated researchers, and ML for science offers a demanding test of that promise: improving a scientific model…

  12. arXiv cs.AIagents
    Forging More Tasks into Better Harnesses: Agentic Harness Evolution via Successive Scale Racing

    arXiv:2610.28815v1 Announce Type: new Abstract: Agentic harness evolution optimizes an agent's instructions, tools, and control flow by using its task execution experiences as evolving evidence. While more evolution task…

  13. arXiv cs.AIresearch
    Decision language models as affordable and rapid alternatives to LLM judges of clinical generative AI

    arXiv:2610.28826v1 Announce Type: new Abstract: Automated judges of clinical artificial intelligence (AI) outputs are necessary, but large language model (LLM) judges are costly and slow at scale. We compared Jev, a deci…

  14. arXiv cs.AIresearch
    Sketch2Sim: an end-to-end modular framework for hand-drawn circuit analysis

    arXiv:2610.28836v1 Announce Type: new Abstract: This study proposes a sketch-to-simulation system to solve handwritten circuit diagrams. The system converts raw images into a Simulation Program with Integrated Circuit Em…

  15. arXiv cs.AIresearch
    Speedrunning Relational Foundation Model Pretraining

    arXiv:2610.28855v1 Announce Type: new Abstract: Progress on foundation model pretraining is gated by who can afford a trial, and relational pretraining is no exception. Recipes are developed inside individual labs, repor…

  16. arXiv cs.AIresearch
    To Manipulate or Not: Opinion Dynamics in LLM Interactions

    arXiv:2610.28875v1 Announce Type: new Abstract: Large language models increasingly take part in extended conversations where they can both shape and be shaped by another party's views, yet most persuasion research measur…

  17. arXiv cs.AIagents
    Fig: Automated Multiagent Behavior Elicitor

    arXiv:2610.28891v2 Announce Type: replace Abstract: Many social evaluations for multiagent systems study behaviors as they emerge from environments instead of systematically intervening in the environment to elicit such…

  18. arXiv cs.AIagents
    Hidden Messages Between Diffusion Language Model Agents: Causal Evidence for Latent Communication

    arXiv:2610.28905v1 Announce Type: new Abstract: Diffusion language models form answers through a sequence of revisable continuous states, but multi-agent systems usually discard those states and make agents communicate o…

  19. arXiv cs.AIresearch
    DiffResearch: Accelerating Deep Research with Diffusion Language Models

    arXiv:2610.28909v1 Announce Type: new Abstract: Deep research systems iteratively plan, gather evidence, synthesize, and revise, making end-to-end latency a key bottleneck for interactive use. Almost all production syste…

  20. arXiv cs.AIresearch
    Simply Logical -- The First Three Decades

    arXiv:2610.28912v1 Announce Type: new Abstract: This paper charts the evolution of the Prolog textbook Simply Logical -- Intelligent Reasoning by Example from print with runnable programmes on a 3.5-inch diskette publish…

  21. arXiv cs.AIagents
    D-Skill: Distilling Teacher Knowledge through Agent Skills

    arXiv:2610.28914v1 Announce Type: new Abstract: Frontier language-model agents excel at complex tasks, but high inference costs make transferring their capabilities to smaller models essential. Traditional knowledge dist…

  22. arXiv cs.AIagents
    Back Up Before You Regret: Measuring Backup Awareness and Automating Backup in Coding Agents

    arXiv:2610.28934v1 Announce Type: new Abstract: Coding agents now complete tasks autonomously, modifying real-world state such as artifacts, software environments, and configurations along the way. Yet they show limited…

  23. arXiv cs.AIagents
    Self-Improving Agents with World Model Predictive Paths

    arXiv:2610.28945v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly expected to interact with environments and improve their decisions during deployment. However, how anticipating future ou…

  24. arXiv cs.AIagents
    Behavior Beyond Text: Evaluating Refusal Transfer Failure in LLM Agents

    arXiv:2610.28982v1 Announce Type: new Abstract: While large language models are increasingly deployed as tool-calling agents, their safety evaluations still focus primarily on their ability to refuse harmful requests in…

  25. arXiv cs.AIagents
    PerMIT: Securing Persistent Memory for LLM Agents via Machine-Checked Integrity Theorems and Scalable Community Trust

    arXiv:2610.28987v1 Announce Type: new Abstract: Persistent memory is a largely undefended surface for injection and poisoning, and the same risk limits memory sharing among agents. We present PerMIT, a memory architectur…

  26. arXiv cs.AIagents
    AgentPolicyForge: From Executable Environments to Policy Benchmarks and Adaptive Guards

    arXiv:2610.28989v1 Announce Type: new Abstract: Customized agent deployments define policies over tools, resources, and execution conditions. Providing these policies in the task agent's prompt does not reliably prevent…

  27. arXiv cs.AIagents
    An Evidence-Driven Multi-Agent Compound AI System for Head and Neck Proton Radiotherapy Planning

    arXiv:2610.29010v1 Announce Type: new Abstract: Radiation treatment planning requires balancing competing objectives to satisfy clinical criteria while accommodating physicians' preferences. This study aims to develop an…

  28. arXiv cs.AIagents
    GenXR-Bench: Benchmarking Coding Agents for Interactive XR Development

    arXiv:2610.29014v2 Announce Type: replace Abstract: Coding agents are rapidly advancing from single-file generation to long-horizon repository-scale engineering, yet the evaluation of their capabilities to author interac…

  29. arXiv cs.AIagents
    Inheritance as an Admission Test for LLM Prompt Merge Operators

    arXiv:2610.29023v1 Announce Type: new Abstract: Large language model (LLM) agents are often improved by iterating until a fixed verifier is done. Once that verifier saturates, the loop has nothing left to climb. We inste…

  30. arXiv cs.AIresearch
    GRAIL: From Saliency to Semantics in Time-Series Explanation

    arXiv:2610.29036v1 Announce Type: new Abstract: Explaining a time-series model requires both locating the evidence and extracting meaningful knowledge from it. Yet a single timestep is not a semantic unit: the meaningful…

  31. arXiv cs.AIresearch
    AutoFraming: Synthesizing Dynamic Frames of C Code with LLMs

    arXiv:2610.29046v1 Announce Type: new Abstract: Large language models (LLMs) have shown considerable promise in synthesizing formal specifications from source code. However, existing approaches primarily focus on functio…

  32. arXiv cs.AIresearch
    Does Every Instance Count Equally? Order Effects in LLM Multi-Instance Processing

    arXiv:2610.29057v1 Announce Type: new Abstract: Users increasingly rely on large language models (LLMs) to analyse collections of independent inputs, such as product reviews or social media posts, and return a single agg…

  33. arXiv cs.AIresearch
    Context-Augmented, Session-Calibrated Blood Pressure Tracking from Photoplethysmography

    arXiv:2610.29091v1 Announce Type: new Abstract: Objective.To distinguish the contributions of acquisition context and photoplethysmography (PPG) to session-calibrated blood pressure (BP) tracking.Approach. The original c…

  34. arXiv cs.AIresearch
    Same Answer, Different Reasons: Trace-Level Divergence in Multilingual Large Language Models

    arXiv:2610.29092v1 Announce Type: new Abstract: Multilingual large language models are increasingly deployed in settings where visible reasoning traces support verification, education, and safety auditing, yet standard e…

  35. arXiv cs.AIresearch
    GRAM: Group-wise Rank-Aware Model Merging via Subspace Alignment

    arXiv:2610.29110v1 Announce Type: new Abstract: Merging different models into a single model is highly desirable for multi-task deployment, particularly in regulated domains like healthcare. In such settings, models are…

  36. arXiv cs.AIagents
    Recursive Self-Improvement on a Budget: Scoring Code Edits Before They Run

    arXiv:2610.29121v1 Announce Type: new Abstract: A coding agent that rewrites its own scaffold has to choose which proposed edit to expand before that edit has been evaluated, and the search then has to return one agent.…

  37. arXiv cs.AIresearch
    StochIKM: Automated High-Fidelity Reconstruction of Individual Patient Data from Published Kaplan-Meier Curves

    arXiv:2610.29122v2 Announce Type: replace Abstract: Individual patient data are the gold standard for secondary analysis of time-to-event evidence, but they are rarely released, and reconstruction from a published Kaplan…

  38. arXiv cs.AIresearch
    NormTune: Norm-Guided Parameter-Efficient Fine-Tuning for Reasoning-Intensive Tasks

    arXiv:2610.29134v1 Announce Type: new Abstract: Full fine-tuning has achieved remarkable success on reasoning-intensive tasks, but it often requires substantial GPU resource consumption. Parameter-efficient fine-tuning (…

  39. arXiv cs.AIagents
    LaVGuard: Selective Decoding for Contextual Value Drift

    arXiv:2610.29135v1 Announce Type: new Abstract: A content-safe response can still promote priorities that conflict with its task: an assistant may demand compliance when asked to preserve autonomy. We study contextual va…

  40. arXiv cs.AIagents
    Steering Black-Box Large Language Model Agents with Pitfall Anticipation World Model

    arXiv:2610.29139v1 Announce Type: new Abstract: Frontier black-box Large Language Model (LLM) agents are proficient at long-horizon reasoning and precise action generation. However, when it comes to a specific agentic ta…

  41. arXiv cs.AIresearch
    TeachBack: Learning to Teach via Bidirectional Preference Optimization for On-Policy Self-Distillation

    arXiv:2610.29167v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) enables a language model to learn from a Teacher instantiated from the same model but given access to privileged information, such as a r…

  42. arXiv cs.AIresearch
    When Multiple Choices Are Correct: Asymmetric Probability Allocation in Jev and Other Decision Models

    arXiv:2610.29217v1 Announce Type: new Abstract: Decision models return normalized probability distributions over candidate choices, which downstream applications can use to select among choices. Although their providers…

  43. arXiv cs.AIresearch
    From Scores to Safe Sets: Exact Safety--Constrained Decoding for Medication Recommendation

    arXiv:2610.29228v1 Announce Type: new Abstract: Recent generative medication recommendation systems ultimately produce sets of drugs, but drug--drug interaction (DDI) constraints depend on the set as a whole. A natural p…

  44. arXiv cs.AIagents
    CrashGym: Measuring the Decision Value of Experimentation for LLM Agents in Counterfactual Market Crashes

    arXiv:2610.29245v1 Announce Type: new Abstract: Language-model agents are increasingly asked to run experiments, yet benchmarks rarely measure whether those experiments improve the decisions they are meant to inform. We…

  45. arXiv cs.AIresearch
    ARCANA: A Benchmark for Abstraction and Analogical Reasoning

    arXiv:2610.29271v3 Announce Type: replace Abstract: Analogical reasoning is widely considered a fundamental component of human intelligence. Few benchmarks are designed to explicitly test far analogical reasoning - reaso…

  46. arXiv cs.AIresearch
    Same Probabilities, Different Advice: Gain-Loss Framing Effects in High-Stakes LLM Decision Support

    arXiv:2610.29294v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to support consequential decisions, yet their reliability under equivalent representations of uncertainty remains unclear…

  47. arXiv cs.AIresearch
    LLM-Based Exogenous World Modeling for Dynamic Scheduling

    arXiv:2610.29308v1 Announce Type: new Abstract: Dynamic scheduling requires dispatching online arrivals while anticipating future jobs, as poor decisions can compound downstream costs under nonlinear tardiness objectives…

  48. arXiv cs.AIresearch
    SpatialBrain: Spatial Intelligence Growing from Experience

    arXiv:2610.29317v1 Announce Type: new Abstract: Spatial reasoning requires more than access to geometric tools: a reasoner must decide when direct observation is sufficient and when to reconstruct, measure, or change ref…

  49. arXiv cs.AIagents
    AgentMonopoly: Behavioral Patterns and Persona Control in LLM Agents

    arXiv:2610.29330v2 Announce Type: replace Abstract: How do LLM agents' strategies differ, and how much can instructions to adopt a persona change their behavior over a game? We study these questions with AgentMonopoly, a…

  50. arXiv cs.AIagents
    From Prompts to Posteriors: Can LLM Agents Perform Bayesian Inference in Context?

    arXiv:2610.29331v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly applied across the scientific discovery pipeline, from synthesizing literature to generating hypotheses to informing experimen…