Search: “tools”

Recurrent Latent Visual Search for GUI Grounding

arXiv:2610.05185v1 Announce Type: new Abstract: GUI grounding is a critical capability for GUI agents powered by vision-language models, helping them execute user instructions by locating the correspo

safetyarxiv-cs-cv

Recursive Self-Improvement of Visuomotor Policies through Local Recovery Supervision

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DGX agent

arXiv:2610.05151v1 Announce Type: new Abstract: Visuomotor policies can execute familiar tasks yet lack the corrective behavior needed after their own mistakes. We present a framework for recursive se

safetyarxiv-cs-ro

6 Oct 2026

Recursive Video In-Context Learning for Agentic Robot

arXiv:2610.06843v1 Announce Type: new Abstract: LLM agents that orchestrate frozen vision-language-action (VLA) policies improve across episodes through text memory, which records what the agent did b

agentsarxiv-cs-ro

Revisiting Ground-Truth Synthesis from High-Speed Video: Exact Validity Conditions and an Audited Consumer Capture Corpus

arXiv:2610.05298v1 Announce Type: new Abstract: Motion-deblurring datasets are commonly synthesised by averaging N consecutive high-frame-rate frames and labelling the result with the central frame. W

researcharxiv-cs-cv

RobotUse: Allocating Computation, Context, and Decisions

arXiv:2610.04929v1 Announce Type: new Abstract: Robot agents must connect their intended actions to observed outcomes while retaining the context needed to revise their choices over repeated attempts.

agentsarxiv-cs-ro

SoccerTrack v2: A Full-Pitch Panoramic Video Dataset for Game State Reconstruction and Ball Action Spotting

model-releasesarxiv-cs-cv

arXiv:2508.01802v2 Announce Type: replace Abstract: Soccer analytics draws on two kinds of information: spatio-temporal data describing where players and the ball are, and event data describing what t

Stability-Shaped Deep Graph Learning

arXiv:2610.06344v1 Announce Type: new Abstract: In deep graph neural networks, increasing depth enlarges the receptive field but often leads to over-smoothing, where node representations tend to align

The Llama 3 Herd of Models

model-releasesarxiv-cs-lg

arXiv:2407.21783v3 Announce Type: cross Abstract: Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It i

ThunderSyncRL: Lossless Acceleration of Agentic Reinforcement Learning

arXiv:2610.05935v1 Announce Type: new Abstract: Language models are moving beyond generating answers to pursuing long-horizon goals in interactive environments. Post-training these agents requires lon

safetyarxiv-cs-lg

Towards Optimal Valve Prescription for Transcatheter Aortic Valve Replacement (TAVR) Surgery: A Machine Learning Approach

arXiv:2512.09198v2 Announce Type: replace Abstract: Transcatheter Aortic Valve Replacement (TAVR) has emerged as a prominent, minimally invasive treatment for patients with severe aortic stenosis, a l

Valid Stopping in Adaptive Generator-Verifier Loops

model-releasesarxiv-cs-lg

arXiv:2610.06432v1 Announce Type: cross Abstract: Numerous agentic workflows are based on a generator-verifier loop: a generator proposes candidates, a cheap verifier scores them, and the workflow ter

VideoTapestry: Query-Adaptive Memory Refinement for Multi-Agent Long-Video Understanding

model-releasesarxiv-cs-cv

arXiv:2610.06672v1 Announce Type: new Abstract: Long-video understanding places substantial demands on memory, as answering questions often requires retrieving information distributed across extended

Hardware

WAMJET: A Harness for World Action Model Acceleration

arXiv:2610.03797v1 Announce Type: new Abstract: World Action Models (WAMs) leverage pretrained video foundation models for robot manipulation, but their large backbones and video-action co-prediction

hardwarearxiv-cs-cv

When the Cross-Silo Federation Goes Offline: Continual Learning for Site Onboarding with Limited Unlabeled Data

arXiv:2610.05598v1 Announce Type: new Abstract: An organization often holds too little labeled data to train a model that generalizes, and the records that would supply the rest sit with organizations

agentsarxiv-cs-lg

A GHOST in Long-Horizon Agents: Governance Hazard from Overlooked Safety Constraints across Turns

arXiv:2610.02664v1 Announce Type: new Abstract: Long-horizon agents are now playing an increasingly significant role in assisting humans with complex problem-solving. However, it is exactly their exte

Automating the Application of HCI Principles: Skills for On-Demand UI Construction, the Human-AI Space to Think, and the Future of HCI

arXiv:2610.02369v1 Announce Type: cross Abstract: Human-computer interaction (HCI) is in the middle of a transition: large language models can now generate functional user interfaces (UIs) on demand f

Beyond Predefined Sinks: Security-Aware Dependency Analysis for LLM Agents

arXiv:2610.03014v1 Announce Type: cross Abstract: Large language model (LLM)-based agents increasingly connect model-generated decisions to security-sensitive software capabilities such as command exe

agentsarxiv-cs-ai

Hardware

Coco: An Agentic Copilot for the Hardware--Software Co-Design Lifecycle

arXiv:2610.02376v1 Announce Type: cross Abstract: Co-designing ML models and the accelerators that run them is an unusual reasoning task: architects must draw confident, high-stakes conclusions about

hardwarearxiv-cs-ai

Applications

Compound AI System Reliability: A Failure Taxonomy and Resilience Pattern Catalog from 150 Production Incidents

arXiv:2610.02503v1 Announce Type: cross Abstract: Deploying compound AI systems reliably and safely requires understanding failure modes that emerge at component boundaries, not within individual mode

applicationsarxiv-cs-ai

Dissecting model behavior through agent trajectories

arXiv:2606.17454v3 Announce Type: replace Abstract: AI agent performance is not just a modeling problem, it is fundamentally a systems problem. The advanced capabilities of models are realized through

Dynamic LLM Routers are Often Misguided

arXiv:2610.02762v1 Announce Type: new Abstract: Dynamic LLM routers promise to cut inference costs by sending each query to the cheapest model that can answer it correctly. We analyze six commercial r

EpiWorld: Grounding LLM Policy Agents in Epidemiological World Models

arXiv:2610.02744v1 Announce Type: new Abstract: Epidemic intervention policies are textual artefacts that human decision-makers interpret, justify, and revise through natural language, making large la

safetyarxiv-cs-cl

Evaluating and Improving the Robustness of Large Language Models to Input Sequence Variations

model-releasesarxiv-cs-cl

arXiv:2610.02432v1 Announce Type: cross Abstract: Large language models (LLMs) in production systems face prompt injections, trojans (backdoors), and manipulation of automatic quality metrics. This th

Evaluating the Retrieval Robustness of Large Language Models

arXiv:2505.21870v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) generally enhances large language models' (LLMs) ability to solve knowledge-intensive tasks. But RAG coul

From Patching to Pruning Visual Computation in Vision Language Models

arXiv:2610.03389v1 Announce Type: new Abstract: Vision language models (VLMs) incur substantial inference cost because every visual token is processed by the attention and MLP projections of every dec

researcharxiv-cs-cv

GeoScaffold: Learning Compact Geometric Latents via Reconstruction for Efficient Vision-Language Navigation

arXiv:2610.02697v1 Announce Type: cross Abstract: Recent vision-and-language navigation (VLN) systems increasingly adopt streaming Video-LLM policies that map egocentric RGB observations and instructi

safetyarxiv-cs-cv

Local Ai

How Artificial Intelligence LLM Engines Shape the Global Conflict Information Environment

arXiv:2607.14197v2 Announce Type: replace Abstract: Artificial Intelligence (AI) answer engines now field a growing share of the questions that analysts, scholars, and the public ask about issues of p

local-aiarxiv-cs-ai

HyperBrowseComp: A Multilingual and Multimodal Stress Test for Web-Browsing Agents

arXiv:2610.03574v1 Announce Type: new Abstract: We introduce HyperBrowseComp, a multilingual and multimodal browsing benchmark comprising 423 manually authored and human-validated questions across 13

Lightweight, Rubric-Guided Trajectory Evaluation for Production AI Agents

arXiv:2610.03315v1 Announce Type: new Abstract: Trajectory evaluation is essential for improving the reliability of LLM-based agents, but production use makes it expensive to run repeatedly. Modern ag

safetyarxiv-cs-ai

Lost in the Request: How Communication Variation Disrupts Retrieval and Action in Email Agents

arXiv:2610.02627v1 Announce Type: new Abstract: An email assistant should not complete less work simply because a user phrases the same request differently. Yet most benchmarks test each task with onl

agentsarxiv-cs-ai

MeshQuery: Agentic Seam Planning for UV Parametrization

arXiv:2610.02507v1 Announce Type: new Abstract: We present MeshQuery, a training-free agentic approach to automatic UV unwrapping of production-grade quad meshes. A Vision-Language Model (VLM) plans a

agentsarxiv-cs-cv

Mitigating Private Data Leakage in LLMs with Whiteout

arXiv: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

safetyarxiv-cs-ai

Multimodal reasoning for broadly neutralizing antibody discovery from label-free human B cell repertoires across virus families

arXiv:2610.03160v1 Announce Type: cross Abstract: Discovering broadly neutralizing antibodies (bnAbs) from human natural immune repertoires remains a fundamental challenge in immunology, hindered by:

researcharxiv-cs-ai

NeuroLens: Learning Latent Embeddings of Neural Semantics from Chronic Recordings

arXiv:2610.02864v1 Announce Type: new Abstract: Understanding how neural activity represents higher-order cognition and how these representations evolve over time has long been a central pursuit in ne

NeutronGym: Physics-Graded Neutron Instrument Design for LLM Agents

arXiv:2610.03631v1 Announce Type: new Abstract: Designing a scientific instrument tests whether language-model agents can do physics rather than recall it, provided the grading cannot be argued with.

OpenRUA: Robot-Use Agents Are Zero-Shot Visuomotor Policies

model-releasesarxiv-cs-ro

arXiv:2610.02459v1 Announce Type: new Abstract: Coding agents are extending their reach into the physical world by writing and executing robot control programs. One might expect the agents to use the

Applications

Predictor-Guided Latent Space Codon Optimization for Maximizing Protein Expression

arXiv:2610.03098v1 Announce Type: new Abstract: Codon optimization, the process of selecting synonymous codons to improve mRNA translation efficiency and protein expression, is central to therapeutic

applicationsarxiv-cs-ai

Prospective Hindsight: Self-Calibrating Reinforcement Learning via Prediction-Reality Gaps

arXiv:2610.02740v1 Announce Type: cross Abstract: Reinforcement learning for long-horizon agents relies on purely retrospective training signals: credit is assigned only after observing environmental

safetyarxiv-cs-ai

Reasoning Models Are Accurate but Unsound on Identification

arXiv:2610.03519v1 Announce Type: new Abstract: A reasoning model asked whether a causal effect is recoverable from observational data can fail in two ways: it refuses an identifiable query or answers

ReFract: Benchmarking Perspective Awareness in Language Model Agents with Text World Models

arXiv:2610.03356v1 Announce Type: new Abstract: Large Language Model (LLM) agents are increasingly deployed in high-stakes settings such as industrial maintenance and equipment fault troubleshooting,

RT-SFT: Text Style Transfer from Non-Parallel Corpora by Roundtrip Translation

arXiv:2602.15013v2 Announce Type: replace Abstract: Text style transfer (TST) is naturally a supervised task - rewrite a sentence in a target style while preserving its meaning - yet the parallel corp

researcharxiv-cs-cl

SecJev: Bringing Security Expertise to System One Decision Models

arXiv:2610.03073v1 Announce Type: cross Abstract: Security workflows need models that turn complex observations and explicit policies into decisions. System One models introduced by Jev return typed p

safetyarxiv-cs-cl

SoftGene: Protein Language Model-Enhanced Soft Prompting for Interpretable Gene Set Annotation

arXiv:2610.03029v1 Announce Type: new Abstract: Gene set analysis is a cornerstone of functional genomics, yet it remains labor-intensive and heavily dependent on manual curation and expert biological

TasteBench: Multimodal Benchmark for Sensory Prediction, from Molecules to Sustainable Foods

arXiv:2610.02599v1 Announce Type: new Abstract: Sustainable protein discovery lacks the fast computational proxies, analogous to molecular docking or density functional theory, that accelerate drug an

Theoretical Lower Bounds on the Robustness of Deep ReLU Networks

arXiv:2602.18674v2 Announce Type: replace Abstract: We present a theoretical study of the robustness of parameterized neural networks to random input perturbations. Specifically, we analyze local robu

WebUIProof: Benchmarking WebUI Code Generators with UI-Agent Execution Harness

arXiv:2610.02617v1 Announce Type: cross Abstract: Evaluating WebUI code generation at scale is difficult: outputs may compile and look plausible yet fail under user interaction, and prior benchmarks l

Local Ai

When Does Synthetic Relational Data Teach Models to Use Relations? Tracing Predictive Structure from Pretraining Data to Model Behavior

arXiv:2610.03057v1 Announce Type: new Abstract: Relational foundation models are increasingly pretrained on synthetic databases, yet downstream benchmarks reveal little about why one synthetic corpus

local-aiarxiv-cs-lg

When to Compile a Computer-Use Agent? Measuring Payback and Making Compilation Decisions for Token Efficiency

arXiv:2610.02932v1 Announce Type: new Abstract: Compiling GUI procedures that agents execute repeatedly into programs can reduce their token costs. However, measuring payback and deciding when to comp

agentsarxiv-cs-ai