Search: “agents”

InstantMimic: A High Performance System for Learning Physics-based Skills in Seconds

arXiv:2609.09821v1 Announce Type: cross Abstract: Physics-based character control is a long-standing challenge in computer graphics and robotics, requiring policies that satisfy complex dynamics while

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Large Language Models Transform Organic Synthesis From Reaction Prediction to Automation

DGX agent

arXiv:2508.05427v2 Announce Type: replace Abstract: Large language models (LLMs) are beginning to reshape how organic-synthesis workflows are represented, queried, planned, and connected to experiment

safetyarxiv-cs-ai

10 Sept 2026

Tutorials

Learning Counterfactual World Models for Embodied Reasoning under Partial Observability

arXiv:2609.05834v1 Announce Type: new Abstract: World models promise a general route to embodied intelligence: learn predictive dynamics once, then reason, plan, and act with them. Increasingly, the r

tutorialsarxiv-cs-ai

Looped GPT-BERT: Trading Parameters for Computation in Small Language Modeling

model-releasesarxiv-cs-cl

arXiv:2609.09691v1 Announce Type: new Abstract: When training data are limited, increasing parameter count is not the only way to improve language-model performance. A small parameter set, when repeat

ObGynLongBench: Revealing the Evidence-to-EHR Gap in Longitudinal EHR Decision-Making

arXiv:2609.07601v1 Announce Type: cross Abstract: The application of large language models (LLMs) to personalized medical assistants has garnered growing interest. However, existing medical benchmarks

Open Tabular Insight Extraction: Where Do We Stand, and Where Should We Go?

arXiv:2609.07629v1 Announce Type: cross Abstract: Democratizing access to the knowledge held in large corpora of tables such as data lakes is emerging as a central research challenge. Research in this

researcharxiv-cs-ai

Optimal Value Inference for Reinforcement Learning

arXiv:2609.09981v1 Announce Type: cross Abstract: We study offline inference for the optimal value in reinforcement learning. Two new nuisances are derived as fixed points of a self-induced Bellman eq

Programmable World Model

arXiv:2609.10540v1 Announce Type: new Abstract: Recent video world models generate increasingly realistic and interactive visual experiences, yet lack reliable mechanisms for maintaining persistent wo

Silent Revision: Measuring Undisclosed Change in the Safety Frameworks of Frontier AI Developers

arXiv:2609.08789v1 Announce Type: cross Abstract: Frontier AI developers publish safety frameworks that commit them to evidencing whether their models are dangerous. The European Union and California

safetyarxiv-cs-ai

Sparks of In Silico Cognitive Science: Theories from Simulated Data Can Generalize to Humans

arXiv:2609.08003v1 Announce Type: new Abstract: Behavioral foundation models have been proposed as stand-ins for human participants across settings, but it is unclear whether theories discovered on th

researcharxiv-cs-ai

StochBench: A Domain-Specific Benchmark for Stochastic Processes in Lean

model-releasesarxiv-cs-cl

arXiv:2609.09264v1 Announce Type: new Abstract: Leading benchmarks for formal theorem proving with large language models are small collections drawn from competition math, such as the IMO and Putnam,

TTGBench: Benchmarking Topological Evolution and Semantic Drift in Text-attributed Temporal Graphs

arXiv:2609.08226v1 Announce Type: new Abstract: Temporal graph learning models the evolution of dynamic systems, where both structural interactions and semantic states change over time. However, exist

xDailyBench: Benchmarking LLMs on Professional Consultation for Real-Life Problems

arXiv:2609.07784v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for everyday assistance, yet existing benchmarks only partially reflect the requests users naturally

A New Strategy for Artificial Intelligence: Training Foundation Models Directly on Human Brain Data

arXiv:2601.12053v2 Announce Type: replace-cross Abstract: While foundation models have achieved remarkable results across a diversity of domains, they still rely on human-generated data, such as text,

researcharxiv-cs-lg

AD-FM: Multimodal LLMs for Anomaly Detection via Multi-Stage Reasoning and Fine-Grained Reward Optimization

arXiv:2508.04175v2 Announce Type: replace Abstract: While Multimodal Large Language Models (MLLMs) demonstrate remarkable capabilities across diverse domains, their application to specialized anomaly

Ambient @ EgoProactive 2026 : Proactive Egocentric Assistance with Visually Grounded Supervision

arXiv:2609.07099v1 Announce Type: new Abstract: We present our submission to the EgoProactive track of the ECCV 2026 Wearable AI Challenge, which ranked first in the large-model division and second in

Beyond the Verdict: Evidence-Aligned Evaluation of Visual Prompt-Injection Guardrails

arXiv:2609.05535v1 Announce Type: new Abstract: Verdict-only evaluation does not reveal whether a vision-language model (VLM) used the visual evidence that should support its decision. We study this p

BlueprintAgent: Constraint-Triggered Targeted Revisits for Simulation-Ready Generation from Scanned Structural Blueprints

arXiv:2609.07362v1 Announce Type: cross Abstract: Converting in-service reinforced-concrete (RC) building blueprints into simulation-ready models---structured frame representations that support determ

Distributed Secure Learning Control for Large-scale Multirobots under Stealthy Actuator Attacks

arXiv:2609.06896v1 Announce Type: new Abstract: Distributed learning control for multirobot systems (MRS) offers significant flexibility in presence of uncertainties but lacks provable performance gua

DriveZero: End-to-End Driving Beyond Human Demonstrations

arXiv:2609.06055v1 Announce Type: new Abstract: Most end-to-end autonomous-driving systems learn by imitating human driving logs, leaving their learned behavior constrained by the quality and behavior

Flow3D-OPD: Multi-Teacher On-Policy Distillation for 3D Geometry Generation with Flow-Matching Diffusion Transformer

arXiv:2609.07137v1 Announce Type: new Abstract: Recent image-to-3D generation models built on flow-matching diffusion Transformers (DiT) can produce high-fidelity meshes, yet their post-training strat

safetyarxiv-cs-cv

HealthLoopQA: A Context-Aware Question Answering Benchmark for Interpreting Wearable Monitoring Data in Diabetes Care

model-releasesarxiv-cs-lg

arXiv:2609.06976v1 Announce Type: new Abstract: As medical wearables become integrated into daily chronic disease care, effectively interpreting longitudinal monitoring data is essential for patients

How to Learn from What a Human Would Avoid? Intervention-Aware World Models with Real-World RL for Dexterous Manipulation

arXiv:2609.06009v1 Announce Type: new Abstract: Multi-fingered dexterous manipulation remains a frontier for real-world reinforcement learning (RL) due to the high-dimensional action space and the pro

Hyperspectral Trajectory Image for Multi-Month Trajectory Anomaly Detection

arXiv:2603.25255v2 Announce Type: replace Abstract: Trajectory anomaly detection underpins applications from fraud detection to urban mobility analysis. Dense GPS methods preserve fine-grained evidenc

Information-Guided Safe Reinforcement Learning for Autonomous Gas Source Localization using sUAS

arXiv:2609.05569v1 Announce Type: new Abstract: The autonomous localization of fugitive gas emissions using small Unmanned Aircraft Systems (sUAS) constitutes a fundamentally ill-posed inverse problem

local-aiarxiv-cs-ro

Local and Global Stability in Performative Reinforcement Learning

arXiv:2609.06467v1 Announce Type: new Abstract: In performative reinforcement learning the deployed policy shapes the environment that generates the learner's future data, and the natural solution con

MamMA: A Mamba-Based Pedestrian Trajectory Prediction Algorithm Considering Occupancy Map and Pedestrian Awareness States

arXiv:2609.08041v1 Announce Type: new Abstract: Many pedestrian trajectory prediction algorithms have been proposed to improve the safety of navigation for mobile robots working in human-robot coexist

Miles v0.1: Production-Level Post-Training

model-releasesarxiv-cs-lg

arXiv:2609.08368v1 Announce Type: new Abstract: We present Miles v0.1, a full-stack, production-ready system for frontier post-training. Building upon the clean design of slime, Miles designs each sta

Mind-to-Face: Neural-Driven Photorealistic Avatar Synthesis via EEG Decoding

arXiv:2512.04313v2 Announce Type: replace Abstract: Current expressive avatar systems rely heavily on visual cues, failing when faces are occluded or when emotions remain internal. We present Mind-to-

researcharxiv-cs-cv

MLIP Detective: Active Failure Mode Discovery Beyond Benchmark Scores for Machine-Learning Interatomic Potentials

model-releasesarxiv-cs-lg

arXiv:2609.08399v1 Announce Type: new Abstract: Universal machine-learning interatomic potentials (u-MLIPs) aim to generalize across diverse configurations. Benchmarks enable reproducible evaluation b

Moment-Matching Probabilistic Data Association for Optimization-Based SLAM

arXiv:2609.05941v1 Announce Type: new Abstract: Optimization-based simultaneous localization and mapping (SLAM) makes it possible to reduce accumulated navigation errors of sensing platforms by return

local-aiarxiv-cs-ro

NEST: Narrative Event Structures in Time for Long Video Understanding

arXiv:2606.19706v2 Announce Type: replace Abstract: Recent progress in vision-language models has enabled processing of increasingly long video sequences, but handling extended token streams does not

Proactive Context-Forecasted Safety Constraints for Nonstationary Reinforcement Learning

arXiv:2609.08080v1 Announce Type: new Abstract: Ensuring safety in reinforcement learning under nonstationarity requires anticipating changes in risk before they lead to unsafe behavior. Existing appr

PV-WM: A Heterogeneous Micro-Macro World Model for Articulated Pedestrian-Vehicle Co-Rollout

arXiv:2609.07328v1 Announce Type: new Abstract: Local pedestrian-vehicle forecasting spans heterogeneous physical scales: pedestrians combine root locomotion with articulated motion, whereas vehicles

local-aiarxiv-cs-ro

Remotely Detectable Keyed Communication through Motion

arXiv:2609.08920v1 Announce Type: new Abstract: Messages from electronic devices are conventionally received as text, audio, or radio signals. But robots move with rich, articulate motion in the real

Rethinking Safety for Generalist Robots

arXiv:2609.06326v1 Announce Type: cross Abstract: Generalist robots promise to transform our society: the same system that prepares a meal or folds laundry might also repair a car, inspect infrastruct

SAM3-O2D2: Zero-Shot Object Out-of-Distribution Detection by Object Class Prompting of the SAM3-Image Model

arXiv:2609.08281v1 Announce Type: new Abstract: Object detectors have shown remarkable performance in various fields, among these medical imaging, surveillance, and autonomous driving. However, they a

Applications

SWE-Tester: Training Open-Source LLMs for Issue Reproduction in Real-World Repositories

arXiv:2601.13713v2 Announce Type: replace-cross Abstract: Software testing is crucial for ensuring the correctness and reliability of software systems. Automated generation of issue reproduction tests

applicationsarxiv-cs-lg

Temporal-Causal Inference for Reinforcement Learning via Automata Learning

arXiv:2609.07461v1 Announce Type: new Abstract: We consider reinforcement learning in environments with dynamics that undergo an irreversible phase transition governed by a hidden temporal pattern. Th

The Price of Consistency: Exploiting Visual Anchors for Multimodal Jailbreaking in Video Generation

arXiv:2609.07216v1 Announce Type: new Abstract: The rapid evolution of video generation has shifted the paradigm from pure text-driven to multi-conditional controllable generation, with reference imag

A Schema Bounded Language Model for Refining Robot Policies Without Destabilizing Local Learning

arXiv:2609.05133v1 Announce Type: cross Abstract: This paper addresses navigation by composite heterogeneous robots in a decentralized system when policy reasoning and local control operate at differe

local-aiarxiv-cs-ai

Large Language Models for HVAC Operations in Building Energy Systems: A Critical Review of Methods, Applications, and Deployment Readiness

arXiv:2609.05314v1 Announce Type: new Abstract: Building automation systems generate rich sensor data yet remain insight-poor because heterogeneous point naming, missing metadata, and fragmented docum

safetyarxiv-cs-ai

LIBERO-RECOVER: Beyond Task Success Towards Failure Recovery in Robotic Manipulation Models

model-releasesarxiv-cs-ro

arXiv:2609.05178v1 Announce Type: new Abstract: Vision-Language-Action (VLA) or World Action (WAM) models have recently demonstrated remarkable performance in robotic manipulation. On LIBERO, SOTA met

One Diffusion Model, Two Roles: Guided Trajectory Planning and Safety-Critical Scenario Generation in Closed-Loop Simulation

arXiv:2609.04921v1 Announce Type: cross Abstract: Diffusion probabilistic models can capture the multi-modal, interaction-rich distribution of joint future trajectories in driving scenes. We show that

Refuse without Refusal: A Structural Analysis of Safety-Tuning Responses for Reducing False Refusals in Language Models

arXiv:2609.04714v1 Announce Type: cross Abstract: Striking a balance between helpfulness and safety remains a fundamental challenge in aligning large language models. To achieve this balance, models s

safetyarxiv-cs-ai

RISE: Recursive Improvement via Self-Extrapolating Policy Distillation

arXiv:2609.05295v1 Announce Type: new Abstract: On-policy distillation (OPD) provides dense, per-token supervision for language model post-training, but its effectiveness is bottlenecked by teacher qu

RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?

arXiv:2609.05324v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown promising progress in language-conditioned robotic manipulation. However, existing datasets and benchma

The History Is the Detector: Executing CVE Patch History, End-to-End

arXiv:2609.05335v1 Announce Type: cross Abstract: Public vulnerability databases collect rich information about known software flaws, including their weakness types, affected components, and related p

researcharxiv-cs-ai