Search: “safety”

How Strongly Should Task State Influence an LLM Agent?

arXiv:2609.25686v1 Announce Type: cross Abstract: Long-horizon assigned work requires an LLM agent to track the state of a task: which steps are done, blocked, cancelled, or open to repetition. Agent

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HYDRA: Proactive Android Malware Drift Adaptation via Hierarchical Graph Contrastive Learning

DGX agent

arXiv:2609.26352v1 Announce Type: cross Abstract: Concept drift, driven by the rapid evolution of Android malware, severely degrades the performance of machine learning detectors. Current adaptation s

safetyarxiv-cs-lg

23 Sept 2026

Imperfection for Precision: Upcycling Imperfect Data for High-Precision Robotic Manipulation

arXiv:2609.26672v1 Announce Type: new Abstract: Training vision-language-action (VLA) models for high-precision manipulation typically requires task-specific, high-quality data (e.g., teleoperation),

Information-Theoretic Decoupled Prompt Tuning for Continual Learning

arXiv:2609.26257v1 Announce Type: new Abstract: Continual learning (CL) aims to incrementally acquire knowledge from sequential data while avoiding catastrophic forgetting. Recently, prompt tuning has

JAMB: Joint Action-Motion Diffusion for Bimanual Manipulation

arXiv:2609.25322v1 Announce Type: new Abstract: Coordinated bimanual manipulation is challenging because the motion of either arm can alter the shared 3D scene and thereby affect the other arm. Yet mo

KwaiMind Technical Report

arXiv:2609.26375v1 Announce Type: new Abstract: Commercial image editing requires product identity preservation, accurate text rendering, and user appeal alongside general editing quality. We present

LADDER: Graph-Guided Diffusion Language Models for Efficient Multi-Hop Reasoning

arXiv:2609.24346v1 Announce Type: new Abstract: Graph Retrieval-Augmented Generation (GraphRAG) has remarkably enhanced large language models on complex reasoning by leveraging structured entity topol

Learning Air-Ground Motion Control with Temporal Mode Switching and Cross-Terrain Tracking

arXiv:2609.26564v1 Announce Type: new Abstract: Passive-wheeled terrestrial-aerial bimodal vehicles (TABVs) combine aerial mobility with energy-efficient ground locomotion. However, reliable air-groun

Learning Diagnostic Reasoning for Decision Support in Toxicology

arXiv:2603.29608v2 Announce Type: replace Abstract: Acute poly-substance intoxication requires rapid, life-saving decisions under substantial uncertainty, as clinicians must rely on incomplete ingesti

Learning to Plan in Human-Robot Collaboration: Multimodal Reinforcement Learning for Adaptive Interaction

arXiv:2609.25274v1 Announce Type: new Abstract: Robot assistants for older adults and people with disabilities need to perform collaborative tasks with users effectively. The core component of these s

MatchFusion: Explicit-Implicit Instance Matching for Spatio-Temporal Multimodal Autonomous Driving

arXiv:2609.25860v1 Announce Type: cross Abstract: Sparse instance representations provide a compact interface for spatial LiDAR-camera and temporal past-current interaction in multimodal perception an

MATE: Multi-Agent Virtual Teleoperation Platform for Humanoid Collaboration Data Collection

arXiv:2609.26520v1 Announce Type: new Abstract: Humanoid robots require diverse embodied experiences to acquire complex loco-manipulation and collaborative skills. However, existing humanoid data pipe

MATES: Learning Multi-Agent Interactions by Transforming Observations for Frozen Single-Agent Policies

arXiv:2609.26010v1 Announce Type: cross Abstract: Multi-agent reinforcement learning (MARL) commonly trains decentralized policies from scratch, requiring agents to acquire individual task competence

MAVP: Map-Aware Visuomotor Policies for Mobile Manipulation

arXiv:2609.26378v1 Announce Type: cross Abstract: Successful mobile manipulation requires coordinated base and arm motion while maintaining accurate spatial positioning. However, demonstration-trained

MicroPush: A Lightweight Simulator for Sim-to-Real Microrobotic Pushing and Assembly

arXiv:2602.23607v2 Announce Type: replace Abstract: Developing learning-based autonomy for microrobotic manipulation is difficult because physical trials are slow, variable, and poorly suited to large

MirrorDistill: Illumination-Aware Latent Distillation for Efficient Low-Light Restoration

arXiv:2609.25331v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) is an im- portant component of visual sensing systems operating under degraded illumination, including nighttime surv

MMAP: Multimodal Missing-Aware Pretraining for Longitudinal Alzheimer's Prediction

arXiv:2609.26617v1 Announce Type: cross Abstract: Clinical decision making heavily relies on predicting the disease progression trajectory by seeking to understand patient's health status which is cha

PACT: From Credit Assignment to Critic Alignment

arXiv:2609.26355v1 Announce Type: new Abstract: Reinforcement learning has become a central component of large language model (LLM) post-training, yet token-level credit lacks a generally accepted mat

PAKT: Physically-Aligned Kinesthetic Teaching for Reinforcement Learning

arXiv:2609.25630v1 Announce Type: new Abstract: Real-world reinforcement learning (RL) systems still struggle with the demands of contact-rich industrial manipulation, including micrometer-level preci

PhyVisGen: Physically and Visually High-Fidelity Robotic Manipulation Data Generation

arXiv:2609.25653v1 Announce Type: new Abstract: Large-scale manipulation demonstrations are essential for learning robust visuomotor policies, yet real-world data collection is expensive and difficult

PLAT: Sparse Timed Keyframe Motion Tracking for Humanoid Control via Privileged Latent Transition Learning

arXiv:2609.25754v1 Announce Type: new Abstract: Humanoid motion tracking policies rely on dense frame-by-frame references, limiting their use as high-level motion controllers for planning and interact

Polynomial Scaling is Possible For Neural Operator Approximations of Structured Families of BSDEs

arXiv:2410.14788v4 Announce Type: replace-cross Abstract: Neural operator (NO) architectures learn nonlinear maps between infinite-dimensional function spaces and are widely used to accelerate simulat

Predict Before You Step: Auditable Occupancy Forecasting for Dynamic Obstacle Avoidance under Sparse Guidance

arXiv:2609.25969v1 Announce Type: new Abstract: Legged robots under sparse waypoint guidance must avoid moving obstacles using partial, rapidly changing LiDAR observations. We present LOOP (Latent-rec

ProcessLight: Process Supervision for Large Language Model Based Traffic Signal Control

arXiv:2609.22746v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently been introduced into traffic signal control (TSC) as decision agents due to their strengths in human-readable

Prompt Breadth and Rollout Refresh Interact in On-Policy Distillation

arXiv:2609.25048v1 Announce Type: new Abstract: How many prompts does on-policy distillation (OPD) need, and how does the answer depend on the student policies that generate its training responses? We

Recording Hand-Held Laparoscopic Instrument Motion in the Operating Room: Magnetometer-Free Fusion of Inertial, Range and Visual Sensing

arXiv:2609.25577v1 Announce Type: new Abstract: Most minimally invasive procedures are still performed with hand-held laparoscopic instruments, yet only the endoscopic video is retained; the instrumen

Recursive self-improvement of AI research agents

arXiv:2609.26457v1 Announce Type: cross Abstract: AI agents are beginning to automate research and development across the AI stack, from improving training efficiency to optimizing inference. A natura

Rethinking Length-Based Training: Batch Composition and Loss Normalization in Speech Token Language Models

arXiv:2609.25890v1 Announce Type: new Abstract: Short-to-long training is a simple curriculum for speech models, but its gains can be difficult to interpret. In speech token language models, length-ba

RoboMP-DINOv2: Prompts, Not Filters for Robust Robot Manipulation

arXiv:2609.25506v1 Announce Type: new Abstract: Robot manipulation policies must generalize across visual shifts while preserving scene context relevant to action. General-purpose vision encoders are

RouteRLT: Learning When and Which RL Specialist Should Control a Vision-Language-Action Policy

arXiv:2609.26467v1 Announce Type: new Abstract: Vision-language-action (VLA) models provide broad manipulation competence, but often struggle during the precision-critical stages that dominate contact

Sample, Simulate, Select: Physics-in-the-Loop Text-to-Motion for Humanoids Without Training

arXiv:2609.26420v1 Announce Type: new Abstract: Text-to-motion models generate plausible human motion but do not model a robot's dynamics; whole-body tracking controllers execute robot references reli

SG-CPG: Severity-Gated Central Pattern Generators for Adaptive Quadruped Locomotion under Continuous Actuator Degradation

arXiv:2609.25687v1 Announce Type: new Abstract: An animal with a weakened limb does not necessarily switch its gait, instead it unloads the affected limb, re-coordinates the remaining limbs, and scale

Skytopia: Monocular Drone Navigation with Action-Conditioned Latent World Models

arXiv:2609.26007v1 Announce Type: new Abstract: Monocular drone navigation requires reaching a goal in an unseen environment from a single forward-facing camera, which offers few cues for depth and sc

StepTrigger: Contact-State-Triggered Backdoor Attacks on VLM-Powered Legged Robots

arXiv:2609.26131v1 Announce Type: new Abstract: Large language models and vision-language models are increasingly used as high-level planners in robotic systems, using task goals and sensor summaries

Structured Decomposition for Reliable LLM-Generated Access Control Policies

arXiv:2609.24036v1 Announce Type: new Abstract: This paper presents an LLM-based system that translates natural-language access control policies (NLACPs) into executable Rego code for Open Policy Agen

Target alignment, dilution and forecast selection when cross-sectional forecasts share a common target

arXiv:2609.26303v1 Announce Type: cross Abstract: Forecasters often score the same units per date against one standardized realized outcome. We show that every standardized forecast splits exactly int

Teaching Reinforcement Learning and Humanoid Robotics to High-School Students: An Expert-Validated Curriculum Design on a Low-Cost Open Platform

arXiv:2609.25674v1 Announce Type: new Abstract: Lower cost open source robots and reinforcement learning (RL) simulation tools create new opportunities for precollege students to engage with contempor

Test-time Reinforcement Learning for Anomalous Video Understanding

arXiv:2609.26099v1 Announce Type: new Abstract: Anomalous video understanding aims to identify abnormal events in videos and interpret their semantic meanings beyond simple anomaly detection. Recent v

Text-only adaptation in LLM-based ASR through text denoising

arXiv:2601.20900v4 Announce Type: replace-cross Abstract: Adapting large language model (LLM)-based automatic speech recognition (ASR) systems to new domains using text-only data is a significant yet

The Law of Stop: Interruptibility, Injunctions, and the Governance of Agentic AI

arXiv:2609.22882v1 Announce Type: cross Abstract: On June 12, 2026, the U.S. government ordered Anthropic to bar foreign nationals from two of its most capable models within ninety minutes. Unable to

The Self Driving Portfolio: Agentic Architecture for Institutional Asset Management

arXiv:2604.02279v2 Announce Type: replace Abstract: Agentic AI shifts the investor's role from analytical execution to oversight. We present an agentic strategic asset allocation pipeline in which 44

Theory for groupoid equivariant neural networks: an approach for steerable CNNs on bounded domains

arXiv:2609.25987v1 Announce Type: new Abstract: Equivariant convolutional neural networks are usually built from a group acting globally on the space of signals. This hypothesis is inappropriate for m

Toward an Unbiased Collective Memory for Efficient LLM-Based Agentic 6G Cross-Domain Management

arXiv:2509.26200v2 Announce Type: replace-cross Abstract: Agentic artificial intelligence is a candidate enabler of Level-4 autonomy in sixth-generation (6G) networks, but agents reasoning over a shar

Train Where the Quantized Model Goes: On-Policy Distillation for Low-Bit Reasoning

arXiv:2609.26708v1 Announce Type: new Abstract: Quantization-aware distillation (QAD) restores much of the short-form question-answering performance lost to sub-3-bit quantization, yet leaves mathemat

Transcribe, Translate, and Optimize: Joint Reward Learning for Speech Translation

arXiv:2609.26536v1 Announce Type: new Abstract: In LLM-based speech translation, transcription-based chain-of-thought (CoT) suffers from a mismatch between reference transcripts used in supervised fin

Understanding Reliability in LLM-based Human Behavior Simulation

arXiv:2609.25066v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to simulate human survey responses and behavioral reactions, yet unreliable simulations can mislead s

What Does Chain-of-Thought Entropy Measure? A Channel Audit of Scaffolding, Routing, and Content

arXiv:2609.25039v1 Announce Type: cross Abstract: Entropy over chain-of-thought tokens decides which tokens receive the policy gradient, which get pruned, and whether a run has collapsed, yet each suc

What Drives Hierarchy-Aware Image Retrieval? Taxonomy Alignment, Objective Choice, and Geometry

arXiv:2609.25638v1 Announce Type: new Abstract: Foundation vision models provide strong generic representations, yet high class-level retrieval accuracy does not necessarily imply that an embedding re