Search: “safety”

RoboIRS: Inference-Time Internal Representation Steering for Generalist Robot Policies

arXiv:2610.04681v1 Announce Type: new Abstract: Vision-language-action (VLA) and world-action models (WAMs) often degrade under out-of-distribution task variations despite retaining partial task capab

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Robot Learning with Visual Predicted Force

DGX agent

arXiv:2610.04741v1 Announce Type: new Abstract: Force-aware manipulation typically relies on specialized force or tactile sensors. We show that force-aware manipulation can instead be achieved through

safetyarxiv-cs-ro

6 Oct 2026

Robotizing Human Videos with Physically Consistent Interactions

arXiv:2610.06137v1 Announce Type: new Abstract: Human videos offer scalable manipulation data, but the embodiment gap between human hands and robot manipulators limits their direct use. Existing video

ROOT: Discovering Rewards for User-Specified Embodied Behaviors

arXiv:2610.04250v1 Announce Type: new Abstract: Reinforcement learning for embodied control remains constrained by the difficulty of reward specification. Although recent large language model (LLM)-ba

Score-Calibrated Flow for Sampling from Unnormalized Densities with Applications to Generative Online Reinforcement Learning

arXiv:2610.04696v1 Announce Type: new Abstract: Diffusion and flow models provide expressive policy classes for online reinforcement learning (RL), enabling multimodal behaviors and improved performan

SEER: Self-Evolving Event Reasoning and Retrieval for Time Series Forecasting

arXiv:2610.04109v1 Announce Type: new Abstract: Real-world time series are frequently driven by exogenous events and structural shifts, rendering conventional forecasting based solely on historical nu

Selecting Long-Horizon Trajectories for Reliable and Efficient Terminal-Agent Training

arXiv:2610.05831v1 Announce Type: new Abstract: Terminal agents are commonly trained by imitating long teacher trajectories, yet how much of each trajectory to supervise remains unexplored. We study t

Sharp Convergence and Sample Complexity of Policy Mirror Descent for Average-Reward MDPs

arXiv:2610.04117v1 Announce Type: new Abstract: Policy mirror descent (PMD) has a mature finite-time theory in discounted Markov decision processes (MDPs), but less is known in the average-reward sett

Sharpen Without Search: On-Policy Distillation of Sequence-Level Power Distribution

arXiv:2610.06804v1 Announce Type: new Abstract: A language model can give a correct answer more probability than any single incorrect answer and still usually sample an incorrect one, because the inco

SimForcing: Distilling Simulation Motion Priors into Real-Domain Robot World Models

arXiv:2610.06598v1 Announce Type: cross Abstract: Action-conditioned robot world models must respond precisely to robot trajectories while preserving realistic visual dynamics, yet learning both from

SPDAlign: Interpretable Riemannian Alignment for EEG Forward Modeling Shifts

arXiv:2610.06315v1 Announce Type: new Abstract: Electroencephalography (EEG) based brain-computer interfaces enable direct brain-to-device communication for applications such as rehabilitation and com

STC-MPM: Coupled Deformation, Progressive Damage, and Cut Formation in Soft-Tissue Cutting

arXiv:2610.06198v1 Announce Type: new Abstract: Cutting is a recurring operation in robotic au tomation, from food preparation to surgical tissue resection. For highly compliant targets, blade motion

StepCAD: Mesh-to-CAD Code Generation via LLM Policy and Geometry-Guided Search

arXiv:2610.03799v1 Announce Type: new Abstract: Recovering executable CAD programs from 3D meshes is challenging due to the compositional nature of CAD construction and the interaction between discret

Strategic Multi-Agent Learning for Interpretable Action Valuation of All Players in Football

arXiv:2610.05961v1 Announce Type: new Abstract: Valuing player actions in football requires accounting for strategic interactions among 22 players, including off-ball movements and defensive positioni

Streaming Multi-Track Timeline Control for 3D Human Motion Generation

arXiv:2610.03873v1 Announce Type: new Abstract: Text-driven human motion generation has advanced substantially, yet most methods assume instructions are available before synthesis. Interactive applica

SUAVE: Unified Video-Action Models via Masked Diffusion

arXiv:2610.04009v1 Announce Type: cross Abstract: Vision-language-action models (VLAs) inherit strong semantic grounding from pretrained vision-language backbones but are typically optimized for predi

TACET: Context-Appropriate Acoustic-Social Navigation for Quadrupeds

arXiv:2610.03828v1 Announce Type: new Abstract: Quadruped robots entering hospitals, care homes, and quiet offices must be context-appropriate not only in where they move but in how loudly they move:

TacOT: Learning Contact-Rich Dexterous Manipulation from Human Demonstrations via Tactile-Guided Optimal Transport

arXiv:2610.04363v1 Announce Type: new Abstract: Learning contact-rich dexterous manipulation from human demonstrations provides a scalable source of interaction data, yet transferring such skills to r

TAME:Topology-Aware Text-Driven Motion Editing across Heterogeneous Humanoid Skeletons

arXiv:2610.04529v1 Announce Type: new Abstract: Text-driven motion editing modifies an existing motion sequence according to a text instruction while preserving the content of the source motion. Exist

Targeted Active Learning for Preference-Based Treatment Effects on Multivariate Outcomes

arXiv:2610.03824v1 Announce Type: cross Abstract: Treatment efficacy is traditionally demonstrated on the basis of a single primary outcome. However, clinical decision-making usually requires consider

Task Inference Beyond Least Squares in Behavioral Foundation Models

arXiv:2610.05350v1 Announce Type: new Abstract: Behavioral Foundation Models (BFMs) aim to solve a wide range of downstream tasks without test-time policy learning by inferring a task vector from the

Task-Sensitive Geometry of Representation Transfer for Object Detection under Image Degradation

arXiv:2610.04627v1 Announce Type: new Abstract: Object detection under image degradation can benefit from clean-image supervision, but aggregate gains do not imply that transferred representation chan

TDC: Sim-to-Real Transferable Directional Compliance for Contact-Rich Manipulation

arXiv:2602.14174v2 Announce Type: replace Abstract: Contact-rich manipulation requires robots to regulate both motion and interaction forces, yet achieving adaptive compliance remains a fundamental ch

Teaching Agents to Code Reliably

arXiv:2610.03984v1 Announce Type: cross Abstract: Autonomous coding agents solve repository issues by reading code, running commands, editing files, and submitting patches. Extra inference-time comput

Test-Time Training as Residual Memory for Robot Policies

arXiv:2610.04701v1 Announce Type: new Abstract: Memory is essential for long-horizon robotic manipulation, where successful actions may depend on past events that are no longer recoverable from the cu

The Score Is Not the Structure: Brain Alignment and Cross-Lingual Transfer

arXiv:2610.03827v1 Announce Type: cross Abstract: Researchers often support the claim that a model shares structure with the brain, or across languages, by reporting a similarity score. We ask what su

The Unexpired Plan: A Free Monitor for Accelerated Diffusion Policies

arXiv:2610.05747v1 Announce Type: new Abstract: Training-free acceleration of a diffusion policy is accepted when an internal similarity signal reports that the shortcut changed nothing. We price ever

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

Towards causal effect estimation with learned instrument representations

arXiv:2602.10370v3 Announce Type: replace-cross Abstract: Instrumental variable (IV) methods mitigate bias from unobserved confounding in observational causal inference but rely on the availability of

Transfer-Stratified On-Policy Distillation for RL-Improved Reasoning Teachers

arXiv:2610.05974v1 Announce Type: new Abstract: Reinforcement learning can substantially improve a reasoning teacher, but it is unclear which of those improvements survive when the teacher supervises

Transporting Unsecured Stacked Payloads with a Quadrupedal Robot via Multi-Objective Reinforcement Learning

arXiv:2610.05819v1 Announce Type: cross Abstract: Transporting unsecured payloads with legged robots over uneven terrain requires balancing locomotion performance and payload stability, since aggressi

TRIM-ReID: Duplication-Aware Token Reduction and Modality-Aligned Interaction for Multi-Modal Object Re-Identification

arXiv:2610.04361v1 Announce Type: new Abstract: Multi-modal object re-identification exploits complementary RGB, near-infrared (NIR), and thermal-infrared (TIR) observations to retrieve target objects

TUCO: Curating Simulation Demonstrations for Sim-to-Real Robot Policy Co-Training

arXiv:2610.05407v1 Announce Type: new Abstract: Simulation demonstrations can supplement scarce real-world data for robot policy co-training. However, the value of using data curation to actively sele

TurboPairFormer: Fast and Stable Protein Folding Model Training with an Optimized Triangle Attention Kernel

arXiv:2610.05854v1 Announce Type: new Abstract: Triangular attention is a core computation in AlphaFold3-style biomolecular models, with cubic cost in token count. Its shared pair bias adds a gradient

Universality and Convergence of Generative Flows

arXiv:2610.05490v1 Announce Type: new Abstract: Generative flows sample from an unnormalized target by training a flow to be balanced, and the training loss is the signal a practitioner watches. We as

VAMPS: Visual and Motor Policies from Sampling-Based Planning

arXiv:2610.05331v1 Announce Type: cross Abstract: Learning robot policies directly on physical systems remains difficult because data collection is costly and policy exploration can be unsafe. We intr

Variance-Aware Fine-Grained Gap-Dependent Bounds for Online Reinforcement Learning

arXiv:2610.04752v1 Announce Type: cross Abstract: We study model-free online reinforcement learning (RL) for episodic tabular Markov decision processes, focusing on both gap-dependent regret and polic

VGGT-Bridge: Beyond Sequential Pose Graphs via Coarse-Stride Skip Edges

arXiv:2610.06594v1 Announce Type: new Abstract: Feed-forward visual geometry transformers such as VGGT reconstruct dense 3D structure from images in a single forward pass, simplifying multi-view 3D re

Visual Swarm Navigation via Deep Reinforcement Learning and Evolutionary Hybrid Design

arXiv:2610.06400v1 Announce Type: new Abstract: Swarm robotics presents a robust and cost-effective paradigm for advanced automation in complex, dynamic environments, such as those encountered in sear

WASP: Weakly Aligned Spatiotemporal Pairs for Fetal Brain MRI-Ultrasound Learning

arXiv:2610.04601v1 Announce Type: new Abstract: Magnetic Resonance Imaging (MRI) is widely regarded as the optimal sensor for fetal brain analysis due to its superior soft-tissue contrast and anatomic

Watermarking: from Impossibility to Auditable Compliance

arXiv:2610.06317v1 Announce Type: cross Abstract: Article 50 (2) of the EU Artificial Intelligence Act requires providers of generative systems to make synthetic outputs machine-readable and detectabl

When to Switch: Reliable Action-Chunk Extension for Vision-Language-Action Models

arXiv:2610.05719v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models serve as unified policies for robotic manipulation, yet their expensive inference forces robots to pause between pol

Which Preferences to Train On? End-to-End Multi-Objective Alignment with an Adversarial Preference Distribution

arXiv:2610.04845v1 Announce Type: new Abstract: Aligning large language models (LLMs) with human values is important for safe, efficient, and beneficial AI deployment. However, human values are multif

A Near-Zero Monitor Readout Is Not Evidence of Behavioral Control

arXiv:2610.03458v1 Announce Type: new Abstract: Post-training with verifiable rewards can induce reward hacking, motivating the use of monitors within the training objective rather than solely for off

safetyarxiv-cs-ai

A Unified Framework for Bayesian Data Assimilation with Generative Models and Observation Interpolants

arXiv:2610.03396v1 Announce Type: new Abstract: Bayesian data assimilation combines model forecasts with noisy observations, but sampling high-dimensional, non-Gaussian posteriors remains challenging.

A Unified Framework for Empowerment and Predictive Control

arXiv:2610.03563v1 Announce Type: new Abstract: Sampling-based model predictive control (MPC) is a powerful approach to trajectory optimization, but its performance depends on an informative cost func

AdaTempo: Learning Shared Relative Tempo from Demonstrations for Faster Robot Manipulation

arXiv:2610.02706v1 Announce Type: new Abstract: Visuomotor policies trained via imitation learning often inherit the unnecessarily slow timing of teleoperated demonstrations. Yet uniform speedup is un

Architecture-Dependent Fusion Pathways in MLLMs

arXiv:2610.03289v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) achieve strong performance across vision-language tasks, yet the internal mechanisms by which visual and textua