Search: “safety”

CMP-IRRT*: A Perception-Assisted Height-Adaptive Planner for Quadruped Robots

arXiv:2610.10470v1 Announce Type: new Abstract: Quadruped robots can traverse low obstacles, but many 2D planning pipelines still model obstacles as binary occupied regions and rely on sampling-based

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Co-Evolving Robot Orchestrators and Policies through Deployment

DGX agent

arXiv:2610.09228v1 Announce Type: new Abstract: Vision-language-action (VLA) policies trained on large datasets are capable within their training domains, yet they still fail to generalize to the vari

safetyarxiv-cs-ro

8 Oct 2026

Co{}^{2}Skill: Whole-Body Control via Skill Composition for Long-Horizon Human-Environment Interaction

arXiv:2610.09291v1 Announce Type: new Abstract: Achieving human-level dexterity in complex, unstructured environments requires the seamless integration of whole-body scene interaction and dexterous ob

Constitution-Guided Watermarking

arXiv:2610.09552v1 Announce Type: cross Abstract: Watermarking enables language model providers to identify text generated by their models. However, its desired properties can conflict (ie~stronger wa

Constrained-Action AI Remediation for SIEM/XDR via a NeMo-Guardrails Proxy

arXiv:2610.09906v1 Announce Type: cross Abstract: Security Operations Centers (SOCs) for information technology and operational technology share one incident-response problem: a flood of correlated al

Contact-Aware Imitation Learning Through Contact Factorization

arXiv:2610.09533v1 Announce Type: new Abstract: Generalizable contact-rich manipulation requires robots to preserve intended task behavior while adapting its physical realization to changing contact c

Convex-Concave Reinforcement Learning

arXiv:2610.09108v1 Announce Type: new Abstract: Policy learning drives many of the most consequential and heavily-invested applications of reinforcement learning today. Yet the core optimization probl

Covariate-dependent Joint Modeling of Multivariate Ordinal Preferences and Its Connections with Comparison Models

arXiv:2610.09070v1 Announce Type: cross Abstract: Multivariate ordinal data along with covariates are commonly collected in problems ranging from alignment of language models with human preferences, a

Decoupling Exploration from Optimization in RLVR

arXiv:2610.10536v1 Announce Type: cross Abstract: Modern language models undergo reinforcement learning with verifiable rewards (RLVR) on top of already-trained checkpoints. A key promise of RLVR is t

DeltaRepresentation: Geometry Supervised Representation Learning of Phenotypes via Counterfactual Reasoning for Medical VLMs

arXiv:2610.10286v1 Announce Type: new Abstract: Medical vision-language models (VLMs) have shown increasing potential for radiological image interpretation. Medical VLMs encode radiological images int

Differential Refresh Policies for Models Trained on Lagging Data Snapshots: From a Single-Age Equivalence Limit to an Optimal Per-Segment Allocation

arXiv:2610.09519v1 Announce Type: new Abstract: Production machine-learning models are derived artifacts of time-bounded training snapshots: a deployed model is a materialized view over a training cut

Distilling Graph Geometry: Knowledge Gap from GNNs to MLPs

arXiv:2610.10520v1 Announce Type: new Abstract: GNN-to-MLP distillation aims to retain the predictive accuracy of a message-passing teacher while deploying a graph-free MLP at inference. Existing meth

DiTS: Multimodal Diffusion Transformers Are Time Series Forecasters

arXiv:2602.06597v2 Announce Type: replace Abstract: While generative modeling facilitates probabilistic time series forecasting, incorporating heterogeneous exogenous information remains challenging.

Do Better Visual Representations Always Lead to Better End-to-End Autonomous Driving?

arXiv:2610.09695v1 Announce Type: cross Abstract: Visual foundation models (VFMs) are increasingly integrated into end-to-end autonomous driving for their powerful representations, yet it remains uncl

Do Generative Priors Align with Human Naturalness Perception?

arXiv:2610.09928v1 Announce Type: new Abstract: Visual generative models are trained to capture the probability distributions of natural images, yet whether their native priors reflect the regularitie

Efficient Best-of-N policy evaluation for inference-time alignment

arXiv:2610.09250v1 Announce Type: new Abstract: Best-of-N (BoN) is a common inference-time alignment method that selects the highest-scoring response among N samples from a reference model. Evaluating

Energy-Efficient Gait Adaptation via Hierarchical Reinforcement Learning for Quadrupedal Locomotion Across Diverse Terrains

arXiv:2610.10297v1 Announce Type: cross Abstract: While energy efficiency is a critical objective for legged-robot locomotion control, achieving low energy consumption while maintaining robust perform

Factorized Tactile Representation and Control for Sim-to-Real Manipulation

arXiv:2610.10510v1 Announce Type: new Abstract: Tactile sim-to-real learning must bridge simulated contact and device-specific sensor responses while preserving information needed for control. We prop

FedSSMCoOp: SSM Encoders for light-weight Federated Prompt Learning for Few-shot Classification

arXiv:2610.09907v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown strong performance across a wide range of downstream vision tasks, thanks to the complementary information cont

FlashNeRD: Performance-First Contact-Rich Neural Robot Dynamics

arXiv:2610.09130v1 Announce Type: new Abstract: Compared with analytical physics, learned dynamics models promise robot simulation that is faster, inherently differentiable, and easily adaptable to re

FoldBack: Self-Correcting Masked Generative Policy for Long-Horizon Garment Folding

arXiv:2610.10462v1 Announce Type: new Abstract: We present FoldBack, a self-correcting masked generative policy for long-horizon garment folding. Existing long-trajectory policies may continue after a

From Digital Human Interactions to Physics-Based Humanoid Skills: Physics-Grounded Post-Training of Interaction Generators

arXiv:2610.10322v1 Announce Type: new Abstract: Recent methods have made promising progress in generating interactions between two humanoids, largely relying on physics-based tracking policies to conv

From Pareto to Preference: Personalized Test-Time Scaling via Amortized Agentic Policy Discovery

arXiv:2610.09684v1 Announce Type: new Abstract: Test-time scaling (TTS) improves the reasoning capabilities of large language models by allocating additional inference computation. Existing approaches

From Wearable Interfaces to Dexterous Policies: Contact Shifts and Tactile Representations

arXiv:2610.08870v1 Announce Type: new Abstract: Unlike conventional teleoperation, wearable interfaces allow operators to collect dexterous demonstrations through their own hand motions while directly

Gauss-Newton Accuracy and Indefinite Hessians: Uniform Coexistence in Low-Cost Sets

arXiv:2610.09675v1 Announce Type: new Abstract: We study the accuracy of Gauss-Newton curvature in ridge-regularized nonlinear least squares. Under local regularity and persistence of level-set curvat

Geometry-Supervised Visual Representation Learning for Multi-Phenotype Lesion Interpretation in Medical VLMs

arXiv:2610.10238v1 Announce Type: new Abstract: Medical vision-language models (VLMs) have shown increasing potential for clinical image interpretation. However, these models still struggle to interpr

Global Average Precision for Representation Learning

arXiv:2610.09863v1 Announce Type: new Abstract: Standard information retrieval metrics, such as mean Average Precision (mAP), assess performance one query at a time, based on how the similarities betw

HULK: Learning Whole-Body Forceful Loco-Manipulation for Humanoids

arXiv:2610.08970v1 Announce Type: cross Abstract: Humanoid loco-manipulation of large, heavy objects demands forceful interaction across the entire body. However, such payloads shift a humanoid's cent

HuMBLE: Human Motion-Driven Behavior Learning for Embodied Locomotion

arXiv:2610.10489v1 Announce Type: new Abstract: Despite recent advances in humanoid locomotion, controllers optimized for command tracking and robustness tend to produce mechanical gaits, whereas cont

Immiscible Diffusion Policy: Preserving Multimodal Robot Actions through Label-Free Noise Assignment

arXiv:2610.09369v1 Announce Type: cross Abstract: When diffusion policies were first introduced, they were expected to recover multi-modal action distributions. However, we find this expectation does

InterView-C: A Synchronized Multimodal Corpus of VR Avatar-Mediated Survey Interviews

arXiv:2610.10145v1 Announce Type: new Abstract: We present InterView-C, a German multimodal corpus of 27 survey interviews conducted entirely in virtual reality, with both interlocutors represented by

Juno: Taming Predictive Latents for Vision-Language-Action Models

arXiv:2610.09940v1 Announce Type: cross Abstract: Joint-embedding predictive architectures (JEPAs) predict masked or future observations in representation space, offering a natural source of predictiv

Kernel Autoresearch for Open-Ended Model Discovery

arXiv:2610.10394v1 Announce Type: new Abstract: Kernels encode the inductive bias of a wide range of machine learning models, yet automated kernel design faces a fundamental dilemma. A fixed grammar o

LACE-CRAFT: Robot Co-Design with Actor Inheritance and Blackboard Collaboration

arXiv:2610.09283v1 Announce Type: new Abstract: Robot co-design couples morphology search with policy learning, yet training every new design from scratch discards acquired control experience. We pres

LASER: Latent Space Adjoint Matching for Support-Constrained Entropy-Regularized Offline RL

arXiv:2610.08989v1 Announce Type: new Abstract: While offline reinforcement learning (RL) enables policy optimization from static datasets without costly online interaction, it remains bottlenecked by

Learning in the Recurrent State: Gradient Descent with Linear Recurrent Networks

arXiv:2410.11687v4 Announce Type: replace Abstract: In-context learning lets a sequence model adapt to a new task from examples in its input. A prominent line of work shows how self-attention can be c

Many Ways to Succeed: Diversity-Driven RL Fine-Tuning for VLA Generalization

arXiv:2610.09943v1 Announce Type: cross Abstract: Reinforcement learning (RL) fine-tuning improves vision-language-action (VLA) policies through closed-loop experience, yet generalization beyond the f

Marrying Pricing and Advertising with LLMs

arXiv:2610.09985v1 Announce Type: cross Abstract: We study a sequential pricing problem in which a seller jointly posts a price and an advertisement generated by a large language model (LLM). The sell

MCFR: A Mask-Guided Coarse-to-Fine Regression Framework for Robust Multi-Variant Board-to-Board Connector Assembly

arXiv:2610.09327v1 Announce Type: new Abstract: Automated insertion of board-to-board (BTB) connectors in 3C manufacturing requires both high visual accuracy and strong deployment robustness. This pro

MimicX: Policy-in-the-Loop Supervision Refinement for Video-Driven Humanoid Motion Tracking

arXiv:2610.09055v1 Announce Type: new Abstract: Human videos provide rich motion targets for humanoid learning, yet visually plausible references can still produce persistent failures under physics-ba

MIRROR: From Imitation to Internalization in LLM Personalization

arXiv:2610.09795v1 Announce Type: new Abstract: The demand for personalized LLMs is shifting from style imitation toward content quality. We investigate whether self-distillation can bridge this gap i

Mitigating Accent-Language Confusion in Self-Supervised Speech Representations for Language Identification

arXiv:2610.09486v1 Announce Type: cross Abstract: Spoken language identification (LID) aims to recognize the target language regardless of accent. In practice, however, LID models fine-tuned from self

MOTIP2: Spatial Priors for End-to-End Multi-Object Tracking

arXiv:2610.10391v1 Announce Type: new Abstract: End-to-end multi-object trackers have narrowed the gap with classical tracking-by-detection on association-difficult benchmarks. Yet they still make spa

Multi-Objective Aligned Small Language Model Framework for SUD Patient Dialogue Generation

arXiv:2610.09209v1 Announce Type: new Abstract: Substance Use Disorder (SUD) counseling requires patient responses that reflect underlying cognitive states such as beliefs, coping strategies, and read

MUNITE: Unified Multimodal Latent Inference for Any-to-Any Multimodal Generation

arXiv:2610.09866v1 Announce Type: new Abstract: We introduce MUNITE, a latent-variable framework for flexible any-to-any multimodal generation that treats encoding and latent generation as the same in

On KL-Regularized Policy Optimization

arXiv:2610.08963v1 Announce Type: cross Abstract: Asynchronous reinforcement learning (RL) for large language model (LLM) agents trains one policy on trajectories generated by another: rollouts come f

On-Policy Distillation Teaches New Skills but Not New Knowledge

arXiv:2610.09639v1 Announce Type: new Abstract: On-policy distillation (OPD) strengthens language-model reasoning, yet whether students acquire new factual knowledge or compositional skill for multi-s

One-Slide Calibration of Pathology Foundation Models

arXiv:2610.08944v1 Announce Type: new Abstract: Scanner variation changes how pathology foundation models represent the same tissue. We introduce SlideRuler, which uses regions within a slide as inter