Search: “safety”

TMT: Runtime Backdoor Detection for Vision-Language-Action Policies on Unseen Tasks

arXiv:2610.09462v1 Announce Type: new Abstract: Backdoored vision-language-action (VLA) policies can preserve benign task performance while producing malicious actions when a trigger appears. Detectin

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TouchScale: 500 Hours of Human Vision and Touch for Visual-Tactile Learning

DGX agent

arXiv:2610.10288v1 Announce Type: new Abstract: Large-scale egocentric human interaction data is becoming an important source of physical supervision for embodied learning, yet video alone leaves the

safetyarxiv-cs-cv

8 Oct 2026

Transition Path Sampling Using Koopman Operators and Exit-Time Optimal Control

arXiv:2610.10054v1 Announce Type: cross Abstract: Sampling transitions between metastable states is a central problem in dynamical systems theory and molecular dynamics in particular. A key challenge

Two-Level Softmax Sampling Done Right: Correcting Bias from Size Imbalance and Dispersion

arXiv:2610.10483v1 Announce Type: new Abstract: Sampling from a softmax distribution is a fundamental operation in machine learning, but its linear complexity in the number of items makes exact sampli

Unpaired Canonical Correlation Analysis

arXiv:2610.09530v1 Announce Type: cross Abstract: Canonical Correlation Analysis (CCA) is a fundamental method for multiview shared space learning. However, its strict reliance on paired data poses a

Using Small Language Models to Reverse-Engineer Machine Learning Pipelines Structures

arXiv:2610.10261v1 Announce Type: cross Abstract: Context: Once defined a taxonomy of stages structuring Machine Learning (ML) pipelines (e.g. Data Preprocessing, Modeling...), extracting these stages

Validity Without Ground Truth: What Stated-Preference Economics Offers the Evaluation of Language Models

arXiv:2610.10506v1 Announce Type: cross Abstract: Many of the questions now put to large language models have no correct answer to score against: what a policy is worth, which option a user should cho

Workhorse: Learning Robust Whole-Body Humanoid Loco-Manipulation from Human Data

arXiv:2610.09117v1 Announce Type: cross Abstract: Humanoid robots still struggle to plan contact-rich whole-body manipulation from egocentric RGB and proprioception. Workhorse learns such manipulation

4D-HOF: Hand-Object Flow Matching for Feed-Forward 4D Interaction Reconstruction

arXiv:2610.08782v1 Announce Type: cross Abstract: Existing methods for 4D hand-object reconstruction often rely on costly per-sequence optimization, while generative approaches typically synthesize in

A Footprint-Aware, High-Resolution Approach for Carbon Flux Prediction Across Diverse Ecosystems

arXiv:2512.01917v2 Announce Type: replace Abstract: Eddy-covariance (EC) flux towers provide in situ measurements of CO_2 flux and serve as the ground-truth data for predictive `upscaling' models deri

A Query Is Not a Commitment: Learning to Correct Expert Answers in Online Deferral

arXiv:2610.07084v1 Announce Type: cross Abstract: An inaccurate expert can still provide useful information after correction. We study online learning to defer in which the learner chooses an expert a

A Systematic Analysis of the Predictive Power of LM Surprisal in Reading Chinese

arXiv:2610.04898v2 Announce Type: replace-cross Abstract: This study analyzes the predictive power of LM-derived, token-level surprisal on Mandarin Chinese reading times. We first propose the Shortest

A theory of platonic representations in language models

arXiv:2610.07168v1 Announce Type: cross Abstract: Representations of translated sentences are similar in the inner layers of multilingual language models -- an observation connected to the platonic re

AccentCL: Robust Accent Classification with Incremental Expansion

arXiv:2610.07426v1 Announce Type: new Abstract: Accent classifiers are typically trained with a fixed label inventory and cannot accommodate new accent categories as new data becomes available. Moreov

ACG-WAM: World-Action Modeling via Action-Conditioned Geometric Latent Prediction

arXiv:2610.06965v1 Announce Type: new Abstract: World action models jointly learn visual predictionand robot actions, providing a way to use observations ofscene evolution for policy learning. Their v

Active Feature Acquisition for Cost-Efficient Temporal Prediction with Reduced Participant Burden

arXiv:2610.07452v1 Announce Type: cross Abstract: Accurate forecasting of pathological outcomes is a central problem in psychology. To do so, psychologists often collect intensive longitudinal data. H

Adapting Vision-Language-Action Models to Unknown Visual Disruptions During Execution

arXiv:2610.07946v1 Announce Type: cross Abstract: Visual disruptions can arise while a robot is executing a task, leaving a vision-language-action (VLA) policy to respond without knowing the disruptio

Adaptive Mean Estimation by In-Context Learning: A Gradient-Flow Analysis

arXiv:2610.07804v1 Announce Type: new Abstract: Prior Fitted Networks (PFNs) such as TabPFN now rival established statistical procedures across prediction and estimation tasks. A natural explanation i

AFA-BANDIT: Provably Near-Optimal Online Multi-Feature Classification Under Budget Constraints

arXiv:2610.07615v1 Announce Type: new Abstract: Active Feature Acquisition (AFA) is a classification problem in which an agent decides which costly features to acquire before predicting each sample's

Aggregating User Preferences while Ensuring Equity, Diversity, and Inclusion using Graph Summarization

arXiv:2610.07128v1 Announce Type: cross Abstract: Aggregating the preferences of diverse user groups into a collective outcome raises fundamental challenges of equity, diversity, and inclusion (EDI):

ARIA: Audio-Driven Melody-Tone Relation Modeling for Cantonese Lyric Authoring

arXiv:2610.07902v1 Announce Type: new Abstract: Cantonese lyric writing requires close alignment between lexical tones and melodic pitch. Existing melody-guided lyric generation methods typically rely

Attacca: Goal-Directed Control under State Continuity for Long-Horizon Embodied Agents

arXiv:2610.07785v1 Announce Type: new Abstract: A central capability of embodied agents is to accomplish complex objectives through sequences of interdependent tasks. Yet existing visual goal-conditio

BAT: Balancing Agility and Stability via Online Policy Switching for Long-Horizon Whole-Body Humanoid Control

arXiv:2604.01064v2 Announce Type: replace Abstract: Despite advances in reinforcement and imitation learning, achieving both precise control and dynamic whole-body behaviors in long-horizon tasks rema

Beyond Perturbation Magnitude: Direction-Dependent Responses in Multimodal Geometric Representations

arXiv:2610.08533v1 Announce Type: new Abstract: Geometric alignment scores based on Gram determinants provide a compact way to model higher-order consistency among modalities, yet how such scores resp

Beyond Retargeting: Low-Latency and Robust Humanoid Whole-Body Teleoperation with Learned Atomic Motion Primitives

arXiv:2610.07891v1 Announce Type: new Abstract: Humanoid whole-body teleoperation translates human motion into stable robot behavior in real time. Existing systems typically rely on online motion reta

Beyond Scalar IoU: Structured Verification from Rollout Groups for Video Temporal Grounding

arXiv:2610.07601v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) provides a natural framework for adapting pretrained models to video temporal grounding, where gen

Can Semantic Geometry Teach an AI Judgement?

arXiv:2610.07249v1 Announce Type: new Abstract: How can an AI agent determine what rules to follow? One rule permits an action. Another imposes a condition, exception, or conflicting obligation. Deter

Cite What You Explore: Budget-Aware LLM Reasoning over Medical KGs with Verifiable Evidence

arXiv:2610.07739v1 Announce Type: new Abstract: Post-discharge risk prediction from electronic health records (EHRs) is difficult because many dependencies that link discharge-time observations to dow

Co-Evolving Paths and Flows via Path-Flow Alignment

arXiv:2610.08717v1 Announce Type: new Abstract: We study path-flow alignment as a unified training objective for flow matching. Instead of fixing the interpolation path and learning only the velocity

Commit While Futures Agree: Consequence-Aware Adaptive Action Chunking for Robot Manipulation

arXiv:2610.07949v1 Announce Type: new Abstract: Action-chunking policies predict multi-step control sequences, but a fundamental question remains: how much of a predicted action chunk should be commit

Constant-Curvature Sliced Gromov-Wasserstein for Heterogeneous Cross-Curvature Alignment

arXiv:2610.07218v1 Announce Type: new Abstract: Recent advances in representation learning have highlighted the utility of constant-curvature models, such as hyperbolic and spherical spaces, for model

Cooperating with Future Collaborators: Multi-Agent RL under Staggered Participation

arXiv:2610.07578v1 Announce Type: new Abstract: In cooperative Multi-Agent Reinforcement Learning (MARL), agents are often trained under concurrent participation, while in many tasks some agents act e

CoRE: Learning Collaboration-Role Experts for Decentralized Collaborative Manipulation with One Policy

arXiv:2610.07752v1 Announce Type: new Abstract: Collaborative manipulation requires robots to perform complementary actions as interactions unfold. We study single-policy decentralized collaboration:

Cross-Lingual Activation Steering for Multilingual Language Models

arXiv:2601.16390v2 Announce Type: replace-cross Abstract: Large language models exhibit strong multilingual capabilities, yet significant performance gaps persist between dominant and non-dominant lan

CtrlCache: Accelerating Interactive Video World Models with Control-Aware Caching

arXiv:2610.08777v1 Announce Type: new Abstract: Interactive video world models need to generate each video chunk efficiently while responding faithfully to user controls. Many systems use chunk-wise a

CueRator: Agentic Search for Symbolic Rules to Adapt Frozen Multimodal Encoders

arXiv:2610.07868v1 Announce Type: new Abstract: Large language model agents have been used to search over symbolic structures such as programs and equations. We propose CueRator, an agentic framework

Cylindrical Geodesic Flow Matching for Quasiperiodic Physiological Signal Transformation

arXiv:2610.08510v1 Announce Type: new Abstract: Paired translation between quasiperiodic physiological waveforms (i.e., recovering a target oscillatory signal from the source) is central to the interp

Data-Driven Personas for Survey Simulation: Insights into Simulation Alignment Across Data-Access Regimes

arXiv:2610.05828v2 Announce Type: replace Abstract: Large language models (LLMs) offer new opportunities for public opinion research by enabling early prediction of survey responses, potentially reduc

Data Fusion for Errors-in-Variables

arXiv:2610.07048v1 Announce Type: cross Abstract: We study errors-in-variables problems in which a target study contains only a single error-prone surrogate of an unobserved exposure, while an externa

DeepAJM: Deep Association Joint Model for Irregularly Sampled data

arXiv:2610.07388v1 Announce Type: cross Abstract: Joint Models simultaneously model longitudinal and survival outcomes, leveraging patterns in patients' longitudinal trajectory to improve the predicti

Deformable CT-US Registration via Anatomy-Aware Implicit Neural Representations

arXiv:2610.08419v1 Announce Type: new Abstract: Slice-to-volume registration between ultrasound (US) and preoperative computed tomography (CT) imaging would enhance many minimally invasive interventio

DepthWorld: 3D World Model for Robot Manipulation

arXiv:2610.08780v1 Announce Type: cross Abstract: World models offer a data-driven alternative to traditional simulators for robotics, with applications spanning policy evaluation, improvement, and pl

Dexterous Control of an 11-DOF Redundant Robot for CT-Guided Needle Insertion With Task-Oriented Weighted Policies

arXiv:2503.14753v3 Announce Type: replace Abstract: Computed tomography (CT)-guided needle biopsies are critical for diagnosing a range of conditions, including lung cancer, but present challenges suc

Direct Regret Optimization in Bayesian Optimization

arXiv:2507.06529v2 Announce Type: replace Abstract: Bayesian optimization (BO) is a powerful paradigm for optimizing expensive black-box functions. Traditional BO methods typically rely on separate ha

DirectSpeech2LLM: A Simple End-to-End Framework to Mitigate Prompt Overfitting in Speech-LLMs

arXiv:2610.08085v1 Announce Type: new Abstract: Speech-LLMs often exhibit prompt overfitting, where models solely trained on automatic speech recognition (ASR) instruction fail to generalize to new in

EmbodiedSmith: Scaling Embodied Data through Recursive Self-Improvement Flywheel in Simulation

arXiv:2610.07969v1 Announce Type: new Abstract: Scaling robotic foundation models requires diverse training data and reliable evaluation environments. Simulation offers a scalable solution, yet existi

Energy-Aware Path Following: Comparative Analysis of Reinforcement Learning and NMPC for Electric Vehicles

arXiv:2610.08112v1 Announce Type: cross Abstract: Path-following control strategies typically follow the bi-objective optimization dilemma: minimizing deviations from a reference path while maintainin

ESP: Energy-Score Policy for One-Step Multimodal Action Generation

arXiv:2610.07696v1 Announce Type: new Abstract: Generative action models based on diffusion and flow matching have been increasingly adopted in vision-language-action (VLA) policies for their ability