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

Toward Evidence-Driven Human-Agent-Robot Teaming for Earth-Independent Anomaly Triage

arXiv:2610.08933v1 Announce Type: new Abstract: Deep-space crews cannot rely on real-time ground support for urgent off-nominal events. Initial alerts may underdetermine cause, while discriminating ev

🧬 Training and evaluating AI scientists on drug target discovery is hard. We introduce DrugTargetWorld: Synthetic Biomedical Worlds for Tra…

🧬 Training and evaluating AI scientists on drug target discovery is hard. We introduce DrugTargetWorld: Synthetic Biomedical Worlds for Training and Benchmarking AI Scientists The environment turns en

safetygary-marcus--x

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

Understanding and Mitigating Token-Pruning-Induced Vulnerabilities in VLMs

arXiv:2610.09703v1 Announce Type: cross Abstract: Token-Pruning accelerates Vision-Language Models by removing redundant visual tokens, yet its safety implications remain underexplored. In this work,

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

We have a choice in front of us. In my latest op-ed for Transformer, I invite employees of frontier AI companies to ask themselves if their …

We have a choice in front of us. In my latest op-ed for Transformer, I invite employees of frontier AI companies to ask themselves if their work is truly leading us toward a safer future. Reflecting o

safetyyoshua-bengio--x

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

Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond)

arXiv:2510.22954v2 Announce Type: replace Abstract: Language models (LMs) often struggle to generate diverse, human-like creative content, raising concerns about the long-term homogenization of human

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

Auditable Claims about AI Agents

arXiv:2610.07459v1 Announce Type: new Abstract: Organizations make claims about their AI agents: a person approves every external email, every action is logged, an evaluation shows the agent is safe t

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

Behavioral Safety Assessment towards Large-scale Deployment of Autonomous Vehicles, Part I: Methodology

arXiv:2610.08450v1 Announce Type: new Abstract: Autonomous vehicles (AVs) have significantly advanced in real-world deployment in recent years, yet safety continues to be a critical barrier to widespr

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 Refusal Patterns: Safe-Role Internalization for Robust and Generalizable LLM Safety Alignment

arXiv:2610.07023v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable capabilities but remain vulnerable to jailbreak attacks that elicit harmful or unsafe outputs. Exi

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

Beyond Waypoint Regression: Query-Based Cost Learning over Reachable Ego Futures for End-to-End Driving

arXiv:2610.08123v1 Announce Type: cross Abstract: End-to-end planners based on waypoint regression achieve strong open-loop accuracy, but they primarily learn to mimic expert geometry and remain diffi

Calibration Is Not Control: Intervention Value for LLM-Agent Oversight

arXiv:2606.21399v2 Announce Type: replace Abstract: Runtime oversight often intervenes when an LLM agent's calibrated failure score crosses a threshold. Yet states with the same failure risk can diffe

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

ChatGPT for Teens is an ‘unacceptable risk,’ says Common Sense Media

Common Sense Media, a nonprofit that offers reviews of apps, services, and entertainment with a focus on youth safety, today said that OpenAI's ChatGPT for Teens is an 'unacceptable risk.' ChatGPT for

safetythe-verge-ai

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

Context-Conditioned Hamilton-Jacobi Reachability for Adaptive Safety Filtering

arXiv:2610.08115v1 Announce Type: cross Abstract: Hamilton-Jacobi reachability constructs safety certificates for specified dynamics and safety constraints, tying each certificate to the deployment co

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