safety

Parasitic Co-Denoising: Unlocking 3D Human Motion Generation in a Frozen Video Diffusion Model

arXiv:2610.03047v1 Announce Type: new Abstract: Despite never being supervised on explicit 3D motion, large-scale text-to-video diffusion models synthesize realistic human motion in their generated vi

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DGX agent

arXiv:2610.03667v1 Announce Type: new Abstract: Policy-gradient methods are central to modern reinforcement learning, including LLM post-training. When they struggle, the usual suspects are exploratio

safetyarxiv-cs-lg

5 Oct 2026

PoCoFL: POlicy-COmpliant Federated Learning

arXiv:2610.03650v1 Announce Type: cross Abstract: Federated Learning (FL) is a privacy-oriented learning paradigm that enables collaborative model training while keeping training data local to partici

Positive-Unlabeled Learning for Agent Safety False Alarm Auditing

arXiv:2610.02925v1 Announce Type: new Abstract: Safety monitors help safeguard language-model agents interacting with external tools and environments, but conservative monitoring can generate many fal

PowerBench: Measuring Language Model Bias in Power-shifting Requests

arXiv:2610.02303v1 Announce Type: new Abstract: Language models increasingly assist people with power-related requests, so systematic differences in whom they help could shift the distribution of powe

Powerful testimony from ex Google DeepMind researcher @Turn_Trout at NYC Hearing on AI, about how he tried to get Google to commit to AI saf…

Powerful testimony from ex Google DeepMind researcher @Turn_Trout at NYC Hearing on AI, about how he tried to get Google to commit to AI safety, and how Google, sadly including Demis Hassabis, ultimat

safetygary-marcus--x

ProAR: Learning Prospective Reasoning with Autoregressive Video Models

arXiv:2610.03664v1 Announce Type: new Abstract: Autoregressive (AR) video models excel at causal generation, but their reliance on next-chunk prediction confines them to a short-sighted, reactive para

Prospective Hindsight: Self-Calibrating Reinforcement Learning via Prediction-Reality Gaps

arXiv:2610.02740v1 Announce Type: cross Abstract: Reinforcement learning for long-horizon agents relies on purely retrospective training signals: credit is assigned only after observing environmental

PsyEvo: A Personalized Counseling Agent That Self-Evolves at Test Time

arXiv:2610.02885v1 Announce Type: new Abstract: Mental health disorders affect a substantial proportion of the global population, yet a persistent shortage of trained practitioners leaves the majority

Q&A with AI researchers Jacob Coxon, Daniel Kokotajlo, Alex Turner, and others on leaving AI labs, AGI's dangers, planned IPOs, AI safety, oversight, and more (New York Magazine)

New York Magazine: Q&A with AI researchers Jacob Coxon, Daniel Kokotajlo, Alex Turner, and others on leaving AI labs, AGI's dangers, planned IPOs, AI safety, oversight, and more — Exit interviews with

Q&A with Sam Altman on his kids, his rivalries, pronatalism, 'prepping' for the apocalypse, new products, the IPO delay, Luca Guadagnino's Artificial, and more (Vanity Fair)

Vanity Fair: Q&A with Sam Altman on his kids, his rivalries, pronatalism, “prepping” for the apocalypse, new products, the IPO delay, Luca Guadagnino's Artificial, and more — In an exclusive video int

Recoverability Has a Law: The ERR Measure for Tool-Augmented Agents

arXiv:2601.22352v2 Announce Type: replace-cross Abstract: Language model agents often appear capable of self-recovery after failing tool call executions, yet this behavior lacks a formal explanation.

Register-Routed Delayed Fusion: Rewiring Shortcut-Prone Observation Fusion in Visuomotor Imitation

arXiv:2610.02813v1 Announce Type: new Abstract: Visuomotor imitation policies combine high-dimensional visual observations with compact signals such as proprioception, and their fusion topology determ

Revealing Epistemic Uncertainty in MLLMs via Causal-Invariant Masking

arXiv:2610.02887v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) suffer from hallucinations, creating a critical need for Uncertainty Quantification (UQ) to ensure reliable d

Revisiting Visual Representation Enhancement of VLMs via Kernel Canonical Correlation Analysis

arXiv:2610.02718v1 Announce Type: cross Abstract: Vision-language models such as CLIP exhibit strong semantic generalization, but remain limited in fine-grained visual perception. A recent work named

Reward Inflation: A Healthy Stimulus for Reinforcement Learning

arXiv:2610.02545v1 Announce Type: new Abstract: Reward serves as the primary learning signal in reinforcement learning (RL). However, while reward magnitudes are typically held fixed throughout traini

Right Order, Wrong Scale: Auditing LLM Judges for Occupational AI Measurement

arXiv:2610.02492v1 Announce Type: new Abstract: LLM judges are increasingly used to assess whether AI outputs meet workplace requirements, but agreement on response rankings does not establish agreeme

RoboBridge: A Self-Evolving Embodied Agent Framework for Sim-to-Real Transfer

arXiv:2610.02717v1 Announce Type: new Abstract: A key challenge in bringing embodied intelligence into the real world is transferring capabilities from simulation to reality and enabling agents to con

ROUTEAUDIT: Interaction-Aware Identification for Budgeted Multi-Verifier Routing

arXiv:2610.02808v1 Announce Type: new Abstract: Adaptive multi-verifier systems are commonly compared through endpoint quality-cost gaps, even when the verifier catalog, availability, accounting, info

Safe Streaming Flow Planning by Aligning Sampling Dynamics with Execution Dynamics

arXiv:2610.03132v1 Announce Type: cross Abstract: Generative planners based on diffusion/flow matching can learn to synthesize long-horizon trajectories from demonstrations. However, real-world deploy

Safeguarding Mutual Correction in Source-Free Domain Adaptation via Cut Statistics

arXiv:2610.02981v1 Announce Type: new Abstract: Source-Free Domain Adaptation (SFDA) aims to adapt a source-pretrained model to an unlabeled target domain without access to the original source domain.

Sam Altman says he's 'very uncomfortable' with attributing religious force to AI, calling it 'a real safety issue', as Anthropic engages with religious leaders (Ben Berkowitz/Axios)

Ben Berkowitz / Axios: Sam Altman says he's “very uncomfortable” with attributing religious force to AI, calling it “a real safety issue”, as Anthropic engages with religious leaders — OpenAI CEO Sam

SARI: Phase-Split Sim-Real Co-Training for Contact-Rich Manipulation

arXiv:2610.02804v1 Announce Type: new Abstract: Vision-language-action (VLA) models often require costly real-world demonstrations to adapt to contact-rich manipulation tasks, particularly when genera

SCAD: Structured Credit Assignment and Distillation for Long-Horizon Agents

arXiv:2610.03372v1 Announce Type: new Abstract: Training long-horizon agents to solve complex tasks requires effective supervision over extended interaction sequences. However, sparse terminal rewards

Scalar Federated Learning for Linear Quadratic Regulator

arXiv:2604.05088v2 Announce Type: replace-cross Abstract: We propose ScalarFedLQR, a communication-efficient federated algorithm for model-free learning of a common policy in linear quadratic regulato

SceneFactory-3D: Lifting 2D Traffic Scenes into 3D Physical Counterfactuals for Scalable Physically Grounded Safety Evaluation

arXiv:2610.02874v1 Announce Type: new Abstract: Scalable driving simulators typically execute vehicle commands using prescribed behavioral or kinematic rules, overlooking the physics of tire-road inte

SecJev: Bringing Security Expertise to System One Decision Models

arXiv:2610.03073v1 Announce Type: cross Abstract: Security workflows need models that turn complex observations and explicit policies into decisions. System One models introduced by Jev return typed p

safetyarxiv-cs-cl

SimpleTouch: Can Vision-Language-Action Models Master Contact-Rich Manipulation Without Tactile Policy Pretraining?

arXiv:2610.02784v1 Announce Type: new Abstract: Tactile sensing provides essential contact information for robotic manipulation, yet incorporating it into pretrained vision-language-action (VLA) model

Single or Multiple Policies for Phase-Structured Reinforcement Learning?

arXiv:2610.03475v1 Announce Type: cross Abstract: Many reinforcement-learning (RL) problems are non-stationary yet structured and can be decomposed into phases, each with its own transition probabilit

Slow-Fast Multi-Teacher On-Policy Distillation for Capability Preservation

arXiv:2610.02324v1 Announce Type: cross Abstract: Foundation multimodal large language models are designed to support a broad spectrum of capabilities across diverse domains. Multi-teacher on-policy d

Smart Sensing for Safer Bridges: From Sensor Signals to AI-Driven Anomaly Detection

arXiv:2610.03082v1 Announce Type: new Abstract: Bridges contribute significantly to transportation connectivity and urban development. Therefore, reliable bridge monitoring is crucial for protecting p

So let me get this straight, now we have to call every piece of AI SI, even • ELIZA, 1965 which was just keyword matching and certainly not …

So let me get this straight, now we have to call every piece of AI SI, even • ELIZA, 1965 which was just keyword matching and certainly not super or intelligent • Deep Blue, which could play chess but

safetygary-marcus--x

SocialVLA: A Social Perception Gateway for Human-Reaction-Based Failure Detection and Recovery in VLA Manipulation

arXiv:2610.02360v1 Announce Type: new Abstract: Vision-language-action (VLA) policies enable diverse robotic manipulation but can fail during execution without recognizing their own errors. Human obse

Spectral Alignment in Forward-Backward Representations via Temporal Abstraction

arXiv:2603.20103v4 Announce Type: replace-cross Abstract: Forward-backward (FB) representations provide a powerful framework for learning the successor representation (SR) in continuous spaces by enfo

Spend Teacher Tokens Where They Matter: Success-Referenced On-Policy Distillation

arXiv:2610.02678v1 Announce Type: new Abstract: On-policy distillation (OPD) combines student-generated rollouts with dense token-level supervision from a teacher, but providing such supervision for e

State-Space Unlearning for Non-Stationary Bias in Land Surface Forecasting

arXiv:2610.02248v1 Announce Type: new Abstract: Operational land surface forecasting systems built on Mamba-family Structured State Space Models absorb non-stationary confounding events (unrecorded ir

Structured Composition of Verifiable Atomic Insights for Table-to-Report Generation

arXiv:2610.03525v1 Announce Type: new Abstract: Table-to-report generation refers to the task of automatically generating article-level analyt- ical reports from relational tables and is an essential

safetyarxiv-cs-cl

Student-Guided Teacher Distillation for Efficient LLM Task Routing: Positioning Against Jev-Style System-1 Classifiers

arXiv:2610.02516v1 Announce Type: cross Abstract: Zero-shot classifiers are useful for routing user requests to specialized LLM tasks, but scoring every request against a large candidate set is expens

TACD: Distilling Efficient Text-to-Motion Models via Terminal Amplification Control

arXiv:2610.02867v1 Announce Type: new Abstract: Recent text-to-motion models have improved motion quality and instruction following, yet many-step denoising and large model components make deployment

TerrainForge: Physics-Grounded road geometry Editing for Counterfactual Autonomous Driving

arXiv:2610.02825v1 Announce Type: new Abstract: Road geometry (e.g., crests, sags, and speed humps) and surface conditions (e.g., wet or icy pavement) affect how vehicles move, what drivers and onboar

Test-time Multi-agent Coordination by Decomposed Value Gradient Flow

arXiv:2610.02554v1 Announce Type: new Abstract: Offline multi-agent reinforcement learning (MARL) faces a persistent trade-off. Expressive generative policies can represent multi-modal coordination in

The Shape of Speech: A Geometric Measure of Coarticulation for Speech-Driven 3D Facial Animation

arXiv:2610.03436v1 Announce Type: cross Abstract: Speech-driven 3D facial animation can reproduce recognizable mouth poses. However, it can simplify the motion between them, and that motion carries co

THPL: A Vision-to-Language Decision Support Framework for Rainbow Trout Feeding Management in RAS

arXiv:2610.02378v1 Announce Type: new Abstract: In Recirculating Aquaculture Systems (RAS), precision feeding is critical for minimizing costs and improving fish welfare. However, existing methods lac

To comply with the EU AI Act, OpenAI plans to add text watermarking for ChatGPT and Codex users in the EU and an opt-in setting for API customers globally (OpenAI)

OpenAI: To comply with the EU AI Act, OpenAI plans to add text watermarking for ChatGPT and Codex users in the EU and an opt-in setting for API customers globally — - Starting today, API customers glo

Tropical Reinforcement Learning

arXiv:2610.02478v1 Announce Type: new Abstract: Reinforcement learning for large language models typically maximizes expected return, adding up the probabilities of all successful trajectories. Howeve

ULTRADISCOVERY: Abductive Exploration in an Interconnected, Epistemically Open Universe

arXiv:2610.03092v1 Announce Type: cross Abstract: Scientific discovery often begins when scattered clues call for a new way of describing the world. Such abductive exploration can require constructing

Understanding Enrichment in Reinforcement Learning

arXiv:2610.02846v1 Announce Type: new Abstract: When rewards are sparse, reinforcement learning with verifiable rewards (RLVR) often uses hints or intermediate guidance to generate more successful rol

UniIntervene++: An Adaptive Intervention Agent for Efficient Real-World Reinforcement Learning

arXiv:2610.03620v1 Announce Type: new Abstract: Online reinforcement learning (RL) enables robot policies to improve through physical interaction, but the assistance they require changes as their comp