Search: “safety”

Vision-Language Models for Egocentric Video: From Hand-Object Interaction to Embodied AI

arXiv:2608.18671v1 Announce Type: new Abstract: Egocentric video captures activities from the wearer's perspective, providing a direct view of human attention, hand--object interaction, and goal-direc

20 Aug 2026

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Weak-to-Strong Generalization via Bregman Bias-Variance Decomposition

DGX agent

arXiv:2505.24313v3 Announce Type: replace Abstract: Weak-to-strong generalization (W2SG) is the phenomenon in which a powerful student model, trained on labels produced by a weaker teacher, ultimately

safetyarxiv-cs-lg

20 Aug 2026

Welcome to the AI crisis in math

Today on Decoder, I’m talking with Robert Hart, The Verge’s London-based AI reporter, about what AI is doing to the field of mathematics and the existential crisis many lead mathematicians are having

safetythe-verge-ai

20 Aug 2026

we're launching new Fable safeguards for enterprises that work on your infrastructure so you have control over where your data lives & who h…

we're launching new Fable safeguards for enterprises that work on your infrastructure so you have control over where your data lives & who has access to it we've been developing it alongside ~100 comp

safetythariq--x

20 Aug 2026

A Diffusion-Refined Planner with Reinforcement Learning Priors for Confined-Space Parking

arXiv:2510.14000v2 Announce Type: replace Abstract: The growing demand for parking has increased the need for automated parking planning methods that can operate reliably in confined spaces. In restri

Action-Effect Memory Pretraining for Robot Manipulation

arXiv:2606.12499v2 Announce Type: replace Abstract: We present AEM, an Action-Effect Memory pretraining framework for robot manipulation that learns compact temporal representations from vision-action

Adaptive Policy Portfolios for Robust Markov Decision Processes

arXiv:2608.17929v1 Announce Type: new Abstract: Robust Markov decision processes optimize one policy against a set of plausible transition functions. This can be conservative when the unknown dynamics

Advancing Health Equity through Multi-Level Fairness in Health Informatics

arXiv:2608.16902v1 Announce Type: cross Abstract: The increasing integration of machine learning in healthcare has highlighted critical challenges related to fairness, transparency, and health equity.

Adversarial Data Modeling in Epidemiology

arXiv:2602.20134v2 Announce Type: replace-cross Abstract: Epidemiological models increasingly rely on crowdsourced, self-reported behavioral data such as vaccination status, mask usage, and social dis

Against Political Polarization: A Unified Framework for Tracing Evolving Political Ideologies on Social Media

arXiv:2608.17987v1 Announce Type: cross Abstract: The rapid growth of social media has greatly influenced political discourse, highlighting the need to understand individual political ideologies and t

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks

arXiv:2509.06777v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) suffer from oversquashing, where structural bottlenecks limit message propagation between distant nodes, hindering task

Beyond BFI: The CSI for Enhanced Reliability and Validity in Evaluating LLM Personality Traits

arXiv:2503.20182v2 Announce Type: replace-cross Abstract: As large language models (LLMs) increasingly function as human-like assistants exhibiting human-like personality traits, understanding their b

Bootstrap Dynamic-Aware 3D Visual Representation for Scalable Robot Learning

arXiv:2512.00074v4 Announce Type: replace-cross Abstract: Despite strong results on recognition and segmentation, current 3D visual pre-training methods often underperform on robotic manipulation. We

Counterpoint: “If alignment issues are becoming big enough that OpenAI is willing to commit 20% of research inference compute to chain-of-th…

Counterpoint: “If alignment issues are becoming big enough that OpenAI is willing to commit 20% of research inference compute to chain-of-thought monitoring [suggesting] that suggests that alignment i

safetygary-marcus--x

Criminal AI tool Kriminal is mostly just Grok with a jailbreak, ThreatDown finds

ThreatDown, the business security arm of Malwarebytes Inc., said in new research published today that Kriminal, one of the newest and most popular tools in the criminal artificial intelligence market,

safetysiliconangle

Cross-Model Memory Transfer via Target-Side Reader Adaptation

arXiv:2608.17050v1 Announce Type: cross Abstract: Methods for improving knowledge use in large language models typically fall into two regimes. Non-parametric retrieval offers flexible access to exter

Decomposition Attacks Across Unlinkable Identities: Limits of Stateful Defenses for LLM Services

arXiv:2608.17445v1 Announce Type: cross Abstract: Most large language model services use stateless defenses, which judge only the current request, to refuse harmful tasks. Decomposition attacks exploi

Denoised Variance-Based Pruning with Optimal Brain Bias Compensation

arXiv:2608.17657v1 Announce Type: new Abstract: Vision Transformers (ViTs) achieve state-of-the-art performance but carry massive computational overhead that restricts edge deployment. Although struct

Depth Enables Local Entropy: Quadratic Depth Dependence in Deep Variation-Norm ReLU Regression

arXiv:2608.17434v1 Announce Type: new Abstract: We study Gaussian regression over the explicit vector-valued Parhi--Nowak deep-RBV^2 architecture with depth L, width w, layer-sum variation budget A, a

DynaForcing: Overcoming Dynamic Collapse in Self-Forcing Distillation for Streaming Avatar Generation

arXiv:2608.17707v1 Announce Type: new Abstract: Audio-driven avatar generation requires realistic lip-sync, expressive motion, and real-time streaming. Recent work achieves the latter via self-forcing

Embodied-Navigator: Point, Think, Memorize, and Align for Efficient Navigation

arXiv:2608.17512v1 Announce Type: new Abstract: Although Large Vision-Language Models (VLMs) have significantly advanced embodied navigation, their direct deployment remains challenging, as existing m

Eval4Sim: An Evaluation Framework for Persona Simulation

arXiv:2603.02876v2 Announce Type: replace Abstract: Large Language Model personas, explicit profiles specifying a user's attributes, preferences, and behavioural tendencies, are increasingly used to s

Model Releases

Fair ASR: Re-Evaluating Black-Box Jailbreaks under Shared Target-Call Budgets

model-releasesarxiv-cs-ai

arXiv:2608.17360v1 Announce Type: cross Abstract: Reliable jailbreak evaluation is essential for assessing LLM safety, but most existing studies rely solely on attack success rate (ASR) without accoun

From Entity Mentions to Tone: An LLM-Based Pipeline for Media Bias Analysis

arXiv:2608.17454v1 Announce Type: new Abstract: This paper presents a pipeline for analyzing media bias and framing in online news. The pipeline groups articles into topics and events, adds named-enti

GUPO: Gradient Uncertainty-aware Policy Optimization for Post-Training Large Language Models

arXiv:2608.17411v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) has become a widely used approach for post-training Large Language Models (LLMs) for reasoning. In GRPO, the g

If OpenAI falls apart (or is e.g., acquired at a big discount), will that on net help or hurt Anthropic?

A forum poll posed the question, “If OpenAI falls apart or is acquired at a big discount, will that on net help or hurt Anthropic?” Participants chose among three options—help, hurt, or neutral—reflec

safetygary-marcus--x

Information Spreading in Diffusion Models from Effective Field Theory

arXiv:2608.14308v1 Announce Type: cross Abstract: We study score-matching diffusion models with a convolutional architecture. We argue that the inductive bias of locality means that the machinery of e

Judge, Retrieve, or Abstain: Uncertainty-Guarded LLM Judging with Provable Risk Guarantees

arXiv:2608.17994v1 Announce Type: new Abstract: Using LLMs as judges has become standard practice for evaluating model outputs at scale. This is particularly common for subjective, open-ended tasks su

KAN We Flow? Advancing Robotic Manipulation with 3D Flow Matching via KAN & RWKV

arXiv:2602.01115v3 Announce Type: replace-cross Abstract: Diffusion-based visuomotor policies excel at modeling action distributions but are inference-inefficient, since recursively denoising from noi

Lambda-Hold Control: Human-Like Movement Emerges from a Minimal Task Reward in Predictive Musculoskeletal Simulation

arXiv:2608.17030v1 Announce Type: new Abstract: The massive overactuation in the human musculoskeletal system makes it challenging to train musculoskeletal models to generate human-like motion via rei

ManiCM: Real-time 3D Diffusion Policy via Consistency Model for Robotic Manipulation

arXiv:2406.01586v4 Announce Type: replace-cross Abstract: Diffusion models have been verified to be effective in generating complex distributions from natural images to motion trajectories. Recent dif

Margin-Regularized Structured Semantic Alignment for Brain-Language Correspondence

arXiv:2608.16975v1 Announce Type: new Abstract: With the rapid advancement of large language models, brain-language decoding has achieved remarkable progress. However, it remains unclear whether decod

Monitoring Pasture Restoration from Satellite Image Time Series: Caveats and Opportunities

arXiv:2608.17704v1 Announce Type: new Abstract: Monitoring nature restoration at scale is an important but difficult ecological problem. Deep learning methods to analyze satellite image time series (S

No Gaussian Required: Contrastive Inverse Dynamics for JEPA World Models

arXiv:2608.17542v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architectures (JEPAs) learn world models by predicting future embeddings, but the objective admits a trivial solution of a

ORPA: Online Residual Policy Adaptation for Robot Manipulation Control with Human Feedback

arXiv:2608.17323v1 Announce Type: cross Abstract: Robotic manipulation policies trained via imitation learning, such as Action Chunking with Transformers (ACT), can achieve strong performance under id

Physics-Informed Sliding-Window Particle Filtering for Tactile-Only In-Hand 6-DoF Object Pose Refinement

arXiv:2608.17601v1 Announce Type: new Abstract: This paper studies tactile-only 6-DoF pose refinement and belief maintenance for grasped objects in static and short quasi-static in-hand configurations

PlanPO: Group Planning-Aware Policy Optimization for Multi-Turn Agentic LLMs

arXiv:2608.17289v1 Announce Type: new Abstract: Group-relative policy optimization has emerged as a key paradigm for training agentic large language models (LLMs) on multi-turn interactive tasks. Howe

Policy-Invariant Reward Shaping from LLM Feedback: A Framework for Hybrid RL Agents

arXiv:2608.18008v1 Announce Type: cross Abstract: Combining large language models with reinforcement learning is increasingly explored, yet the theoretical status of LLM-derived reward signals is ofte

Position: Fairness Failure in Generative Models is an Evaluation Problem

arXiv:2608.16974v1 Announce Type: cross Abstract: Despite groundbreaking advancements in generative models during the last decade, concerns about their lack of fairness, reinforcing societal inequalit

Prism-GRPO: Faster VLA Policy Optimization via Splitting Same-outcome Groups

arXiv:2608.17423v1 Announce Type: new Abstract: GRPO is increasingly used for reinforcement learning of vision-language-action (VLA) policies because, unlike PPO, it does not require training a critic

Q-Learning With World Models

arXiv:2608.17163v1 Announce Type: cross Abstract: Off-policy reinforcement learning (RL) has become increasingly sample-efficient, enabling applications such as RL fine-tuning of Vision-Language-Actio

Read it and weep for the AI bubble

Read it and weep for the AI bubble The unraveling of OpenAI sure looks like it has begun: https://garymarcus.substack.com/p/breaking-openais-unraveling-has-begun?utm_source=app-post-stats-page&r=8tdk6

safetygary-marcus--x

Reinforcement Learning as (Discrete) Potential Theory

arXiv:2608.17181v1 Announce Type: new Abstract: Reinforcement learning (RL) theory fundamentally depends on probability theory through the Markov chain. There is a deep connection between probability

Reinforcing Consistency in Video MLLMs with Structured Rewards

arXiv:2604.01460v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have achieved remarkable progress in video understanding. However, seemingly plausible outputs often suffer

Rethinking Irregular Time Series Forecasting from the Perspective of Basis Functions

arXiv:2608.17284v1 Announce Type: cross Abstract: Irregular time series forecasting is crucial in many domains, such as healthcare and meteorological observation. However, due to the inherent characte

Reuse Before You Retrieve: Diagnosing Headroom and Complementarity for Test-Time Augmentation of Embodied Multimodal Policies

arXiv:2608.17484v1 Announce Type: new Abstract: Frozen vision-language-action (VLA) policies are increasingly improved at test time by sampling additional policy behaviors or introducing external demo

SEE: Structure-aware Exploring & Exploiting for Long-horizon GUI Agent Trajectory Synthesis

arXiv:2607.18046v2 Announce Type: replace Abstract: Graphical User Interface (GUI) agents powered by vision-language models hold promise for automating real-world mobile tasks. However, progress is li

Solving nonconvex Hamilton--Jacobi--Isaacs equations with PINN-based policy iteration

arXiv:2507.15455v3 Announce Type: replace-cross Abstract: We propose a mesh-free policy iteration framework that combines classical dynamic programming with physics-informed neural networks (PINNs) to