safety

OneShot: Index-in-Ranking with Neural Scoring for Large-Scale Retrieval

arXiv:2607.27475v1 Announce Type: cross Abstract: In modern recommendation systems, retrieval serves as a primary stage responsible for filtering billions of candidate items down to thousands prior to

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OPLD: On-Policy Latent Distillation for Multimodal Reasoning

DGX agent

arXiv:2607.28154v1 Announce Type: new Abstract: Interleaved multimodal Chain-of-Thought (CoT) improves visual reasoning by incorporating auxiliary visual evidence into intermediate reasoning. However,

safetyarxiv-cs-cv

31 Jul 2026

Optimizing Regret

arXiv:2607.18866v2 Announce Type: replace-cross Abstract: Building on the identity that expected regret equals the covariance between costs and decisions, this paper develops a derivative theory of th

Optimizing Sensor Placement for Hydrogen Leak Detection in Enclosed Infrastructure: A Comparative Study Using CFD-informed Genetic Algorithm and DeepSets Neural Surrogate

arXiv:2607.26078v1 Announce Type: cross Abstract: Hydrogen infrastructure in enclosed environments, such as parking facilities for fuel cell vehicles, presents significant safety challenges due to hyd

Policy Gradient Steering: Interventions from Behavioral Objectives

arXiv:2607.27574v1 Announce Type: new Abstract: Activation steering has emerged in large language models as a lightweight alternative for dynamically changing a model's behavior at inference time. How

PoseMaster: A Unified 3D Native Framework for Stylized Pose Generation

arXiv:2506.21076v4 Announce Type: replace Abstract: Pose stylization, which aims to synthesize stylized content aligning with target poses, serves as a fundamental task across 2D, 3D, and video domain

Procedural Fairness in Multi-Agent Bandits

arXiv:2601.10600v2 Announce Type: replace-cross Abstract: In the context of multi-agent multi-armed bandits (MA-MAB), fairness is often reduced to outcomes: maximizing welfare, reducing inequality, or

QQWorld: Quantile-Quantile Matching for World Model Regularization

arXiv:2607.28415v1 Announce Type: cross Abstract: Latent world models enable efficient planning by predicting future states in a compact representation space, but their performance depends critically

Real-Time Hard Peak Age-of-Information Safety with No-Regret Learning

arXiv:2607.27626v1 Announce Type: new Abstract: Safety-critical IoT systems such as industrial closed-loop control, V2X coordination, and remote teleoperation require every sensor's peak Age of Inform

Recognition and Label-Free Adaptation Across Recording Sessions in Surface-EMG Gesture Decoding

arXiv:2607.27568v1 Announce Type: new Abstract: Recognition accuracy obtained during a recording session does not persist when a user puts on the electrodes again after the electrodes had previously b

ReDiPPO: Reference-Guided Value Calibration and Discrepancy-Aware Token Reweighting for Mathematical Reasoning

arXiv:2607.27631v1 Announce Type: cross Abstract: Reinforcement learning has emerged as an effective paradigm for enhancing the mathematical reasoning capabilities of large language models. Among exis

REFINE-DP: Diffusion Policy Fine-tuning for Humanoid Loco-manipulation via Reinforcement Learning

arXiv:2603.13707v3 Announce Type: replace-cross Abstract: Humanoid loco-manipulation requires coordinated task-space motion planning with stable loco-manipulation command tracking under complex robot-

Regularizing modality contribution drift in multimodal continual learning

arXiv:2607.27260v1 Announce Type: new Abstract: Multimodal continual learning (MMCL) aims to learn emerging knowledge from multimodal data while preserving knowledge. To mitigate forgetting, current M

Reviewer Scores Are Not Comparable Across Research Areas in ML Peer Review

arXiv:2607.27209v1 Announce Type: cross Abstract: Peer review at ML conferences increasingly relies on reviewer scores as the primary decision instrument. As submissions have scaled from thousands to

ROAD: Reciprocal-Objective Alignment of Discriminative Semantics for 3D Shape Generation

arXiv:2607.28581v1 Announce Type: new Abstract: High-fidelity 3D generation predominantly relies on scaling model capacity and data, which incurs prohibitive computational costs. This paradigm typical

Robust Estimation of Sparse Numerical Vectors under Local Differential Privacy

arXiv:2607.27815v1 Announce Type: cross Abstract: Local differential privacy (LDP) protocols are vulnerable to poisoning attacks. Existing research have proposed efficient defense strategies for singl

Safety Verification of Wait-Only Non-Blocking Broadcast Protocols

arXiv:2403.18591v3 Announce Type: replace-cross Abstract: Broadcast protocols are programs designed to be executed by networks of processes. Each process runs the same protocol, and communication betw

SCOPE: Supply-Chain Operations through Coupled Policies for End-to-End Coordination

arXiv:2607.28488v1 Announce Type: cross Abstract: Can supply-chain AI move beyond isolated decision modules toward unified operational planning? A complete replenishment plan specifies which products

ServerlessT2I: Efficient Text-to-Image Workflow Serving on a Serverless Platform

arXiv:2607.26566v1 Announce Type: cross Abstract: Text-to-image (T2I) workflows are increasingly deployed on serverless platforms because users often compose customized workflows and invoke them inter

SimpleWikiSearch: A Clean Offline Wikipedia Environment for Agentic Search

arXiv:2607.26070v1 Announce Type: cross Abstract: Large language model (LLM)-based agentic search systems are often evaluated as if the underlying LLM were the only component that matters, yet their m

SkillSight: Calibrating Generic Content Bias for Skill Retrieval

arXiv:2607.18785v2 Announce Type: replace Abstract: As large language model agents gain access to increasingly large skill libraries, retrieving the right skill becomes critical to reliable capability

State-Dependent Safety Failures in Multi-Turn Language Model Interaction

arXiv:2603.15684v2 Announce Type: replace-cross Abstract: Safety alignment in large language models is typically evaluated under isolated queries, yet real-world use is inherently multi-turn. Although

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation

arXiv:2607.27890v1 Announce Type: new Abstract: Visuomotor policies have advanced on manipulation tasks where the target object stays static during execution, but real deployments break this assumptio

safetyarxiv-cs-ro

Strategies for Milestone-driven Start-ups in Multi-activity Settings

arXiv:2607.27563v1 Announce Type: new Abstract: New venture start-ups need to ``survive'' through multiple stages of reaching milestone targets. We investigate the strategies for start-ups in a milest

SVR: Self-Verifying Refinement via Joint Verdict-Confidence Reinforcement Learning for Adaptive Test-Time Compute

arXiv:2607.28457v1 Announce Type: cross Abstract: Scaling test-time computation can improve language-model reasoning, but uniform budgets waste computation on easy inputs, while verifier-guided refine

TAPO: Transition-Aware Policy Optimization for LLM Agents

arXiv:2607.27973v1 Announce Type: new Abstract: Recently, Reinforcement Learning (RL) has emerged as a crucial paradigm for the post-training of Large Language Model (LLM) agents. However, existing me

Temporal Concentration from Rollout Errors: Implicit Preference Optimization for Text-to-Video Diffusion

arXiv:2607.28058v1 Announce Type: new Abstract: Recent advances in preference alignment for diffusion-based video generation, particularly via Direct Preference Optimization (DPO), have significantly

The Confidence Manifold: Geometric Structure of Correctness Representations in Language Models

arXiv:2602.08159v2 Announce Type: replace-cross Abstract: When a language model asserts that 'the capital of Australia is Sydney,' does it know this is wrong? Models assert misconceptions with the sam

The Easy Trap: Why LLMs Underestimate Misconception-Driven Difficulty

arXiv:2607.26067v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for estimating item difficulty in educational assessment. However, it remains unclear whether such

The Human Utility Factor: A Computable Welfare Metric That Reframes AI Governance as a Constrained Optimisation Problem

arXiv:2607.26068v1 Announce Type: cross Abstract: Existing AI governance frameworks, including the EU AI Act and NIST AI RMF, address safety, transparency, and accountability but do not operationalize

The Kinetics of Training: A Driven-Nucleation Rate Law for Emergence, Plasticity Loss, and Circuit Control in Language Models

arXiv:2607.27281v1 Announce Type: new Abstract: A capability appears in a language model when the last parts of its circuit align in one stochastic attempt, and getting all but one right is worth noth

this is the whole problem in a nutshell. LLM-centered systems just can’t be trusted to follow hard constraints, we absolutely must find alte…

this is the whole problem in a nutshell. LLM-centered systems just can’t be trusted to follow hard constraints, we absolutely must find alternatives that can, or we are screwed. Anybody remember this

safetygary-marcus--x

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles

arXiv:2607.28483v1 Announce Type: new Abstract: Real-time anomaly segmentation is essential for the safety of autonomous systems. Although recent approaches offer high accuracy, their computational co

Uncertainty quantification for trustworthy deep learning: Methods and measures

arXiv:2607.28248v1 Announce Type: cross Abstract: The deployment of deep neural networks in safety-critical domains demands reliable estimates of predictive confidence, yet conventional architectures

UniCross: Unified Cross-Skill Dexterous Manipulation Synthesis

arXiv:2607.28198v1 Announce Type: cross Abstract: Many dexterous manipulation tasks require the object to remain securely held throughout the interaction. From the perspective of hand-object relationa

Unifying Adversarially Robust Model Experts in Vision-Language Models

arXiv:2607.27897v1 Announce Type: new Abstract: Vision-language models (VLMs), such as CLIP, are vulnerable to adversarial attacks, posing a serious problem for real-life applications and deployment.

VAD: Attributing Visual Evidence for Target Reconstruction in Multimodal On-Policy Distillation

arXiv:2607.28590v1 Announce Type: cross Abstract: Multimodal on-policy distillation (OPD) transfers fine-grained visual knowledge by supervising student-generated trajectories with a privileged-view t

Variance-Aware Baselines and Adaptive Learning Rates for Reinforcement Learning with Verifiable Rewards

arXiv:2511.23310v3 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as an effective paradigm for post-training large language models, yet the de

When Does Explicit View Routing Work? A Controlled Study of Multi-View Graph-Text Alignment

arXiv:2607.27530v1 Announce Type: new Abstract: Graph-text retrieval typically maps a graph and its description to a single embedding, even when a query concerns only one semantic aspect, such as a cl

World Action Planner: Generalizable Decision-Making with Action-Conditioned World Models

arXiv:2607.27599v1 Announce Type: cross Abstract: Building generalizable agents for diverse applications remains a fundamental challenge. While imitation learning-based policies succeed in specific tr

safetyarxiv-cs-ro

A fundamental flaw leaves LLMs strikingly vulnerable to attack

It is impossible to make large language models fully secure against hacks because of a fundamental flaw in how they work, a team of researchers argue in a paper presented at the International Conferen

safetymit-tech-review

A Persona-based Rate Action Index

arXiv:2607.26545v1 Announce Type: cross Abstract: We propose an index for predicting the U.S. Federal Open Market Committee (FOMC) decision to hike/hold/cut the current federal funds target rate based

A Picture Says Thousands of Words - Harnessing Dermal Exposure Data from Images through Hybrid Deep Learning for Enhanced Safety Assessment

arXiv:2607.26170v1 Announce Type: new Abstract: This study developed a hybrid computer vision method to quantify exposed skin from images for dermal exposure assessment. Using 170 indoor-painting imag

AgentGFM: A Graph Foundation Model with Node-Agent Information-Flow Control

arXiv:2607.26533v1 Announce Type: new Abstract: Graph Foundation Models (GFMs) aim to learn transferable knowledge from multi-domain graphs and adapt to unseen scenarios. As a fundamental source of re

AgentSnare: Learning to Delay, Divert, and Defuse Autonomous Penetration Agents

arXiv:2607.26998v1 Announce Type: cross Abstract: Large language model (LLM) agents automate penetration testing through an observation-action loop, selecting actions based on observations returned by

AI Alignment in Medical Imaging: Unveiling Hidden Biases Through Counterfactual Analysis

arXiv:2504.19621v2 Announce Type: replace Abstract: Machine learning (ML) systems for medical imaging have demonstrated remarkable diagnostic capabilities, but their susceptibility to biases poses sig

AlloyDB adds group authentication to secure enterprise scale and AI agents

Database security traditionally relies on a fragile balance between the granular control developers need and the administrative overhead of managing thousands of individual database passwords. Between

safetygoogle-cloud-ai

Anatomy Contextualized Adaption of CT Foundation Models

arXiv:2607.27154v1 Announce Type: new Abstract: CT vision-language foundation models have demonstrated promising performance across downstream tasks, but are typically trained with whole-volume repres