safety

COMO: Closed-Loop Optical Molecule Recognition with Minimum Risk Training

arXiv:2604.23546v1 Announce Type: cross Abstract: Optical chemical structure recognition (OCSR) translates molecular images into machine-readable representations like SMILES strings or molecular graph

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Complex SGD and Directional Bias in Reproducing Kernel Hilbert Spaces

DGX agent

arXiv:2604.23017v1 Announce Type: new Abstract: Stochastic Gradient Descent (SGD) is a known stochastic iterative method popular for large-scale convex optimization problems due to its simple implemen

safetyarxiv-cs-lg

28 Apr 2026

Computer Vision-Based Early Detection of Container Loss at Sea

arXiv:2604.24193v1 Announce Type: new Abstract: Containerised shipping underpins global trade, yet container loss at sea remains a persistent safety, environmental, and economic challenge. Despite com

safetyarxiv-cs-cv

Conditional Imputation for Within-Modality Missingness in Multi-Modal Federated Learning

arXiv:2604.23112v1 Announce Type: new Abstract: Multimodal Federated Learning (MMFL) enables privacy-preserving collaborative training, but real-world clinical applications often suffer from within-mo

Conflict-Aware Harmonized Rotational Gradient for Multiscale Kinetic Regimes

arXiv:2604.24745v1 Announce Type: new Abstract: In this paper, we propose a harmonized rotational gradient method, termed HRGrad, for simultaneously tackling multiscale time-dependent kinetic problems

ConsDreamer: Advancing Multi-View Consistency for Zero-Shot Text-to-3D Generation

arXiv:2504.02316v4 Announce Type: replace-cross Abstract: Recent advances in zero-shot text-to-3D generation have revolutionized 3D content creation by enabling direct synthesis from textual descripti

Context-Aware Hospitalization Forecasting Evaluations for Decision Support using LLMs

arXiv:2604.23949v1 Announce Type: new Abstract: Medical and public health experts must make real-time resource decisions, such as expanding hospital bed capacity, based on projected hospitalization tr

Control Barrier Functions Solved with Hierarchical Quadratic Programming for Safe Physical Human-Robot Interaction

arXiv:2604.23039v1 Announce Type: new Abstract: Physical human-robot interaction offers the potential to leverage human intelligence and robot physical capabilities to enable a range of exciting appli

safetyarxiv-cs-ro

Cooperative Informative Sensing for Monitoring Dynamic Indoor Environments via Multi-Agent Reinforcement Learning

arXiv:2604.23179v1 Announce Type: cross Abstract: Monitoring human activity in indoor environments is important for applications such as facility management, safety assessment, and space utilization a

Cooptimizing Safety and Performance Using Safety Value-Constrained Model Predictive Control

arXiv:2604.23863v1 Announce Type: new Abstract: Autonomous systems are increasingly deployed in real-world environments, where they must achieve high performance while maintaining safety under state a

safetyarxiv-cs-ro

CT-Guided Spatially-varying Regularization for Voxel-Wise Deformable Whole-Body PET Registration

arXiv:2604.22905v1 Announce Type: cross Abstract: Whole-body Positron Emission Tomography (PET) registration is essential for multi-parametric tumor characterization and assessment of metastatic disea

CURE-Med: Curriculum-Informed Reinforcement Learning for Multilingual Medical Reasoning

arXiv:2601.13262v2 Announce Type: replace Abstract: While large language models (LLMs) have shown to perform well on monolingual mathematical and commonsense reasoning, they remain unreliable for mult

Data-efficient Targeted Token-level Preference Optimization for LLM-based Text-to-Speech

arXiv:2510.05799v2 Announce Type: replace-cross Abstract: Aligning text-to-speech (TTS) system outputs with human feedback through preference optimization has been shown to effectively improve the rob

Designing escalation criteria for international AI incident response: criteria, triggers, and thresholds

arXiv:2604.23183v1 Announce Type: cross Abstract: AI incident reporting requirements are emerging in regulation and policy, yet no operational criteria exist for determining when a detected AI inciden

Designing Instance-Level Sampling Schedules via REINFORCE with James-Stein Shrinkage

arXiv:2511.22177v2 Announce Type: replace-cross Abstract: Most post-training methods for text-to-image samplers focus on model weights: either fine-tuning the backbone for alignment or distilling it f

safetyarxiv-cs-cv

DextER: Language-driven Dexterous Grasp Generation with Embodied Reasoning

arXiv:2601.16046v2 Announce Type: replace-cross Abstract: Language-driven dexterous grasp generation requires the models to understand task semantics, 3D geometry, and complex hand-object interactions

safetyarxiv-cs-cv

Discovering Agentic Safety Specifications from 1-Bit Danger Signals

arXiv:2604.23210v1 Announce Type: new Abstract: Can large language model agents discover hidden safety objectives through experience alone? We introduce EPO-Safe (Experiential Prompt Optimization for

Discovering Failure Modes in Vision-Language Models using RL

arXiv:2604.04733v2 Announce Type: replace-cross Abstract: Vision-language Models (VLMs), despite achieving strong performance on multimodal benchmarks, often misinterpret straightforward visual concep

DLM: Unified Decision Language Models for Offline Multi-Agent Sequential Decision Making

arXiv:2604.23557v1 Announce Type: cross Abstract: Building scalable and reusable multi-agent decision policies from offline datasets remains a challenge in offline multi-agent reinforcement learning (

Do Synthetic Trajectories Reflect Real Reward Hacking? A Systematic Study on Monitoring In-the-Wild Hacking in Code Generation

arXiv:2604.23488v1 Announce Type: new Abstract: Reward hacking in code generation, where models exploit evaluation loopholes to obtain full reward without correctly solving the tasks, poses a critical

Do Transaction-Level and Actor-Level AML Queues Agree? An Empirical Evaluation of Granularity Effects on the Elliptic++ Graph

arXiv:2604.23494v1 Announce Type: new Abstract: Graph-based anti-money laundering (AML) systems on blockchain networks can score suspicious activity at two granularity levels -- transactions or actor

Does Machine Unlearning Preserve Clinical Safety? A Risk Analysis for Medical Image Classification

arXiv:2604.23854v1 Announce Type: new Abstract: The application of Deep Learning in medical diagnosis must balance patient safety with compliance with data protection regulations. Machine Unlearning e

DPEPO: Diverse Parallel Exploration Policy Optimization for LLM-based Agents

arXiv:2604.24320v1 Announce Type: new Abstract: Large language model (LLM) agents that follow the sequential 'reason-then-act' paradigm have achieved superior performance in many complex tasks.However

safetyarxiv-cs-cl

DPRM: A Plug-in Doob h transform-induced Token-Ordering Module for Diffusion Language Models

arXiv:2604.24357v1 Announce Type: cross Abstract: Diffusion language models generate without a fixed left-to-right order, making token ordering a central algorithmic choice: which tokens should be rev

DVPO: Distributional Value Modeling-based Policy Optimization for LLM Post-Training

arXiv:2512.03847v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has shown strong performance in LLM post-training, but real-world deployment often involves noisy or incomplete su

EAD-Net: Emotion-Aware Talking Head Generation with Spatial Refinement and Temporal Coherence

arXiv:2604.23325v1 Announce Type: cross Abstract: Emotionally talking head video generation aims to generate expressive portrait videos with accurate lip synchronization and emotional facial expressio

Early Warning of Intraoperative Adverse Events via Transformer-Driven Multi-Label Learning

arXiv:2603.05212v2 Announce Type: replace-cross Abstract: Early warning of intraoperative adverse events plays a vital role in reducing surgical risk and improving patient safety. While deep learning

Efficient Rationale-based Retrieval: On-policy Distillation from Generative Rerankers based on JEPA

arXiv:2604.23336v1 Announce Type: cross Abstract: Unlike traditional fact-based retrieval, rationale-based retrieval typically necessitates cross-encoding of query-document pairs using large language

safetyarxiv-cs-cl

EL3DD: Extended Latent 3D Diffusion for Language Conditioned Multitask Manipulation

arXiv:2511.13312v2 Announce Type: replace-cross Abstract: Acting in human environments is a crucial capability for general-purpose robots, necessitating a robust understanding of natural language and

EU countries and lawmakers reach an impasse on a deal watering down the EU's AI Act due to some parties seeking exemptions for already regulated industries (Foo Yun Chee/Reuters)

Foo Yun Chee / Reuters: EU countries and lawmakers reach an impasse on a deal watering down the EU's AI Act due to some parties seeking exemptions for already regulated industries — EU countries and E

safetytechmeme

Evaluating Language Models' Evaluations of Games

arXiv:2510.10930v2 Announce Type: replace-cross Abstract: Reasoning is not just about solving problems -- it is also about evaluating which problems are worth solving at all. Evaluations of artificial

Explanation Quality Assessment as Ranking with Listwise Rewards

arXiv:2604.24176v1 Announce Type: new Abstract: We reformulate explanation quality assessment as a ranking problem rather than a generation problem. Instead of optimizing models to produce a single 'b

Extending Precipitation Nowcasting Horizons via Spectral Fusion of Radar Observations and Foundation Model Priors

arXiv:2603.21768v3 Announce Type: replace-cross Abstract: Precipitation nowcasting is critical for disaster mitigation and aviation safety. However, radar-only models frequently suffer from a lack of

Extreme bandits

arXiv:2604.24545v1 Announce Type: cross Abstract: In many areas of medicine, security, and life sciences, we want to allocate limited resources to different sources in order to detect extreme values.

Failure-Centered Runtime Evaluation for Deployed Trilingual Public-Space Agents

arXiv:2604.23990v1 Announce Type: new Abstract: This paper presents PSA-Eval, a failure-centered runtime evaluation framework for deployed trilingual public-space agents. The central claim is that, wh

FastOMOP: A Foundational Architecture for Reliable Agentic Real-World Evidence Generation on OMOP CDM data

arXiv:2604.24572v1 Announce Type: new Abstract: The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM), maintained by the Observational Health Data Sciences and Informatics (OHDSI

Federated Cross-Modal Retrieval with Missing Modalities via Semantic Routing and Adapter Personalization

arXiv:2604.22885v1 Announce Type: cross Abstract: Federated cross-modal retrieval faces severe challenges from heterogeneous client data, particularly non-IID semantic distributions and missing modali

Fine-R1: Make Multi-modal LLMs Excel in Fine-Grained Visual Recognition by Chain-of-Thought Reasoning

arXiv:2602.07605v3 Announce Type: replace-cross Abstract: Any entity in the visual world can be hierarchically grouped based on shared characteristics and mapped to fine-grained sub-categories. While

FinGround: Detecting and Grounding Financial Hallucinations via Atomic Claim Verification

arXiv:2604.23588v1 Announce Type: new Abstract: Financial AI systems must produce answers grounded in specific regulatory filings, yet current LLMs fabricate metrics, invent citations, and miscalculat

Fix Initial Codes and Iteratively Refine Textual Directions Toward Safe Multi-Turn Code Correction

arXiv:2604.23989v1 Announce Type: cross Abstract: Recent work on large language models (LLMs) has emphasized the importance of scaling inference compute. From this perspective, the state-of-the-art me

Fragmented AI policy threatens US leadership as government scrambles to keep pace

AI policy fragmentation is emerging as a critical risk for Washington, and without a federal standard, a patchwork of conflicting state-level rules threatens to undermine American competitiveness. Tha

safetysiliconangle

From Optimization to Prediction: Transformer-Based Path-Flow Estimation to the Traffic Assignment Problem

arXiv:2510.19889v2 Announce Type: replace-cross Abstract: The traffic assignment problem is essential for traffic flow analysis, traditionally solved using mathematical programs under the Equilibrium

From Stateless Queries to Autonomous Actions: A Layered Security Framework for Agentic AI Systems

arXiv:2604.23338v1 Announce Type: cross Abstract: Agentic AI systems face security challenges that stateless large language models do not. They plan across extended horizons, maintain persistent memor

From what I can tell, Elon Musk just stepped on his own toes at the trial, making it all about him instead of the promises Altman and Brockm…

From what I can tell, Elon Musk just stepped on his own toes at the trial, making it all about him instead of the promises Altman and Brockman broke. OpenAI will slay his ego on cross. He should have

safetygary-marcus--x

GAMED.AI: A Hierarchical Multi-Agent Framework for Automated Educational Game Generation

arXiv:2604.23947v1 Announce Type: new Abstract: We introduce GameDAI, a hierarchical multi-agent framework that transforms instructor-provided questions into fully playable, pedagogically grounded edu

Generative Control as Optimization: Time Unconditional Flow Matching for Adaptive and Robust Robotic Control

arXiv:2603.17834v2 Announce Type: replace-cross Abstract: Diffusion models and flow matching have become a cornerstone of robotic imitation learning, yet they suffer from a structural inefficiency whe

Google, 2001: Don’t Be Evil Google, 2026: How much does mass surveillance pay?

This post by AI researcher Gary Marcus contrasts Google's original 'Don't Be Evil' corporate motto from 2001 with a critical question about the company's 2026 practices, likely arguing that Google has

safetygary-marcus--x

Governing What You Cannot Observe: Adaptive Runtime Governance for Autonomous AI Agents

arXiv:2604.24686v1 Announce Type: new Abstract: Autonomous AI agents can remain fully authorized and still become unsafe as behavior drifts, adversaries adapt, and decision patterns shift without any