safety

„Language models model language“ is going to be my quote of the week … maybe I print a T shirt for the next conference.

„Language models model language“ is going to be my quote of the week … maybe I print a T shirt for the next conference. super interesting - and a reminder that language models model language and not i

safetygary-marcus--x

Safety

Learning to Throw Objects Safely in Multi-Obstacle Environments

DGX agent

arXiv:2607.06388v1 Announce Type: cross Abstract: Robotic throwing enables fast and efficient object placement beyond the robot's immediate workspace, but reliable throwing in cluttered environments r

safetyarxiv-cs-cv

8 Jul 2026

Learning When to Automate: Queue Control in Human-AI Service Systems

arXiv:2607.06017v1 Announce Type: new Abstract: We study a human-AI service system in which tasks arrive sequentially and are processed through a two-stage architecture: an automated chatbot followed,

Lingering Authority: Revocable Resource-and-Effect Capabilities for Coding Agents

arXiv:2606.22504v1 Announce Type: cross Abstract: Coding agents often receive broad tool access for an entire task, even when a resource is needed only for one subgoal. We call this gap lingering auth

MAC-XA: Multi-view Anatomy-Correspondence Fusion for Coronary Stenosis Reporting from X-ray Angiography

arXiv:2607.06268v1 Announce Type: new Abstract: Multi-view reasoning in coronary X-ray angiography is inherently a cross-projection geometric problem, yet automated report generation in this setting r

MAME: Multidimensional Adaptive Metamer Exploration with Human Perceptual Feedback

arXiv:2503.13212v3 Announce Type: replace Abstract: Alignment between human brain networks and artificial models has become an active research area in vision science and machine learning. A widely ado

MASCA: LLM based-Multi Agents System for Credit Assessment

arXiv:2507.22758v2 Announce Type: replace Abstract: Recent advancements in financial problem-solving have leveraged LLMs and agent-based systems, with a primary focus on trading and financial modeling

// Memory becomes an action space // Great paper on long-term memory for agents. (bookmark it) In short, it's discusses the use of a learned…

// Memory becomes an action space // Great paper on long-term memory for agents. (bookmark it) In short, it's discusses the use of a learned policy for using memory at the right granularity. Most memo

safetydair-ai--x

Multimodal Analytics of Cybersecurity Crisis Preparation Exercises: What Predicts Success?

arXiv:2603.28553v2 Announce Type: replace-cross Abstract: Instructional alignment, the match between intended cognition and enacted activity, is central to effective instruction but hard to operationa

O3N: Omnidirectional Open-Vocabulary Occupancy Prediction

arXiv:2603.12144v2 Announce Type: replace Abstract: Understanding and reconstructing the 3D world through omnidirectional perception is becoming increasingly important for autonomous agents and embodi

OBBSeg: Irregular Lesion Segmentation under Oriented Bounding Box Annotations

arXiv:2607.06007v1 Announce Type: new Abstract: Pixel-level annotation remains a major bottleneck in medical image segmentation, making weak supervision an attractive yet under-constrained alternative

Optimal Transport Q-Learning for Flow Policy Steering and Acceleration

arXiv:2607.06262v1 Announce Type: new Abstract: Diffusion and flow policies have recently demonstrated remarkable performance in robotic applications by accurately capturing multimodal robot trajector

safetyarxiv-cs-ro

Our approach to government and national security partnerships

OpenAI outlines its strategy for collaborating with government agencies and national security institutions, likely covering principles for responsible AI deployment in defense and security contexts. T

safetyopenai

Platonic Representations for Poverty Mapping: Unified Vision-Language Codes or Agent-Induced Novelty?

arXiv:2508.01109v3 Announce Type: replace Abstract: We investigate whether socioeconomic indicators, like household wealth, leave recoverable informational imprints in both satellite imagery (capturin

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models

arXiv:2607.05441v1 Announce Type: cross Abstract: Integrating external tools with Large Language Models (LLMs) has emerged as a promising paradigm for accomplishing complex tasks. Since LLMs still str

Position: EU AI Act's Research Exemptions Can Break the Publication Norms of Major AI Conferences

arXiv:2506.03218v2 Announce Type: replace-cross Abstract: The EU has become one of the vanguards in regulating the digital age. A particularly important regulation in the Artificial Intelligence (AI)

Position: Preventing AI-Generated CSAM Necessitates New Approaches to AI Safety

arXiv:2607.05407v1 Announce Type: cross Abstract: Modern artificial intelligence (AI) systems present profound new risks to child safety. AI is increasingly being misused to create AI-generated child

Property-Driven Synthetic Data Engineering for Data-Scarce Software Systems: Reflections from the Breast Cancer Domain

arXiv:2607.06133v1 Announce Type: cross Abstract: Modern software systems increasingly depend on data for analysis, prediction, testing, and decision-making. Yet many important domains, including medi

Quantifying Retriever-Generator Alignment in RAG with Local Explanations

arXiv:2601.21803v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems combine dense retrievers and language models to ground their outputs in external documents. However, th

Realistic Compound-Lens Defocus Blur Synthesis

arXiv:2607.05837v1 Announce Type: new Abstract: Defocus blur degrades fine image structures and limits visual perception, which can adversely affect downstream vision tasks. Although recent deep learn

Recovering Cloud Microstructures with Cascaded Diffusion Inversion

arXiv:2607.05637v1 Announce Type: new Abstract: High-resolution satellite imagery is critical for observing fine-scale cloud structures that inform weather modification strategies like cloud seeding f

RoboTALES: Learning Reasoning-Guided Robot Policies via Task-Aligned Simulated Futures

arXiv:2607.06018v1 Announce Type: new Abstract: Pretrained video generative models are promising backbones for visuomotor control, but their imagined futures often drift from task intent and are not r

safetyarxiv-cs-ro

RynnWorld-4D: 4D Embodied World Models for Robotic Manipulation

arXiv:2607.06559v1 Announce Type: new Abstract: Robotic manipulation in the open world requires not only recognizing what a scene looks like, but also anticipating how its 3D structure moves under int

safetyarxiv-cs-ro

Safe Bayesian Optimization with Counterfactual Policies

arXiv:2607.05620v1 Announce Type: cross Abstract: In many decision-making settings, new interventions are acceptable only if they do not reduce outcomes below some established threshold. For example,

SearchEyes: Towards Frontier Multimodal Deep Search Intelligence via Search World Simulation

arXiv:2607.05943v1 Announce Type: new Abstract: Training multimodal search agents to perform multi-hop reasoning remains challenging due to a fundamental structural disconnect: existing pipelines cons

Securing Amazon Bedrock AgentCore Runtime with AWS WAF

This post shows you two architecture patterns that address this problem. Both use an internet-facing ALB with AWS WAF and route traffic through a VPC Interface Endpoint to AgentCore Runtime. Pattern 1

safetyaws-ml-blog

SpatialFly: Implicit 3D Prior-Guided Visual Reparameterization for Continuous UAV Vision-and-Language Navigation

arXiv:2603.21046v2 Announce Type: replace-cross Abstract: UAVs play an important role in applications such as autonomous exploration, disaster response, and infrastructure inspection. However, UAV VLN

Stability Annealing Selects the Implicit Bias of Smoothed Sign Descent: A Rate-Indexed Barrier Path on Separable Data

arXiv:2607.06013v1 Announce Type: new Abstract: Adaptive gradient methods can favor max-margin separators that differ from gradient descent, yet a fixed positive numerical stability constant eventuall

Statistical Adversaries: Natural Backdoor-like Features in Vision Datasets

arXiv:2607.05516v1 Announce Type: cross Abstract: Model-specific adversarial attacks have been extensively studied. We study a different failure mode: naturally occurring statistical signals in vision

Straight-Path Flow Matching for Incomplete Multi-View Clustering

arXiv:2607.06281v1 Announce Type: new Abstract: Incomplete Multi-View Clustering addresses the problem of clustering multi-modal data when certain views are missing. Recent end-to-end generative appro

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition

arXiv:2607.06185v1 Announce Type: new Abstract: Fine-grained image recognition poses a significant challenge due to the substantial expertise and effort required for manual annotation. Vision-language

Superman: Unifying Skeleton and Vision for Human Motion Perception and Generation

arXiv:2602.02401v2 Announce Type: replace Abstract: Human motion analysis tasks, such as temporal 3D pose estimation, motion prediction, and motion in-betweening, play an essential role in computer vi

Synthetic-to-Real Translation for Class-Agnostic Motion Prediction

arXiv:2607.06319v1 Announce Type: new Abstract: Motion understanding is critical for ensuring safety and robustness in autonomous driving systems, driving increasing interest in motion prediction. A k

The Jagged Global Economy: Frontier AI Unevenly Exposes National Economies

arXiv:2607.05404v1 Announce Type: cross Abstract: Frontier AI's labor-market effects matter to workers, firms, and policymakers, but current evidence generally comes from a handful of high-income econ

The Large Cancer Assistant (LCA): A Model-Agnostic Orchestration Framework for Scalable Clinical Decision Support in Oncology

arXiv:2607.06531v1 Announce Type: new Abstract: - Objective: Multimodal deep learning models in oncology are currently limited by monolithic designs that rigidly couple data ingestion, clinical routin

TILDE: TILt-based Distributional Erasure for Concept Unlearning

arXiv:2607.06432v1 Announce Type: cross Abstract: Concept unlearning in text-to-image diffusion models is critical for safe and practical deployment: with rising privacy concerns, copyright disputes,

To Retain or to Adapt? Generalizing Continual Learning

arXiv:2607.05609v1 Announce Type: cross Abstract: The Continual Learning (CL) literature has long been driven by the goal of mitigating catastrophic forgetting. This objective rests on a pervasive, of

Truthful or Fabricated? Using Causal Attribution to Mitigate Reward Hacking in Explanations

arXiv:2504.05294v3 Announce Type: replace Abstract: Chain-of-thought explanations are widely used to inspect the decision process of large language models (LLMs) and to evaluate the trustworthiness of

TurnOPD: Making On-Policy Distillation Turn-Aware for Efficient Long-Horizon Agent Training

arXiv:2607.05804v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student policy by matching a stronger teacher on the student's own trajectories, offering a promising framework fo

UniField: A Unified Field-Aware MRI Enhancement Framework

arXiv:2603.09223v2 Announce Type: replace Abstract: Magnetic Resonance Imaging (MRI) field-strength enhancement holds immense value for both clinical diagnostics and advanced research. However, existi

VEIL: How Visual Encoding Hijacking Induces Bias In Vision Models

arXiv:2607.05641v1 Announce Type: new Abstract: Rendering time series as chart images for CNN-based classification has become increasingly common in time-series classification (TSC). However, it remai

Volumetric Directional Diffusion: Anchoring Uncertainty Quantification in Anatomical Consensus for Ambiguous Medical Image Segmentation

arXiv:2603.04024v2 Announce Type: replace-cross Abstract: Ambiguous 3D medical image segmentation often involves boundaries where different expert delineations are non-identical yet clinically plausib

When Lower Privileges Suffice: Investigating Over-Privileged Tool Selection in LLM Agents

arXiv:2606.20023v2 Announce Type: replace-cross Abstract: As LLM agents increasingly select tools autonomously, their choices among tools with different privileges become safety-relevant. However, pri

Whose fairness? Structural concentration in AI bias research

arXiv:2607.05574v1 Announce Type: cross Abstract: Artificial intelligence increasingly mediates consequential decisions in healthcare, law, and public services, and the field has responded with an ext

Width-Robust Learnability in Mean-Field Bayesian Neural Networks

arXiv:2607.05735v1 Announce Type: cross Abstract: Infinite-width limits are a standard way to reason about neural networks, but it is not automatic that the limiting learner has the same complexity-th

WordVoice: Explicit and Decoupled Multi-Dimensional Word-Level Control for LLM-Based TTS

arXiv:2607.06461v1 Announce Type: cross Abstract: While recent Large Language Model (LLM)-based Text-to-Speech (TTS) systems have achieved remarkable naturalness, they predominantly rely on implicit e

X-FEMR: A Token-level Explainable Approach for Electronic Health Records Foundation Models using Transformer-based Models

arXiv:2607.06163v1 Announce Type: cross Abstract: Foundation Models for Electronic Health Records (FEMRs) are pretrained on large-scale structured patient data, enabling them to convert longitudinal p

A Bayesian Framework for Evaluating Scenario Compatibility in Generative Population Synthesis

arXiv:2607.03190v1 Announce Type: cross Abstract: Scenario-based transportation analysis specifies future assumptions through aggregate population targets, whereas generative population synthesis mode