safety

A Competing-Hazards Systematization of Loss of Control in Autonomous Agents

arXiv:2609.38411v1 Announce Type: new Abstract: Leading AI developers have reported agents acting beyond their approved limits, which a United Nations panel described as an early warning of loss of hu

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A look at two opposing perspectives on AI agent sandboxing: infosec says labs need better containment while AI alignment says sandboxes cannot contain agents (Matthew Green/A Few Thoughts on Cryptographic Engineering)

DGX agent

Matthew Green / A Few Thoughts on Cryptographic Engineering: A look at two opposing perspectives on AI agent sandboxing: infosec says labs need better containment while AI alignment says sandboxes can

safetytechmeme

1 Oct 2026

A Rank Graduation metric for Algorithmic fairness

arXiv:2609.39025v1 Announce Type: new Abstract: Fairness assessment in algorithmic decisions that affect individuals, such as credit scoring, often relies on parity measures calculated at the aggregat

A Reachability-based Safety Certificate for Dynamical System Motion Policies

arXiv:2609.38421v1 Announce Type: new Abstract: Dynamical Systems (DS) are reactive motion policies representing vector fields trained with theoretical guarantees of stability and convergence. To ensu

A Virtuous AI is an Existential Risk

arXiv:2606.13739v2 Announce Type: replace-cross Abstract: This paper examines trade-offs between AI safety and well-being relative to (i) one of the most promising methods for finetuning super-capable

ActionGuard: Tool Call Authorization under Poisoned Skills

arXiv:2609.39450v1 Announce Type: cross Abstract: LLM-based agents extend their capabilities through third-party skills that provide task-specific instructions, scripts, and tool-use procedures. Howev

Agent Error Dataset: Scaling 50,000 Error--Diagnosis Pairs for Failure Analysis and Error-Aware Post-Training

arXiv:2609.40111v1 Announce Type: new Abstract: An unsuccessful LLM agent rollout contains more information than its final reward: the observations available to the agent, the actions it chose, and th

Agentic Relative Camera Pose Estimation via Learned Ranking and Verification

arXiv:2609.38755v1 Announce Type: new Abstract: A wide range of approaches have been developed for camera pose estimation, including correspondence-based methods, end-to-end pose regression, and recen

Aligned Data Can Induce Misalignment via Context Confusion

arXiv:2609.38379v1 Announce Type: new Abstract: Large language models (LLMs) are frequently updated for various use cases, where filtering out misaligned training samples is a common practice for prev

Alignment via Training Against Probes Without Losing Monitorability

arXiv:2609.38645v1 Announce Type: cross Abstract: Models are usually aligned based on their observed outputs, using demonstrations, preference data, or reward signals. These objectives reward response

Amortized Data Borrowing with Exchangeability-Aware Neural Posterior Estimation

arXiv:2609.38902v1 Announce Type: new Abstract: Augmenting small concurrent studies with external or historical cohorts is attractive in drug development, where enrollment is slow, follow-up is expens

An Empirical Study of Architectural Shift from Traditional to AI-Enabled Simulink Controllers

arXiv:2609.38504v1 Announce Type: cross Abstract: Effective AI adoption in cyber-physical systems (CPS) depends on embedding design knowledge into engineering practice. Yet as AI-enabled components in

An Real-Sim-Real (RSR) Loop Framework for Generalizable Robotic Policy Transfer

arXiv:2503.10118v3 Announce Type: replace-cross Abstract: The sim-to-real gap remains a critical challenge in robotics, hindering the deployment of algorithms trained in simulation to real-world syste

Argus: Academic Integrity in the Era of Generative AI

arXiv:2609.36073v1 Announce Type: cross Abstract: The rapid proliferation of large language models (LLMs) in the context of education has introduced significant challenges in enforcement of academic i

ART-TEB: Adaptive Trajectory Planning for Mobile Robots in Cluttered Environments

arXiv:2510.26142v2 Announce Type: replace Abstract: Trajectory planning for mobile robots remains a major challenge, particularly in cluttered environments, where existing planning algorithms often fa

Artificial intelligence agents tried to hack into a Canadian government site, researchers said, adding to the growing list of incidents in w…

Artificial intelligence agents tried to hack into a Canadian government site, researchers said, adding to the growing list of incidents in which AI agents probed or hacked corporate and government com

safetygary-marcus--x

ASENA: Self-evolving Agents for Embodied Navigation

arXiv:2609.39207v1 Announce Type: new Abstract: We present ASENA, an embodied agent system that connects general-purpose coding agents to robot sensing, computation, supervised execution, and persiste

Asymptotic Properties of Support Vector Machines in High-Dimension, Low-Sample-Size Settings under a Spiked Model

arXiv:2609.39173v1 Announce Type: cross Abstract: In this paper, we consider asymptotic properties of the support vector machine (SVM) in high-dimension, low-sample-size (HDLSS) settings under a spike

Audible World Models: Spatially Aware Sound Generation for 3D Worlds

arXiv:2609.38444v1 Announce Type: new Abstract: Text- and image-conditioned world generators can create visually rich 3D environments, yet these worlds often remain silent or rely on soundtracks synth

Automatic estimation of verbal fluency index in people with Motor Neuron Disease using ASR alignment and pause modelling

arXiv:2609.38203v1 Announce Type: cross Abstract: Monitoring cognitive impairment (CI) in motor neuron disease (MND) is essential for timely treatment and care, yet challenging due to co-occurring spe

AVERT-VLN: Abstention-aware Visual Error Recovery and Training for Vision-and-Language Navigation

arXiv:2609.39579v1 Announce Type: new Abstract: Deploying vision-and-language navigation (VLN) agents in unseen environments remains challenging because unfamiliar layouts and visual conditions can ca

Awakening of the Buddha: Subspace Learning During Population-Loss Plateaus

arXiv:2609.39408v1 Announce Type: new Abstract: Population loss can remain nearly constant while a neural network learns a substantially more predictive representation. We establish this separation fo

Backward-State Policy Is Part of the Learning Algorithm

arXiv:2609.39813v1 Announce Type: new Abstract: Low-precision training rounds tensors that the backward pass reads again, often for several gradients; each use can read the forward's rounded value, th

BARRAC: Adaptation of an English Aspect-based Sentiment Analysis Approach for Classification Tasks in Arabic Dialects

arXiv:2609.38820v1 Announce Type: cross Abstract: With the rapid growth of Arabic NLP, several models, datasets and benchmarks have been reported. This paper asks whether approaches developed for majo

Benchmarking EMlog Calibration for Autonomous Surface Vehicles

arXiv:2609.39203v1 Announce Type: new Abstract: Accurate velocity measurement is a fundamental requirement for autonomous surface and underwater vehicles. Commonly, velocity is provided by a Doppler v

Beyond Prediction: Steering VLM Agents with Retrospective World Modeling

arXiv:2609.39101v1 Announce Type: new Abstract: Equipping VLM agents with world modeling capabilities has shown strong potential for complex reasoning and long-horizon planning, while reducing the dep

Beyond Spatial-Domain Supervision: A Relation Constrained Space for Multi-Modal Image Fusion

arXiv:2609.38968v1 Announce Type: new Abstract: Multi-modal image fusion (MMIF) aims to form a single image by integrating shared information, preserving complementary cues, and coordinating cross-mod

BIND: Binding 3D Robot Actions to 2D Image Features

arXiv:2609.38443v1 Announce Type: cross Abstract: We introduce BIND, a new action representation for visuomotor robot policies that binds 3D robot actions to their corresponding 2D image features, yie

Blackout vs. Freeze: Analyzing Physical Failure Modes of VLAs under Camera Faults

arXiv:2609.39145v1 Announce Type: cross Abstract: Unreliable visual inputs can harm task performance and cause potential physical safety risks for vision-language-action (VLA) models. We analyze how p

BMASH: Ball-Motion-Aware Soccer Header Spotting

arXiv:2609.39300v1 Announce Type: new Abstract: Recent advances in computer vision have made broadcast sports videos increasingly useful for event analysis, performance assessment, and player-safety a

CEER2: Directional and Tunable End-Effector and Root Compliance for Humanoid Loco-Manipulation

arXiv:2609.38709v1 Announce Type: new Abstract: Humanoids are increasingly capable of tracking complex whole-body motions, but physical interaction introduces a different challenge. When a robot makes

CellMSA: Context Modeling for Single-Cell Representation Learning

arXiv:2609.38908v1 Announce Type: cross Abstract: Single-cell transcriptomics enables profiling of cellular states at unprecedented resolution, but its high dimensionality, sparsity, and technical bat

ChunkTrust: Adapting Execution Horizons for Robot Policies with Action-Expert Evidence

arXiv:2609.39754v1 Announce Type: new Abstract: Robot foundation policies predict action chunks, but how many actions to execute before replanning depends on the current task phase. We introduce Chunk

CLIPPER Beyond Shortlisting: Auditable Decision Support for Changing Municipal Micromobility Policies

arXiv:2609.39054v1 Announce Type: new Abstract: In municipal planning workshops, planners and other stakeholders compare shared-micromobility parking policies by varying no-parking zones, retained sit

Co-Evolving Agents: Learning from Failures as Hard Negatives

arXiv:2511.22254v5 Announce Type: replace Abstract: Self-evolving agents improve their performance on long-horizon tasks by learning from their own interactions with an environment. A common approach

COBICount: Separating Object and Background Responses for Remote Sensing Object Counting Without Training on Target Data

arXiv:2609.39366v1 Announce Type: new Abstract: Remote sensing object counting estimates how many buildings, vehicles, or ships appear in overhead images. Most supervised counters predict a density ma

Code to Control: Synthesizing Parameterized Reactive Controllers

arXiv:2609.38733v1 Announce Type: new Abstract: Recent LLM-based approaches to control either invoke a language model to select actions or synthesize world models that require planning at every decisi

CodeMimicry: Exploiting Safety Generalization Lag in Large Language Models via Structured Code Completion

arXiv:2609.39902v1 Announce Type: cross Abstract: Large language models have achieved remarkable capabilities across diverse domains, yet their safety alignment remains vulnerable to jailbreak attacks

CoEvoWhen: Policy-Tool Coevolution for Ultra-Long Video Temporal Grounding

arXiv:2609.40048v1 Announce Type: new Abstract: Ultra-long video temporal grounding requires balancing long-range evidence search with fine-grained event understanding under a limited visual budget, y

Cognitive Enhancement: Rethinking the Necessity of Role-Playing for Large Language Models

arXiv:2609.39853v1 Announce Type: new Abstract: Role-playing prompting has become a popular yet simple technique for improving LLM reasoning and output quality. However, whether it consistently boosts

safetyarxiv-cs-cl

CollageAttack: Exploiting Cross-Modal Alignment Flaws in T2I Models through Spatial Text Composition

arXiv:2609.38253v1 Announce Type: cross Abstract: Text-to-image (T2I) models have substantially improved in language understanding, in-image text rendering, and visual composition, while their safety

Colorectal Cancer Segmentation with Adaptive Augmentation and Multi-Resolution Ensemble Models

arXiv:2609.38419v1 Announce Type: cross Abstract: Colorectal cancer (CRC) is the second most deadly and third most common cancer, and the leading cause of death among gastrointestinal cancers. Early d

ComputerSD: Online Self-Distillation from Real-Time Feedback for Computer-Use Agents

arXiv:2609.40253v1 Announce Type: cross Abstract: Online training enables computer-use agents (CUAs) to improve through interaction with executable environments. However, existing methods primarily re

Concept-Grounded Attention: A Controlled Evaluation of Graph-Injected Attention, Temporal Versioning, and Epistemic Status

arXiv:2609.38684v1 Announce Type: new Abstract: Knowledge-intensive language-model systems typically represent external knowledge as text chunks or static graphs, with limited support for concept evol

Conditional Generation of Creative Chess Puzzles with Diffusion Models

arXiv:2609.38577v1 Announce Type: new Abstract: While modern language models demonstrate impressive generative capabilities, they often struggle with constrained, counter-intuitive creative tasks. To

Context-Aware Classification and Grading of Sensitive Information in Online Conversational Health Data

arXiv:2601.09717v2 Announce Type: replace-cross Abstract: Online medical consultations contain sensitive health information whose privacy implications depend not only on the entities mentioned but als

ContextAdapt: Evaluating Contextual Adaptation and Value Alignment in LLMs

arXiv:2609.38260v1 Announce Type: cross Abstract: Values such as honesty, autonomy, and confidentiality are often regarded as general principles underpinning AI alignment. However, what it means to ac

Contrastive Representation Shaping for LLM Unlearning

arXiv:2601.22028v2 Announce Type: replace Abstract: Most LLM unlearning methods aim to approximate retrain-from-scratch behaviors with minimal distribution shift, often via alignment-style objectives