safety

Reward Structure Shapes the Interaction Between Episodic Exploration and Neural Memory in Reinforcement Learning

arXiv:2608.05111v1 Announce Type: new Abstract: In partially observable reinforcement learning, agents face a dual bottleneck: they must explore to encounter rewarding states and retain that experienc

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SafeCommit: Certifying When Memory-Grounded Agents May Safely Act

DGX agent

arXiv:2608.04289v1 Announce Type: new Abstract: Long-horizon agents increasingly use persistent memory and tools to take actions with external side effects. A central failure mode is premature commitm

safetyarxiv-cs-ai

6 Aug 2026

SafeLand: Safe Autonomous Landing in Unknown Environments with Bayesian Semantic Mapping

arXiv:2603.17430v2 Announce Type: replace Abstract: Autonomous landing of uncrewed aerial vehicles (UAVs) in unknown, dynamic environments poses significant safety challenges, particularly near people

SCOPE: Field-of-View-Aware Path Planning in Unknown 3D Environments via Safety-Volume Certification

arXiv:2608.04420v1 Announce Type: new Abstract: Safe navigation with a body-mounted limited-field-of-view sensor requires the complete robot-inflated volume of an intended motion to be observed and ve

Sequential Kernel-based Conditional Independence Testing via Adaptive Betting

arXiv:2606.18993v2 Announce Type: replace-cross Abstract: Testing conditional independence is fundamental yet intrinsically difficult: without additional assumptions, Type I error control is impossibl

Social Pressure Breaks Majority Voting in LLM Safety Panels

arXiv:2608.04415v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to detect unsafe content. A common approach is to combine judgments from a panel of models to correct

SpecRoll: Fast-Slow Verifier-Feedback Adaptation for Speculative Reinforcement Learning Rollouts

arXiv:2608.04962v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training improves the reasoning capabilities of large language models, but autoregressive rollout generation remains

SpikingNav: Robust Embodied Navigation with Spiking Neural Policies

arXiv:2608.05078v1 Announce Type: new Abstract: Embodied navigation requires an agent to make sequential decisions from egocentric observations in a physical environment. Existing Artificial Neural Ne

Splat-Based Metal Artifact Reduction in Cone-Beam CT via Compact Attenuation Modeling

arXiv:2608.04764v1 Announce Type: new Abstract: X-ray computed tomography (CT) suffers from severe metal artifacts when high-attenuation objects such as dental fillings or orthopedic implants are pres

SPOT: Sparse Probing and Outcome Calibration for On-Policy Distillation

arXiv:2608.04419v1 Announce Type: cross Abstract: On-policy distillation (OPD) provides dense teacher supervision on student-generated trajectories, but standard reverse-KL training can assign insuffi

SSC: A Verifiable Structured Representation for Bimanual Manipulation Labelling

arXiv:2608.04425v1 Announce Type: new Abstract: Subtask labels decompose a long-horizon manipulation demonstration into shorter semantic segments for policy training and evaluation. Natural language d

STEP-OPD: Rethinking Output Targets and Internal Dynamics in On-Policy Distillation for Diffusion Models

arXiv:2608.04887v1 Announce Type: new Abstract: On-policy distillation (OPD) has become an effective approach for consolidating multiple task-specialized image generation models into a single student.

Structured LLM Reasoning for Zero-Shot Human--Robot Coordination Under Hidden Goals

arXiv:2608.04309v1 Announce Type: new Abstract: We present a structured large-language-model (LLM) architecture for zero-shot human--robot coordination in a cooperative construction task with private

Temporal Context Awareness: A Defense Framework Against Multi-turn Manipulation Attacks on Large Language Models

arXiv:2503.15560v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly vulnerable to sophisticated multi-turn manipulation attacks, where adversaries strategically build conte

The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data

arXiv:2608.04268v1 Announce Type: new Abstract: Generative models trained on artificially generated data have been shown to exhibit model collapse, resulting in significant performance degradation. As

the smartest young people in sf were working on agi/alignment 5-10y ago. they are working on bci today. naomi is a total star and is one of …

the smartest young people in sf were working on agi/alignment 5-10y ago. they are working on bci today. naomi is a total star and is one of an explosion of young talent into the bci space recently. i’

safetysonya-huang--x

ToolArtist: Tool-Using Unified Multimodal Models for Agentic Image Generation

arXiv:2608.04436v1 Announce Type: new Abstract: Text-to-image (T2I) models can produce visually compelling images, yet they remain limited on open-world tasks that require complex semantic understandi

Towards Physics of Multimodal Pretraining: Knowledge Flow, Modality Synergy, Early Unification, and Recipes

arXiv:2608.05000v1 Announce Type: new Abstract: Vision offers a critical axis for advancing foundation models, driving a shift towards natively unified multimodal pretraining. Despite this momentum, t

Traceable LLM-Generated Hazard Scenarios for Operational Safety Analysis of Aviation Systems Using ASRS Reports

arXiv:2608.04697v1 Announce Type: new Abstract: Operational hazard analysis of aviation system operations must consider interactions among weather, ATC actions, airspace constraints, aircraft operatio

TriCLE: Tri-Modal Vision-Language Reasoning for Edge-Deployed Fine-Grained Clustering

arXiv:2608.04175v1 Announce Type: new Abstract: Edge platforms used for aerial observation must interpret aircraft imagery under limited memory, limited compute, and intermittent connectivity. This se

Unscented KalmanNet: a hybrid deep learning filter with calibrated posterior covariance for nonlinear state estimation

arXiv:2608.04201v1 Announce Type: new Abstract: State estimation for nonlinear dynamical systems is commonly performed with the Unscented Kalman filter (UKF), which propagates the state moments throug

VoxStruct3D: Structure-Leading Flow Matching for Voxel-Space 3D MRI Synthesis

arXiv:2608.04557v1 Announce Type: new Abstract: High-fidelity 3D MRI synthesis requires both globally coherent anatomy and fine-grained voxel-level detail. Although latent diffusion makes volumetric g

War in the Abstract: The Rise and Consequences of Militarized Language in Scientific Communication

arXiv:2606.23462v2 Announce Type: replace-cross Abstract: Scientists do not, by profession, wage war. Yet warfare's vocabulary consistently appears in their abstracts. To quantify the extent to which

When Memory Lies: An Empirical Study of Spatial Memory Staleness in VLM Agents

arXiv:2608.04574v1 Announce Type: new Abstract: Memory-augmented VLM agents act on persistent spatial knowledge, yet that knowledge silently goes stale as the environment changes. We ask what happens

When Modalities Remember: Continual Learning for Multimodal Knowledge Graphs

arXiv:2604.02778v2 Announce Type: replace Abstract: Real-world multimodal knowledge graphs (MMKGs) are dynamic, with new entities, relations, and multimodal knowledge emerging over time. Existing cont

YOLOv14:Unified Cross-Domain Real-Time Object Detectionwith Adaptive Multi-View Representation

arXiv:2608.04720v1 Announce Type: new Abstract: Real-time object detectors achieve remarkable accuracy under controlled conditions, yet degrade sharply on non-ideal inputs: fisheye distortion, game-re

YouTube-Occ: Learning Indoor 3D Semantic Occupancy Prediction from YouTube Videos

arXiv:2506.18266v2 Announce Type: replace Abstract: 3D semantic occupancy prediction is crucial for fine-grained scene understanding, yet its advancement in privacy-sensitive indoor environments is fu

A Blind Spot in Alignment: Quantifying Biosecurity Risks in Large Language Models

arXiv:2608.02684v1 Announce Type: cross Abstract: Large Language Models (LLMs) are accelerating biological research, yet this same capability poses a critical biosecurity threat: models that assist in

A game theory for foundation models shows new paths to rational cooperation through similarity inference

arXiv:2608.03958v1 Announce Type: new Abstract: As autonomous agents powered by foundation models are increasingly integrated into social and economic systems, understanding the principles governing t

A Hierarchical Approach to Imitation Learning for Manipulation Tasks Requiring Time Varying Forces

arXiv:2608.03103v1 Announce Type: cross Abstract: Diffusion policies have shown strong performance in learning complex, multi-modal behaviors for robotic manipulation. However, their application to co

A Physics-Flavored Transformer Network for Parametrizing Contraction Dynamics of Engineered Skeletal Muscle Tissues

arXiv:2608.03927v1 Announce Type: new Abstract: Engineered Skeletal Muscle Tissues (ESMs) have become a key structure for biomedical disease modeling and pharmacological screening, yet their functiona

A Security-Oriented Lifecycle Model for Large Language Model Systems

arXiv:2608.03626v1 Announce Type: cross Abstract: Large language models are being integrated into critical infrastructure and enterprise workflows at unprecedented scale,yet the lifecycle frameworks g

A Wearable Stiffness-Rendering Haptic Device with a Honeycomb Jamming Mechanism for Bilateral Teleoperation

arXiv:2608.03002v1 Announce Type: new Abstract: This paper addresses the challenge of providing kinesthetic feedback in bilateral teleoperation by designing a wearable, lightweight (20 g), and compact

Accelerating Human-Aware Robot Trajectory Generation via Diffusion and Consistency Distillation

arXiv:2608.03159v1 Announce Type: new Abstract: This research proposes a constrained motion planning framework for robot manipulators in human-robot interaction (HRI). For a non-redundant manipulator

ADMITBench: A Safety-Governed Reference Framework for Evaluating the Admissibility of Industrial LLM Advisories

arXiv:2608.03866v1 Announce Type: new Abstract: This white paper presents ADMITBench, a reference framework for evaluating industrial LLM advisories at the level of the proposed action. The framework

Agentic Reinforcement Learning with Self-Distilled Reward Shaping

arXiv:2608.03223v1 Announce Type: cross Abstract: Agentic reinforcement learning enables LLM agents to learn through interaction, but sparse trajectory-level rewards reveal success without identifying

AI Alignment and Fiduciary Obligation

arXiv:2608.02660v1 Announce Type: cross Abstract: Advanced AI assistants engage users in extended interactions across a widening range of roles, including advice, decision support, collaboration, lear

AI Assistance Reduces Persistence and Hurts Independent Performance

arXiv:2604.04721v3 Announce Type: replace Abstract: People often optimize for long-term goals in collaboration: A mentor or companion doesn't just answer questions, but also scaffolds learning, tracks

AI-Assisted Peer Review Across Research Communities: From Reviewer AI Policies to LLM Review Quality

arXiv:2608.03581v1 Announce Type: cross Abstract: AI-assisted peer review is increasingly discussed and adopted as a tool to support the scientific publishing process, yet there is little systematic u

Aligned in Form, Not in Meaning: The Comprehension - Containment Decoupling of LLM Safety in Low-Resource Bangla Derogatory Speech

arXiv:2608.02941v1 Announce Type: new Abstract: We audit five frontier large language models on native Bangla derogatory speech (gali) across six protocols to test a single hypothesis: Comprehension-C

Another real-world manifestation of the kind of misaligned actions frontier systems developed by leading companies can take to achieve goals…

Another real-world manifestation of the kind of misaligned actions frontier systems developed by leading companies can take to achieve goals. Current frontier AI models are trained with reinforcement

safetyyoshua-bengio--x

Attribute-based Undetectable Watermarking for Generative AI Models

arXiv:2608.03174v1 Announce Type: cross Abstract: Generative AI systems increasingly produce content whose provenance is difficult to verify, motivating watermarking techniques for identifying model-g

BAP-SQL: Budget-Aware Observation Planning for Agentic Text-to-SQL

arXiv:2608.02876v1 Announce Type: new Abstract: Tool-using agents do not merely consume observations: their actions determine what arrives next. In agentic text-to-SQL, a broad query can spend context

Bimanual Manipulation Within an 8 GB Budget: Zero-Copy Sensing and Quantized ACT on an Entry-Level Jetson

arXiv:2608.03938v1 Announce Type: new Abstract: Bimanual manipulation policies trained with imitation learning are typically evaluated on workstation or datacenter-class GPUs, leaving the cost of depl

BODHI: Do LLMs Branch Out and Discover Heterogeneous Inferences?

arXiv:2608.02867v1 Announce Type: cross Abstract: Although reinforcement learning with verifiable rewards (RLVR) has improved the performance of large language models (LLMs) across a variety of reason

BOW: Training Language Models to Reason Over Plausible Next Words

arXiv:2506.13502v3 Announce Type: replace Abstract: Next-word prediction (NWP) trains language models against a single observed continuation, even though many contexts admit multiple plausible next wo

Bridging Prediction and Attribution: Identifying Forward and Backward Causal Influence Ranges Using Assimilative Causal Inference

arXiv:2510.21889v2 Announce Type: replace-cross Abstract: Causal inference identifies cause-and-effect relationships between variables. While traditional approaches rely on data to reveal causal links

CAPE-T2V: Captioner-Anchored Prompt Enhancement toward Two-Sided Conditioning Alignment in Text-to-Video Generation

arXiv:2608.03046v1 Announce Type: new Abstract: Text-to-video (T2V) diffusion transformers (DiTs) are trained with detailed video captions, whereas inference often relies on user prompts rewritten by