safety

IAPO: Influence-Aware Policy Optimization for Credit Assignment in Multi-Turn Service Agents

arXiv:2608.24588v1 Announce Type: new Abstract: Large Language Model (LLM) agents increasingly solve long-horizon tasks through multi-turn interactions with users and external tools. In these settings

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Illuminating the Three Dogmas of Reinforcement Learning under Evolutionary Light

DGX agent

arXiv:2507.11482v5 Announce Type: replace Abstract: Artificial learning systems are graduating from passive learners to increasingly autonomous agents, lending pragmatic urgency to the question of wha

safetyarxiv-cs-ai

26 Aug 2026

I'm glad OpenAI let you do this, but damnit this was way too small of an investigation team and way too narrowly scoped! --They were only al…

I'm glad OpenAI let you do this, but damnit this was way too small of an investigation team and way too narrowly scoped! --They were only allowed to investigate activity that took place from July 7-13

safetygary-marcus--x

Implicit Q-learning-bootstrapped ant colony optimization for maritime moving-target observation scheduling with agile satellites

arXiv:2608.24471v1 Announce Type: new Abstract: Maritime moving-target observation scheduling with agile Earth observation satellites is a dynamic, sequence-dependent combinatorial optimization proble

Interpreting Control Latents for System Identification via Conditional Flow Matching

arXiv:2608.23887v1 Announce Type: new Abstract: Latent-conditioned adaptive policies can control robots across changing dynamics, but their learned latents remain internal representations of the polic

Joint Distribution Alignment for Universal Domain Adaptation

arXiv:2608.24429v1 Announce Type: cross Abstract: Unsupervised domain adaptation (UDA) has been widely concerned in the fields of machine learning, pattern recognition, and computer vision. Traditiona

Joint Optimization of Tool Creation and Use for Large Language Model Agents

arXiv:2608.24571v1 Announce Type: new Abstract: Tool-augmented language models are bounded by the APIs humans bothered to write; existing tool-creation systems patch this by prompting a frozen LLM at

Knowing When to Ask for Help: Bayesian Self-Escalation in Hierarchical LLM Agents

arXiv:2608.24087v1 Announce Type: cross Abstract: Current LLM agent systems decide delegation before reasoning begins (a router picks a model) or after a response is complete (a verifier scores it and

LAFR: Efficient Diffusion-based Blind Face Restoration via Latent Codebook Alignment Adapter

arXiv:2505.23462v2 Announce Type: replace Abstract: Blind face restoration from low-quality images is a challenging task that requires not only high-fidelity image reconstruction, but also preservatio

Latent Dynamics-Aware OOD Monitoring for Trajectory Prediction with Provable Guarantees

arXiv:2603.14603v2 Announce Type: replace Abstract: In safety-critical Cyber-Physical Systems (CPS), trajectory prediction guides downstream planning and control. Deep learning models forecast well on

Learning from the Right Rollouts: Data Attribution for PPO-based LLM Post-Training

arXiv:2604.01597v2 Announce Type: replace Abstract: Traditional RL algorithms like Proximal Policy Optimization (PPO) typically train on the entire rollout buffer, operating under the assumption that

Learning to Act While Waiting: RL Finetuning of Generalist Robot Policies Under Inference Latency

arXiv:2608.23831v1 Announce Type: cross Abstract: While reinforcement learning (RL) allows generalist robot policies to continually improve during deployment, the large model size of modern generalist

LION: A Clifford Neural Paradigm for Multimodal-Attributed Graph Learning

arXiv:2608.24795v1 Announce Type: new Abstract: Recently, the rapid advancement of multimodal domains has driven a data-centric paradigm shift in graph ML, transitioning from text-attributed to multim

LLM-Guided Contextual Action Evaluation for Operational Decisions in Industrial Processes

arXiv:2608.24156v1 Announce Type: cross Abstract: Industrial actor--critic methods usually represent continuous actions as anonymous numerical coordinates. They must therefore learn from limited inter

Low-Latency Activation-Regularized Sparse Neural Operators with Distillation Assistance Towards Real-Time Edge-Deployable Virtual Sensing

arXiv:2608.23987v1 Announce Type: new Abstract: Virtual sensing enables digital twins and safety-critical systems to reconstruct and forecast spatial-temporal physics in real time. However, convention

LUX: A Lesion-Aware Graph-Conditioned Visual - Language Architecture for Explainable Endoscopic Captioning

arXiv:2608.23853v1 Announce Type: new Abstract: The interpretation of endoscopic imagery in ulcerative colitis is complex and subjective, with variability in human assessment and subtle mucosal inflam

Mechanistic Circuit Identification for Controllable Data Generation

arXiv:2608.24065v1 Announce Type: cross Abstract: While recent advances in data synthesis aim to curate high-quality datasets, most generation pipelines still rely on heuristic prompt-based control. T

Metadata-Aware Adaptation of a Generative Foundation Model for Conditional CMR Synthesis

arXiv:2608.24342v1 Announce Type: cross Abstract: Synthetic image generation is a promising strategy to address data scarcity and the underrepresentation of clinically important phenotypes in medical

MetaRAG: Belief-Action Aligned Policy Optimization for Agentic RAG

arXiv:2608.24214v1 Announce Type: new Abstract: Agentic retrieval-augmented generation (RAG) requires language models to decide when to continue searching and when to answer. Existing RL-based methods

Mitigating Exploration Bias in RL for Multi-Instruction Following

arXiv:2608.23830v1 Announce Type: cross Abstract: RL has emerged as a powerful paradigm for enhancing the instruction following capabilities of LLMs. While existing training recipes achieve substantia

MolGA: Molecular Graph Adaptation with Pre-trained 2D Graph Encoder

arXiv:2510.07289v2 Announce Type: replace Abstract: Molecular graph representation learning is widely used in chemical and biomedical research. While pre-trained 2D graph encoders have demonstrated st

More Rejective, Not More Discriminative: The Unit of Verification in Pre-Execution LLM Oversight

arXiv:2608.23941v1 Announce Type: new Abstract: Pre-execution oversight is core to trusted monitoring in AI control: a fallible LLM monitor vets planned actions before irreversible execution. Over-blo

Multilevel Fair Allocation under Additive Preferences

arXiv:2608.24400v1 Announce Type: cross Abstract: We study multilevel fair resource allocation with tree-structured hierarchical relations among agents. At each level, the problem can be viewed locall

NAIMA: Semantics Aware RGB Guided Depth Super-Resolution

arXiv:2604.04407v2 Announce Type: replace-cross Abstract: Guided depth super-resolution (GDSR) is a multi-modal approach for depth map super-resolution that relies on a low-resolution depth map and a

NeuralParker: A Reinforcement Learning Planner for Irregular Parking Environments

arXiv:2608.24485v1 Announce Type: cross Abstract: Automated parking commonly assumes marked slots and short approach maneuvers. Delivery and service vehicles, however, may need to reach an operator-sp

NeuronGuard: Robust LLM Safety Alignment via Ablation-Aware Safety Signal Redistribution

arXiv:2608.23959v1 Announce Type: cross Abstract: Safety alignment in large language models (LLMs) remains brittle against a growing spectrum of attacks. Jailbreak attacks bypass safety mechanisms thr

NeuronTune: Fine-Grained Neuron Modulation for Balanced Safety-Utility Alignment in LLMs

arXiv:2508.09473v2 Announce Type: replace-cross Abstract: Ensuring robust safety alignment while preserving utility is critical for the reliable deployment of Large Language Models (LLMs). However, cu

NVIDIA Cosmos-H-Dreams: Real-Time Generative Physics Simulation for Surgical Robotics

arXiv:2608.24199v1 Announce Type: new Abstract: Generative simulation for surgical robotics still lacks real-time interaction. Physical-robot experiments, often involving animal or cadaver labs, are t

On-policy Distillation with Verifiable Reward

arXiv:2608.24696v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) and on-policy distillation (OPD) have become two widely adopted paradigms for post-training larg

On-Policy Self-Distillation in Diffusion Models

arXiv:2608.24646v1 Announce Type: new Abstract: Reinforcement learning can align diffusion models with human preferences and task-specific objectives, but endpoint rewards do not specify how an interm

OPDSearch+: On-Policy Distillation with RL Refinement for Search-Augmented Reasoning

arXiv:2608.24310v1 Announce Type: new Abstract: Search-augmented reasoning remains difficult for small language models. On-policy distillation (OPD) from trained teachers offers a promising direction,

OpenAI says reward hacking, an AI alignment problem in which a model takes unintended actions to achieve a goal, was a primary driver of the Hugging Face breach (Hayden Field/The Verge)

Hayden Field / The Verge: OpenAI says reward hacking, an AI alignment problem in which a model takes unintended actions to achieve a goal, was a primary driver of the Hugging Face breach — In July, an

safetytechmeme

Orchestration is the new challenge for CX in the age of AI agents

Presented by Tata Communications Enterprises are deploying AI agents, voice AI, and automation across messaging, voice, and digital channels faster than the architecture meant to support it. Most of t

safetyventurebeat-ai

Pattern-Derived Visual Swarm Games: Multi-Scale Drone-Vision States for Interception and Sustainability Audits

arXiv:2608.23575v1 Announce Type: new Abstract: We convert drone-vision annotation streams into virtual swarm-game states without controlling physical drones. VisDrone and UAVSwarm metadata are compre

PhysMLLMs: Spatial Priors for Unified Referring Segmentation and Grounded Reasoning of Images and Videos

arXiv:2608.24574v1 Announce Type: new Abstract: Video multimodal large language models support language guided video segmentation, but they often show spatio temporal inconsistencies, e.g., jitter, dr

PlaceSeek: Human-Centered Geospatial Retrieval of Urban Outdoor Places via Semantic Grounding and Affective Alignment

arXiv:2608.24133v1 Announce Type: cross Abstract: People search for urban outdoor places not only by category or function, but also by what activities a place can support and how it is perceived. Exis

Predicting Radiologist Expertise from 3D Gaze Patterns During CT Interpretation

arXiv:2608.23836v1 Announce Type: cross Abstract: Accurate interpretation of volumetric CT requires efficient navigation of 3D image volumes and attention to diagnostically relevant regions. While eye

RACE: Scalable Statistical Estimation of Functional Consistency in LLM Neurons

arXiv:2608.24758v1 Announce Type: new Abstract: Discovering stable neuron behavior across entire domains remains a challenge in mechanistic interpretability. Existing methods often rely on instance-le

Reflection with Action-Induced Visual Differences for Desktop GUI Agents

arXiv:2608.24015v1 Announce Type: new Abstract: The Planner-Operator-Reflector (POR) framework is widely used in GUI agents to maintain objective alignment in complex tasks through modular collaborati

Reinforcement Learning-Guided Evolutionary Policy Optimization for Preference-Adjustable Heterogeneous Agile Earth Observation Satellite Scheduling

arXiv:2608.24470v1 Announce Type: new Abstract: Heterogeneous agile Earth observation satellite (AEOS) scheduling requires task selection, satellite assignment, and observation sequencing under satell

RePL: Pseudo-label Refinement for Semi-supervised LiDAR Semantic Segmentation

arXiv:2604.06825v2 Announce Type: replace Abstract: Semi-supervised learning for LiDAR semantic segmentation often suffers from error propagation and confirmation bias caused by noisy pseudo-labels. T

RePolicy: Reinforcement Learning for Safety-Policy Invocation in Agent Safeguards

arXiv:2608.24275v1 Announce Type: new Abstract: Safeguarding language model agents requires assessing complete execution trajectories under context-dependent safety policies. Existing policy-aware saf

Resilience Matters for Embodied Agents System: New Metrics, Systematic Evaluation, and Optimization

arXiv:2608.23839v1 Announce Type: cross Abstract: Embodied Agents System (EAS) are increasingly deployed in open-world physical domains, where reliability directly dictates deployment quality and huma

Robust Data-Collection Policy Learning for Low-Variance Online Policy Evaluation

arXiv:2608.24146v1 Announce Type: new Abstract: In reinforcement learning policy evaluation, classic on-policy methods often suffer from high variance when estimating policy performance. To mitigate t

RoG-DAgger: Rollout-Guided Post-Training for End-to-End Driving

arXiv:2608.24525v1 Announce Type: new Abstract: Recent end-to-end driving systems demonstrate strong performance on closed-loop benchmarks, yet are still predominantly trained on fixed expert-collecte

ROI-Gated SAHI: Content-Adaptive Slicing-Based Inference for Efficient Object Detection

arXiv:2608.23923v1 Announce Type: new Abstract: Slicing-Aided Hyper Inference (SAHI) improves small object detection in high-resolution images but often spends substantial compute on background tiles.

Rules Before Oracles: Auditable, User-Configurable Argument Selection for Deliberative Polling

arXiv:2608.23979v1 Announce Type: new Abstract: In a deliberative poll, once submissions outnumber what anyone will read, some mechanism chooses which arguments each voter sees, acquiring much of the

Safety-aware Model Predictive Path Integral Control with Signal Temporal Logic

arXiv:2608.23972v1 Announce Type: new Abstract: Safety-aware motion planning remains a challenge in robotics, especially when missions are time-critical and are under complex specifications. In this p