Search: “safety”

Reinforcement Learning Inspired Black-box Adversarial Attacks for Computer Vision

arXiv:2609.24249v1 Announce Type: cross Abstract: Neural networks, both convolution or transformer based, are essential for modern computer vision systems. However, they are vulnerable to small pertur

safetyarxiv-cs-cv

22 Sept 2026

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Seeing Through Conflicts: Improving Instruction Hierarchy Alignment in Vision-Language Models

DGX agent

arXiv:2609.22234v1 Announce Type: new Abstract: Instruction hierarchy (IH) alignment teaches language models to prioritize higher-level instructions when inputs conflict. While studied primarily in te

safetyarxiv-cs-cl

22 Sept 2026

Transformer-Based Warm-Starting for Feasible and Optimal Terminal Approach to Tumbling Objects with Space Manipulators

arXiv:2606.17317v2 Announce Type: replace Abstract: Autonomous capture of a tumbling object with a space manipulator requires trajectory generation under real-time onboard constraints. However, couple

22 Sept 2026

What Can a Recurrent State Safely Forget?

arXiv:2609.23366v1 Announce Type: new Abstract: Recurrent models must preserve information that changes future behavior while suppressing hidden-state error. These objectives conflict: contraction imp

22 Sept 2026

AirSplan: Risk-Aware Motion Planning for Quadrotors in Cluttered 3D Gaussian Splats

arXiv:2609.21226v1 Announce Type: new Abstract: Quadrotors are increasingly deployed in applications such as agriculture, infrastructure inspection, and maintenance. In each of these applications, the

CASCADE Against Jailbreaks: Combination Across Stages with Controlled Attack-Defense Evaluation

arXiv:2609.21793v1 Announce Type: cross Abstract: Defenses against jailbreak attacks on Large Language Models (LLMs) operate at different pipeline stages, such as input modification or output guard, b

Clinician-Grounded Quality Assurance for AI-Assisted Psychiatric Intake

arXiv:2609.21149v1 Announce Type: new Abstract: Before patients can use AI-assisted psychiatric intake systems, health systems need practical ways to routinely evaluate these tools against their clini

CounterPlay: Counterfactual Post-Training for Self-Play Driving Policies

arXiv:2609.21617v1 Announce Type: new Abstract: Self-play in high-throughput simulators yields driving policies with robust closed-loop performance, but improvement per unit of simulation diminishes a

Efficient Bayes-Adaptive Reinforcement Learning with Temporal Logic Specifications

arXiv:2609.20954v1 Announce Type: new Abstract: We present a novel end-to-end model-based Reinforcement Learning (RL) algorithm for efficient policy synthesis under given Linear Temporal Logic (LTL) s

Offline Constrained RLHF with Multiple Preference Oracles

arXiv:2604.00200v2 Announce Type: replace Abstract: We study offline constrained reinforcement learning from human feedback with multiple preference oracles. Motivated by applications that trade off p

On the Limits of Maximal Coding Rate Reduction for Out-of-Distribution Generalisation

arXiv:2609.21001v1 Announce Type: new Abstract: Substantial efforts have been devoted to making deep learning objectives, representations, and architectures interpretable, with the goal of improving t

OverThink: Slowdown Attacks on Reasoning LLMs

arXiv:2502.02542v5 Announce Type: replace Abstract: A reasoning language model (RLM) generates costly reasoning tokens, often hidden from the users, that help it excel at many tasks. Our Overthink att

Robotic Multiphase Interaction: Manipulating Coupled Liquid and Solid Dynamics with a World Model

arXiv:2609.21448v1 Announce Type: new Abstract: This work presents extit{Robotic Multiphase Interaction (RMI)}, a setting in which liquid enters a porous material and interacts mechanically with its d

ServeGuard: Verifiable, Bounded-Residual Confinement of Operator-Invisible Channels Without Revealing the Certified Read Factor

arXiv:2609.21515v1 Announce Type: cross Abstract: Third-party adapters for open-weight language models ship as opaque weight matrices; a recipient cannot check whether an adapter hides a backdoor with

Stochastic Neural Signed Swept Volume for Real-time Chance-Constrained Trajectory Optimization

arXiv:2609.21211v1 Announce Type: new Abstract: Collision-free motion planning requires reliable collision models from sensed environments and validation of states along a continuous trajectory. To ma

VIRGA: Virtual-Agent-Intermediated Riemannian Geometry for Active-Sensing Air-Ground Coordination

arXiv:2609.21883v1 Announce Type: new Abstract: Air-ground autonomy becomes harder when the unmanned aerial vehicle (UAV) must remain observable by a gimbal light detection and ranging (LiDAR) mounted

An Open Letter to OpenAI: Please Don’t Eliminate Custom GPTs Until You Have a REAL Replacement

OpenAI’s decision to retire custom GPTs appears to rest on the assumption that Plugins, Skills, Projects, Apps, and Workspace Agents collectively replace their functionality. For many Small and Medium

safetyr-chatgpt

20 Sept 2026

Over the course of 85 days this spring and summer, the course of AI policy under Trump was completed altered. We set out to understand the t…

Over the course of 85 days this spring and summer, the course of AI policy under Trump was completed altered. We set out to understand the thinking behind those events, beginning with the arrival of A

safetygary-marcus--x

20 Sept 2026

A few thoughts on this: 1) If you’ve only seen clips of this interview, I’d encourage you to watch the full podcast. I push back on plenty o…

A few thoughts on this: 1) If you’ve only seen clips of this interview, I’d encourage you to watch the full podcast. I push back on plenty of AI hype in it. 2) As I said in the podcast, this example i

safetyswyx--x

A Noise Optimum in Rehearsal-Free Continual Learning: Isolation, Mechanism, and Scope

arXiv:2609.20162v1 Announce Type: new Abstract: Injecting stochastic noise into a consolidation rule can improve a network's retention of earlier tasks up to an optimal level, then degrade it -- an in

AntiGrounding: Executable Robot Trajectories as Visual Prompts for VLM-Guided Manipulation

arXiv:2506.12374v3 Announce Type: replace-cross Abstract: Natural-language manipulation instructions specify the task goal but leave the underlying robot trajectory unspecified. We present AntiGroundi

Behavioral Coherence: A Method for Sensitive-Domain LLM Evaluation

arXiv:2512.13142v5 Announce Type: replace Abstract: People use LLMs for reproductive-health questions, including abortion-related support. A response can sound supportive while answers reinforce harmf

CoreSense: Traceable Failure Recall and Conflict-Aware Belief Gating for Auditable Robot Decisions

arXiv:2609.19512v1 Announce Type: cross Abstract: Robots can recall prior failures without knowing whether recalled evidence remains valid, conflicts with current observations, or is sufficient to gui

Custom PX4 firmware for autonomous hybrid aerial-marine missions

arXiv:2609.20691v1 Announce Type: new Abstract: Mapping and monitoring aquatic environments can benefit from hybrid aerial-amphibious drones able to combine flight and water-surface navigation within

HerHealthEval: Evaluating Multilingual and Register-Sensitive Understanding of Women's Health Communication

arXiv:2609.20684v1 Announce Type: new Abstract: Large language models are increasingly used in healthcare communication, yet most evaluations emphasize response quality while assuming that the user's

Integrated Guidance and Control of a Mother-Child UAV-UGV System for Cooperative Missions

arXiv:2609.20540v1 Announce Type: new Abstract: Autonomous recovery of a small multirotor onto a hovering multirotor carrier differs from recovery onto ground or shipborne platforms because the recove

OPTED: On-Policy Fine-Tuning for End-to-End Driving using a Render-Free Teacher

arXiv:2609.20756v1 Announce Type: cross Abstract: As scaling pre-training data alone yields diminishing returns, post-training is becoming increasingly important across physical AI domains such as aut

safetyarxiv-cs-cv

Reproducibility is not construct validity: LLM measurement of institutionally situated communication

arXiv:2609.19866v1 Announce Type: new Abstract: High annotation reproducibility does not necessarily imply that an LLM-inferred measure captures the construct it is intended to measure. We test this d

Robotic Video World Models: A Survey of Applications, Research Challenges, Future Directions

arXiv:2601.07823v2 Announce Type: replace-cross Abstract: Video world models have emerged as promising candidates for high-fidelity world models, offering the potential to synthesize high-quality vide

RTK-Vision PPO for Autonomous Micro UAV Recovery on an Airborne Carrier

arXiv:2609.20629v1 Announce Type: new Abstract: Autonomous recovery of a micro unmanned aerial vehicle (UAV) onto a moving airborne carrier enables reusable deploy-mission-recover operation, but coupl

SGM: A Statistical Godel Machine for Risk-Controlled Recursive Self-Modification

arXiv:2510.10232v2 Announce Type: replace-cross Abstract: Recursive self-modification is increasingly central in AutoML, neural architecture search, and adaptive optimization, yet no existing framewor

VLN on the Fly: An Onboard Vision-Language Navigation Stack for Aerial Robots

arXiv:2609.20191v1 Announce Type: cross Abstract: Running vision-language navigation fully onboard an aerial robot is hard, since grounding, planning, and control must share limited compute and a sing

Xeno-Interpretability: Investigating the Alien Minds of LLMs

arXiv:2609.20408v1 Announce Type: cross Abstract: Large language models are usually interpreted through concepts that humans already possess: truthfulness, refusal, deception, personality, harmfulness

'Your Robot Was Trained on a Lie': Collision Mesh Poisoning Attacks on Robotic Manipulation

arXiv:2609.18122v1 Announce Type: cross Abstract: Learning-enabled robotic manipulation increasingly relies on robot simulators for policy training and evaluation before real-world deployment. Inside

A Comprehensive Review of Generative Physical Artificial Intelligence

arXiv:2609.18111v1 Announce Type: cross Abstract: The integration of large-scale foundation models with physical embodiments has led to significant advancements in robotics known as Generative Physica

Autonomy in Check: Governor-Mediated Adaptive Security at the Edge

arXiv:2609.18338v1 Announce Type: cross Abstract: Adaptive security at the network edge increasingly relies on automated planners, including rule-based controllers, learned policies, and LLM-assisted

DyMT-ESB: Dynamic Multi-Turn Evaluation of Social Bias in User-LLM Interactions

arXiv:2609.18649v1 Announce Type: new Abstract: Warning: This paper contains examples of stereotypes and social bias. LLMs are increasingly used in interactive settings by the general public, making t

EmboAlign: Aligning Video Generation with Compositional Constraints for Zero-Shot Manipulation

arXiv:2603.05757v2 Announce Type: replace Abstract: Video generative models (VGMs) pretrained on large-scale internet data can produce temporally coherent rollout videos that capture rich object dynam

End2Race: An End-to-End Learning Framework for Multi-Vehicle Autonomous Racing

arXiv:2509.16894v2 Announce Type: replace Abstract: Autonomous racing serves as a compelling testbed for advancing autonomous vehicle systems. The 1/10-scale F1Tenth platform is widely adopted for edu

Future of general LLM work (interp/inference/alignment) vs agentic/physical AI (VLA, multimodal) for career [D]

I'm at a crossroads with two grad school options that would take me in somewhat different research directions, and I wanted some general advice on these fields, their growth, and industry alignment. I

safetyr-machinelearning

Hardware-Free Robotics Laboratories in Mixed Reality

arXiv:2609.18434v1 Announce Type: new Abstract: Teaching robotics relies on screen-based simulation, showing robot motion in an abstract coordinate frame rather than at real scale in the learner's own

Indicators of resilience for autonomous control systems

arXiv:2609.18264v1 Announce Type: cross Abstract: As modern societies rely more on autonomous systems to facilitate daily life, assuring their safe operation is paramount. Naturally, there are many te

Label-Confidence-Aware Uncertainty Estimation in Natural Language Generation

arXiv:2412.07255v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) demonstrate remarkable capabilities in generative tasks but pose potential risks due to their tendency to generat

Ultralytics YOLO Evolution: An Overview of YOLO27, YOLO26, YOLO11, YOLOv8, and YOLOv5 Object Detectors for Computer Vision and Pattern Recognition

arXiv:2510.09653v4 Announce Type: replace-cross Abstract: This paper presents a comprehensive overview of the Ultralytics YOLO family, emphasizing architectural evolution, benchmarking, deployment, an

A Systematic Evaluation of Machine Learning Methods for Fault Detection and Line Identification in Electrical Power Grids

arXiv:2609.16744v1 Announce Type: new Abstract: The integration of renewable energy sources into the electrical grid introduces complex challenges in fault detection and coordination of grid recovery

Artificial Intelligence-Enabled Space Robot Operations: Technologies, Challenges and Prospects

arXiv:2609.16880v1 Announce Type: new Abstract: Space robots are increasingly expected to perform long-duration, contact-rich, and multi-stage operations with limited human intervention. Recent advanc

Benchmarking Factual Robustness of LLMs via Multi-conversation Persuasion

arXiv:2609.16777v1 Announce Type: new Abstract: As Large Language Models (LLMs) increasingly serve as primary knowledge retrieval interfaces, their robustness against extit{persuasion attacks}---attem

Driver Behavior Estimation at Signalized Intersections Using a Physics-Constrained Decision-Conditioned Autoregressive Transformer

arXiv:2609.16058v1 Announce Type: cross Abstract: Red-light violations and harsh braking at signalized intersections are major contributors to traffic accidents. This paper analyzes and predicts human