Search: “safety”

arXiv:2512.09953v2 Announce Type: replace-cross Abstract: Machine unlearning aims to remove the influence of specific data points from a trained model to satisfy privacy, copyright, and safety require

arXiv:2604.12781v1 Announce Type: new Abstract: Recently, detecting AI-generated images produced by diffusion-based models has attracted increasing attention due to their potential threat to safety. A

FSD v14.3.1 review after 10 drives and many hours, here are my thoughts (it’s a great one) - v14.3.1 feels like a big jump even compared to FSD v14.3, even for “just” a point release build. Everything

arXiv:2604.12994v1 Announce Type: cross Abstract: Logical vulnerabilities in software stem from flaws in program logic rather than memory safety, which can lead to critical security failures. Although

arXiv:2604.12986v1 Announce Type: cross Abstract: Autonomous AI agents are rapidly transitioning from experimental tools to operational infrastructure, with projections that 80% of enterprise applicat

arXiv:2603.12583v2 Announce Type: replace Abstract: In this work, we propose a data-driven framework to design optimal haptic nudge feedback leveraging the learner's estimated skill to address the cha

arXiv:2604.11709v1 Announce Type: new Abstract: Accurate and rapid structural damage assessment (SDA) is crucial for post-disaster management, helping responders prioritise resources, plan rescues, an

arXiv:2604.10290v1 Announce Type: new Abstract: AI is increasingly deployed in multi-agent systems; however, most research considers only the behavior of individual models. We experimentally show that

arXiv:2604.09945v1 Announce Type: cross Abstract: The rapid adoption of large vision-language models (LVLMs) in recent years has been accompanied by growing fairness concerns due to their propensity t

arXiv:2604.05320v2 Announce Type: replace Abstract: Mobile manipulators are increasingly deployed in human-centered environments to perform tasks. While completing such tasks, they should also be able

arXiv:2604.07382v2 Announce Type: replace-cross Abstract: The geometric structure of latent representations in large language models (LLMs) is an active area of research, driven in part by its implica

arXiv:2604.11699v1 Announce Type: cross Abstract: This work aims to improve the generalization of logic-based legal reasoning systems by integrating recent advances in NLP with legal-domain adaptive f

arXiv:2604.09963v1 Announce Type: cross Abstract: Microreboot enables fast recovery by restarting only the failing component, but in modern microservices naive restarts are unsafe: dense dependencies

arXiv:2601.06540v2 Announce Type: replace-cross Abstract: This paper proposes a novel reinforcement learning framework, named Self-Organizing Dual-buffer Adaptive Clustering Experience Replay (SODACER

arXiv:2604.08591v1 Announce Type: cross Abstract: Hallucinations in large ASR models present a critical safety risk. In this work, we propose the extit{Spectral Sensitivity Theorem}, which predicts a

arXiv:2604.09326v1 Announce Type: cross Abstract: Ensuring safety and reliability in human-robot interaction (HRI) requires the timely detection of unexpected events that could lead to system failures

arXiv:2604.08815v1 Announce Type: new Abstract: Medical vision-language models (VLMs) show strong performance on radiology tasks but often produce fluent yet weakly grounded conclusions due to over-re

arXiv:2508.04691v2 Announce Type: replace-cross Abstract: As humans move toward collaborating with coordinated robot teams, understanding how these teams coordinate and fail is essential for building

arXiv:2604.06210v2 Announce Type: cross Abstract: As LLMs are globally deployed, aligning their cultural value orientations is critical for safety and user engagement. However, existing benchmarks fac

arXiv:2604.08292v1 Announce Type: new Abstract: The autonomous operation of tracked mobile manipulators in rescue missions requires not only ensuring the reachability and safety of robot motion but al

arXiv:2604.07378v1 Announce Type: new Abstract: Autonomous vehicles in interactive traffic environments are often limited by the scarcity of safety-critical tail events in static datasets, which biase

arXiv:2604.07392v1 Announce Type: cross Abstract: Autonomous agents operating in dynamic and safety-critical environments require decision-making frameworks that are both computationally efficient and

arXiv:2604.07577v1 Announce Type: new Abstract: Reliable monitoring of surgical instrument exchanges is essential for maintaining procedural efficiency and patient safety in the operating room. Automa

The OpenAI Academy page on 'Responsible and Safe Use of AI' is a guidance resource focused on best practices for using ChatGPT responsibly in professional and personal settings. It emphasizes that ...

Read The Story of Civilization by Durant “But the curse of every ancient civilization was that its men in the end became unable to fight. Materialism, luxury, safety, even sometimes an almost modern s

link to @HeidyKhlaaf’s sharp analysis: As someone who has audited dozens of safety-critical systems, built static analysis tools, and used most formal verification and security tools, here are some re

arXiv:2608.11480v1 Announce Type: cross Abstract: Hamilton-Jacobi (HJ) reachability provides a mathematically rigorous framework for safe control of dynamical systems, but its practical application is

arXiv:2608.12198v1 Announce Type: cross Abstract: Recent research in machine and deep learning has shown the potential of learningbased motion planning approaches to improve the driving behavior of au

arXiv:2608.10196v1 Announce Type: cross Abstract: Program evolution can measure whether a mutation helped, but it rarely controls how far the mutation moves in behavior space. Syntactic edit size is a

arXiv:2608.10393v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong capabilities in controlling robots across diverse manipulation tasks. However, their adversarial r

arXiv:2608.11181v1 Announce Type: cross Abstract: When a probabilistic predictor answers many conditional-probability queries, are its answers self-consistent, and can this be verified in polynomial t

arXiv:2608.10635v1 Announce Type: cross Abstract: Medical Vision-Language Models (Med-VLMs) excel at verbalizing visual content, yet precise visual perception, segmentation, and grounding remain chall

arXiv:2608.10405v1 Announce Type: cross Abstract: Many studies have shown that specially crafted inputs can induce large language models (LLMs) to generate excessively long outputs, resulting in signi

arXiv:2608.10590v1 Announce Type: new Abstract: Vision Transformers (ViTs) are widely believed to require more labeled data than CNNs for industrial dense prediction. Through controlled experiments on

arXiv:2608.09967v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) agents achieve strong performance in complex environments, yet their decision-making processes remain difficult to int

arXiv:2608.10153v1 Announce Type: new Abstract: Enterprises are deploying autonomous AI agents faster than they can govern them, and prevailing approaches stretch a single discipline, typically DevSec

arXiv:2603.20907v5 Announce Type: replace Abstract: As users increasingly turn to LLMs for practical and personal advice, they become vulnerable to subtle steering toward hidden incentives misaligned

arXiv:2608.10976v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models can connect scene understanding, semantic reasoning, and trajectory generation for autonomous driving. However, verb

arXiv:2608.09142v1 Announce Type: new Abstract: Treatment planning in precision oncology requires synthesizing heterogeneous patient information with rapidly evolving clinical guidelines to ensure gui

arXiv:2608.01043v2 Announce Type: replace-cross Abstract: We report a counter-intuitive interaction between image inputs and existing black-box defenses on Vision--Language Models (VLMs): pairing an e

arXiv:2608.08941v1 Announce Type: cross Abstract: Operational Design Domain (ODD) specifications describe where an automated driving system (ADS) is permitted to operate, but they do not prescribe wha

arXiv:2608.08623v1 Announce Type: new Abstract: In Reinforcement Learning with Verifiable Rewards (RLVR) frameworks for mathematical reasoning tasks, floating-point results are typically evaluated usi

arXiv:2608.09928v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) exhibit strong visual understanding, yet the internal features that cause these behaviors remain difficult to

Securing infrastructure and services against a future cryptographically-relevant quantum computer has been a goal for Google for a decade, and we’ve dedicated ourselves to help developers by advancing

arXiv:2608.08453v1 Announce Type: new Abstract: Under the current standard, Agent Skills are SKILL.md files that combine instructions with supporting resources, enabling Large Language Model (LLM) age

arXiv:2608.06727v1 Announce Type: new Abstract: Transformer models for high-dimensional omics analysis process thousands of genes or pathways, although only a subset requires deep computation. Mixture