Search: “safety”

Responsiveness Verification: Will Predictions Change? How Much? How Often?

arXiv:2507.02169v2 Announce Type: replace Abstract: Machine learning models are often used in applications where their inputs change due to routine interactions, strategic manipulation, or noise. In s

17 Aug 2026

Somebody needs to do an internship at the FDA.

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Dr. Catharine Young noted on Twitter that someone should pursue an internship at the U.S. Food & Drug Administration (FDA). On August 16, Polymarket reported that Anthropic CEO Dario Amodei predicted

safetygary-marcus--x

16 Aug 2026

Gradual Code-Switching as Inference-Time Cross-Lingual Representational Alignment for LLMs

arXiv:2510.05678v2 Announce Type: replace-cross Abstract: While large language models (LLMs) have achieved notable progress in multilingual settings, their performance remains uneven across languages

14 Aug 2026

Practice Makes Unsafe: Skill Misevolution in Self-Improving LLM Agents

arXiv:2608.12851v1 Announce Type: new Abstract: Self-improving LLM agents convert successful trajectories into persistent cross-task state. An unsafe success can thereby become reusable policy after i

14 Aug 2026

Forward Trajectory Steering for Hamilton-Jacobi Reachability Analysis

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

13 Aug 2026

Learning-Based Behavior Planning for Automated Driving: Real-World Integration and Deployment

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

13 Aug 2026

ELMER: Evolutionary Language Model that Explores and Refines

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

Hidden in Plain Sight: Diffusion-Based Unrestricted Robotic Attacks on Vision-Language-Action Models

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

How to Verify Consistency of Probabilistic Claims

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

MedUP: Awakening Unified Understanding and Perception in Medical Vision-Language Models

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

Never Stop Speaking: a Denial-of-Service Attack on End-to-End Speech Language Models

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

Rethinking Data Efficiency in Industrial Dense Prediction: Pretraining Coherence, Not Inductive Bias, Determines ViTs Low-Data Advantage

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

SPOTting the Future: Lookahead Explanations for Deep Reinforcement Learning

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

The CASE Framework: A Multi-Disciplinary Control Architecture for Governing Enterprise Agentic AI

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

The Hidden Puppet Master: Predicting Human Belief Change in Manipulative LLM Dialogues

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

safetyarxiv-cs-cl

XCoT-VLA: Executable Chain-of-Thought for Vision-Language-Action Driving

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

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer

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

safetyarxiv-cs-cl

Decoy Images Amplify Caption-Mediated Defenses Against Encoded Jailbreaks

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

From Operational Design Domain to Action: A Systematic Behavioral Taxonomy for Autonomous Driving

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

MedCalc-R1: Knowledge-Guided Reward Framework for Medical Mathematical Reasoning

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

Multimodal Model Diffing for Feature Discovery and Control

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

PQC in Plaintext: Google Cloud’s post-quantum cryptography roadmap

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

safetygoogle-cloud-ai

What Keeps Agent Skills from Being Reusable? Evidence from 138K SKILL.md Files

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

bioMoR: Biology-Guided Mixture-of-Recursions for Effective Genomic Learning

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

10 Aug 2026

From Cheap Fakes to Pure Synthesis: Addressing the New Era of T2V Fake News Videos

arXiv:2608.06732v1 Announce Type: new Abstract: Recent text-to-video (T2V) generation models enable fake news videos to be synthesized from scratch, shifting the threat beyond cheap fakes assembled fr

10 Aug 2026

SoRoMoX: Fast, Differentiable, and Parallelizable Soft Robot Models

arXiv:2608.06650v1 Announce Type: cross Abstract: Reduced-order models based on Cosserat-rod theory are now well established, and modeling theory is no longer the primary bottleneck in soft-robot cont

10 Aug 2026

A System for Train Condition Monitoring and Structural Health Assessment of Rail Vehicles

arXiv:2608.05221v1 Announce Type: new Abstract: The ongoing digitalization of rail systems and the increasing use of artificial intelligence (AI) are fundamentally transforming the design, operation,

7 Aug 2026

DreamGuard: Efficient Runtime Guardrail for LLM Agents via Risk-Aware World Model

arXiv:2608.05695v1 Announce Type: new Abstract: As large language model (LLM) agents increasingly invoke external tools and interact with real-world systems, unsafe actions may cause irreversible cons

7 Aug 2026

Looking in the Mirror: Introspecting Side-Effect Misalignments Induced by Fine-Tuning

arXiv:2608.04347v1 Announce Type: new Abstract: Fine-tuning enables a source model to acquire desired capabilities and behaviors in a target domain while retaining much of its general-purpose competen

6 Aug 2026

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

LatentGuard: Efficient and Inspectable Latent Reasoning for LLM Safeguards

arXiv:2608.03838v1 Announce Type: new Abstract: Reasoning-based guard models improve LLM safeguards, but decoding explicit rationales for every interaction makes them costly to deploy. Although latent

Poisoning Prompt-Guided Sampling in Video Large Language Models

arXiv:2509.20851v2 Announce Type: replace Abstract: Video Large Language Models (VideoLLMs) are increasingly deployed as automated moderators on user-generated video platforms, where a few unwatched s

PULSE: An Executable Contract Language for Spatiotemporal Knowledge Graph Engineering

arXiv:2608.02630v1 Announce Type: new Abstract: Knowledge graph engineering often distributes accepted state, observations, constraints, processes, and hypothetical scenarios across artifacts whose co

HapticVLA: Contact-Rich Manipulation via Vision-Language-Action Model without Inference-Time Tactile Sensing

arXiv:2603.15257v2 Announce Type: replace Abstract: Tactile sensing is a crucial capability for Vision-Language-Action (VLA) architectures, as it enables dexterous and safe manipulation in contact-ric

MedPRESS: A Multi-turn Benchmark for Patient-Pressure-Induced Medical Sycophancy in LLMs

arXiv:2608.02520v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for health-related advice. Existing research measures their safety with static questions rather than

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models

model-releasesarxiv-cs-lg

arXiv:2506.07121v2 Announce Type: replace Abstract: Ensuring the safety and robustness of large language models (LLMs) is a fundamental challenge and a critical prerequisite for the responsible deploy

Self-Improving Large Language Models via Progressive Experience Evolution

arXiv:2608.02139v1 Announce Type: new Abstract: Large language models (LLMs) capable of self-improvement require not only effective policy optimization, but also a principled mechanism for transformin

safetyarxiv-cs-cl

When May a Model Replace the Experiment? Audits, Licenses, and the Price of Trust in Surrogate-Driven Design

arXiv:2608.01378v1 Announce Type: new Abstract: Design campaigns in chemistry, materials science, and machine learning share a bottleneck: determining how good a candidate truly is requires an expensi

CAGE: Certified Authorization under Typed-Return Uncertainty for Tool-Using Agents

arXiv:2607.29190v1 Announce Type: new Abstract: Tool-using LLM agents act on typed tool returns, records pairing provenance and categorical fields with numerical values. Runtime permission gates gener

3 Aug 2026

Active Lubrication of Transluminal Medical Instruments

arXiv:2506.07225v2 Announce Type: replace-cross Abstract: Transluminal minimally invasive surgery uses natural orifices and small incisions to access internal anatomical structures, promoting quicker

Ask don't tell: Reducing sycophancy in large language models

arXiv:2602.23971v4 Announce Type: replace-cross Abstract: Sycophancy, the tendency of large language models to favour user-affirming responses over critical engagement, has been identified as an align

Corrigible Assistance in One Round: Pragmatic-Pedagogic Best Response

arXiv:2607.27508v1 Announce Type: new Abstract: Assistance games formalize human-robot collaboration under asymmetric information: the human knows the goal, while the robot must infer it from observat

EmoFeedback^2: Reinforcement of Continuous Emotional Image Generation via LVLM-based Reward and Textual Feedback

arXiv:2511.19982v3 Announce Type: replace Abstract: Continuous emotional image content generation (C-EICG) is emerging rapidly due to its ability to produce images aligned with both user descriptions

FleetScape: A Mixed Reality Sandtable for Spatial Supervision and Control of Scalable Drone Fleets

arXiv:2607.26423v1 Announce Type: cross Abstract: As autonomous drone deployments scale from individual units to coordinated swarms, the human operator's role shifts from direct piloting to high-level

30 Jul 2026

Prosody-driven Jailbreaks in Audio LLMs: A Controlled Study and Mechanistic Analysis

arXiv:2607.26541v1 Announce Type: cross Abstract: Audio-capable foundation models enable end-to-end spoken interaction, but they also introduce safety risks beyond transcript content. It remains uncle

30 Jul 2026

Agentic AI in medicine: architectures, applications, evaluation, and challenges for clinical translation

arXiv:2607.25489v1 Announce Type: new Abstract: Large language models and multimodal foundation models are enabling medical artificial intelligence (AI) systems to move beyond isolated prediction and

29 Jul 2026

Inspect India Evals: An Open Benchmarking Framework for Evaluating Large Language Models in the Indian Linguistic and Cultural Context

arXiv:2607.25375v1 Announce Type: new Abstract: India is a vast nation of over 1.4 billion people, varied by hundreds of diverse and locally specific traditions and cultures and 22 officially recogniz

29 Jul 2026

Shieldstral

arXiv:2607.25857v1 Announce Type: new Abstract: We introduce Shieldstral, a 3B-parameter policy-adaptive multimodal safety classifier that matches or outperforms models nearly 7imes its size on text s