Search: “safety”

SONG: A Photorealistic 3D Gaussian Simulation Platform for Benchmarking Social Navigation

arXiv:2607.25219v1 Announce Type: new Abstract: Social navigation has progressed from simplified 2D environments toward a more general vision-based setting, in which a robot needs to achieve socially

29 Jul 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

A Computational Ethical Framework for Financial Digital Phenotyping for Mental Health

DGX agent

arXiv:2607.24275v1 Announce Type: cross Abstract: Ethical governance of AI-driven systems is often expressed through high-level principles and static documentation, creating a gap between regulatory r

safetyarxiv-cs-ai

28 Jul 2026

Adapter Merging Reactivates Latent Reasoning Traces: A Mechanism Analysis

arXiv:2601.18350v5 Announce Type: replace-cross Abstract: Large language models fine-tuned via a two-stage pipeline (domain adaptation followed by instruction alignment) can exhibit non-trivial interf

ARdena: Scenario-driven control of real-time LLM agents

arXiv:2607.22651v1 Announce Type: new Abstract: Large language models (LLMs) have enabled increasingly capable conversational agents, but reliably controlling their behavior in real-time interactive e

Frustratingly Simple Black-Box Adaptation of Language Models via Logit Bias

arXiv:2607.22837v1 Announce Type: cross Abstract: Many organizations aim to adapt language models for internal use, both to improve performance on domain-specific tasks and to address privacy concerns

How LLM Task-Adaptation Reshapes Alignment: A Multi-dimensional Study of Behavioral and Representational Drift

arXiv:2607.22676v1 Announce Type: new Abstract: Post-training is a key mechanism for adapting large language models to downstream tasks. While prior work suggests that task adaptation can alter a mode

IJCB-AFMFR 2026: Competition on Adapting Foundation Models for Face Recognition Using Synthetic Training Data

arXiv:2607.24422v1 Announce Type: new Abstract: This paper presents a summary of the Competition on Adapting Foundation Models for Face Recognition Using Synthetic Training Data (AFMFR), held at the 2

Position: AI/ML Deepfake Research is Misaligned with AI-Generated Non-Consensual Intimate Imagery (AIG-NCII)

arXiv:2607.18263v2 Announce Type: replace Abstract: AI-generated non-consensual intimate imagery (AIG-NCII) is not adequately addressed in AI/ML literature regarding AI-generated media, commonly refer

RM-Distiller: Exploiting Generative LLM for Reward Model Distillation

arXiv:2601.14032v2 Announce Type: replace Abstract: Reward models (RMs) play a pivotal role in aligning large language models (LLMs) with human preferences. Due to the difficulty of obtaining high-qua

Self-Authored Verification Is Unreliable in Heuristic Self-Improving Agents

arXiv:2607.24300v1 Announce Type: new Abstract: Self-improving agents accumulate capability by repeatedly rewriting procedural policies, controllers, or heuristic rules. They typically rely on self-au

STAIF: A Stage-wise Optimization for Complex Instruction Following

arXiv:2607.22649v1 Announce Type: new Abstract: Following complex instructions with multiple explicit constraints remains a fundamental challenge for large language models (LLMs). Existing alignment m

Tailored untruths: How personalisation challenges LLM safeguards

arXiv:2510.12993v3 Announce Type: replace Abstract: Large Language Models (LLMs) can generate highly persuasive disinformation, yet little is known about how effectively they personalise it across lan

Unequal Trips, Unequal Places: Diagnosing and Mitigating Delay Inequity in Autonomous Vehicle Fleet Coordination

arXiv:2607.24336v1 Announce Type: new Abstract: City-scale autonomous vehicle fleet coordinators are typically optimized for aggregate travel time, yet fleet averages conceal how delay is distributed

White-hat hacking IS the defense to black-hat hacking. The techniques are the same. How does Dario expect companies to do it if their models refuse?

You patch security holes by intentionally finding them. If the models refuse to do it, how can companies protect themselves against rogue AIs, whether they are Chinese or OpenAI/Anthropic themselves?

safetyr-localllama

Why Anthropic's battle is meant to poison the wells of open weight models, in 3 steps.

It doesn't solve any problems. Just a few paragraphs above, he says he fears that authoritarian states (he names China, and possibly others) can use their models to do evil stuff. And surely enough, m

safetyr-localllama

We recognize there are a lot of questions and speculative details circulating related to the Hugging Face incident. This is an unprecedented…

We recognize there are a lot of questions and speculative details circulating related to the Hugging Face incident. This is an unprecedented incident, and we think it marks an important moment for AI

safetyopenai--x

25 Jul 2026

Interaction Dynamics Modeling and Predictive Control for Safe Steerable Catheter--Tissue Interaction

arXiv:2607.20939v1 Announce Type: cross Abstract: Safe steerable catheter control is fundamentally a problem of interaction dynamics: the tip must follow a planned motion, remain compliant against mov

OpenAI and Anthropic are now competing to see who can make the scariest AI for marketing purposes. What could possibly go wrong?

Pedro Domingos noted that OpenAI and Anthropic are competing to develop the scariest AI for marketing, raising concerns about the potential misuse of persuasive machine‑learning models. His comment hi

safetygary-marcus--x

Robust Critics: Defending LLMs Against Multi-Turn Attacks

arXiv:2607.20472v1 Announce Type: new Abstract: When a user asks a language model something harmful, is it a genuine attack or a misunderstood but well-meaning question? This ambiguity is one of the c

Safe and Scalable Multi-Drone Payload Transport via CBF-based Reinforcement Learning with Zero-Shot Sim-to-Real Transfer

arXiv:2607.20665v1 Announce Type: new Abstract: Multi-drone payload transportation has emerged as a promising research paradigm with potential applications in construction, logistics, and disaster res

Formal Foundations for Known Good Reliable Die Screening in Chiplet-Based AI Systems-on-Chip

arXiv:2607.20141v1 Announce Type: cross Abstract: The rapid growth of chiplet-based artificial intelligence systems-on-chip (SoCs) has exposed a fundamental gap in semiconductor test methodology. Exis

23 Jul 2026

No Training, Better Flights: Test-Time Scaled VLMs for UAV Navigation

arXiv:2607.19288v1 Announce Type: new Abstract: Test-time scaling offers a promising method to improve the inference performance of Vision-Language Models (VLMs) without additional training. Existing

23 Jul 2026

OPIUM: Mitigating Steering Externalities and Over-Refusal via Dual Objective Latent Optimization

arXiv:2607.19806v1 Announce Type: cross Abstract: Activation steering provides a lightweight mechanism for controlling large language models at inference time, but steering vectors can have unintended

23 Jul 2026

SSI should open-source an opus-tier model. 1. it nearly closes the us/china gap on the os frontier 2. they don't want to waste compute alloc…

SSI should open-source an opus-tier model. 1. it nearly closes the us/china gap on the os frontier 2. they don't want to waste compute allocation on inference, releasing os will enable continued full

safetyclem-delangue--x

20 Jul 2026

Model Releases

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions

model-releasesarxiv-cs-cv

arXiv:2601.22830v2 Announce Type: replace Abstract: Reliable environmental perception remains one of the main obstacles for safe operation of automated vehicles. Safety of the Intended Functionality (

Model Releases

Ask Before You Diagnose: Safe-Psych, a Sequential Evaluation Benchmark for LLMs in Psychiatry

model-releasesarxiv-cs-ai

arXiv:2607.13036v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for decision support in healthcare, but clinical evidence is often incomplete or evolving. When the

Distributionally Robust and Safe Imitation Learning

arXiv:2607.13436v1 Announce Type: new Abstract: Imitation learning (IL) has achieved remarkable success in complex decision-making tasks. However, its performance is highly sensitive to distribution s

Earthquaker-AI: A Retrieval-Augmented Generation Framework with Rubric-Based Assessment for Primary School Earthquake Education

arXiv:2607.14046v1 Announce Type: new Abstract: This paper presents Earthquaker-AI, a hybrid educational framework building upon a previously implemented educational robotics project by integrating a

Model Releases

Safeguard-Conditioned Uplift: Measuring Utility-Risk Frontiers for Dual-Use Biology Assistants

model-releasesarxiv-cs-ai

arXiv:2607.13039v1 Announce Type: cross Abstract: Safety evaluations for dual-use biology assistants often measure base-model capability, refusal behavior, or jailbreak success. These metrics miss a d

A Neurosymbolic Approach to Natural Language Formalization and Verification

arXiv:2511.09008v2 Announce Type: replace-cross Abstract: Large Language Models perform well at natural language interpretation and reasoning, but their lack of formal correctness guarantees limits th

Can Induced Emotion Bias LLM Behaviors in Sequential Decision Making?

arXiv:2607.12631v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly deployed as autonomous agents in high-stakes domains, understanding contextual factors that may modul

Expert Knowledge-driven Reinforcement Learning for Autonomous Racing via Trajectory Guidance and Dynamics Constraints

arXiv:2603.05842v2 Announce Type: replace Abstract: Reinforcement learning has demonstrated significant potential in the field of autonomous driving. However, it suffers from defects such as training

From Sentiment to Actionable Insights: Public Sentiment Analysis of Advanced Air Mobility

arXiv:2606.20751v2 Announce Type: replace Abstract: Advanced Air Mobility (AAM) is an emerging low-altitude transportation system whose successful deployment depends on both technological progress and

StratMamba: Strategic and Reactive Stream Partitioning for Path-Efficient LiDAR-Based Obstacle Avoidance

arXiv:2607.12370v1 Announce Type: new Abstract: This paper proposes StratMamba, a dual-stream Mamba-based temporal modeling architecture, to more efficiently capture long-horizon temporal dependencies

Alignment Plausibility: A New Standard for Assuring AI in Healthcare

arXiv:2607.07766v1 Announce Type: new Abstract: Large language models (LLMs) have become significant providers of mental health support, yet they remain products of an attention economy whose operatio

10 Jul 2026

Post-Training in End-to-End Autonomous Driving

arXiv:2607.08072v1 Announce Type: new Abstract: End-to-end models that map multimodal inputs directly to future trajectories/maneuvers have emerged as an increasingly prominent research paradigm in au

10 Jul 2026

Securing Autonomous Vehicle Systems via Twin-Aware Federated Reinforcement Learning

arXiv:2607.08137v1 Announce Type: cross Abstract: Federated reinforcement learning (FRL) is crucial for enabling collaborative learning across multiple agents without sharing raw data, thereby enhanci

10 Jul 2026

Online Data Selection Is Implicit Alignment

arXiv:2607.07023v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) is often treated as a capability-adaptation step, while alignment is attributed to later preference optimization or reinfor

9 Jul 2026

Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows in Production

arXiv:2607.07052v1 Announce Type: cross Abstract: AI agents deployed for IT operations are typically permanent cost centers because every execution requires full LLM inference, even for previously sol

9 Jul 2026

Agentic AI for Commercial Insurance Underwriting with Adversarial Self-Critique

arXiv:2602.13213v2 Announce Type: replace Abstract: Commercial insurance underwriting is a labor-intensive process that requires manual review of extensive documentation to assess risk and determine p

8 Jul 2026

Closed-loop vs. Open-loop Kalman Filter Architectures in Airborne Aided Inertial Navigation

arXiv:2607.03338v1 Announce Type: new Abstract: Closed-loop (or feedback) error-state Kalman filters with their relatives and offspring are the state-of-the-art in modern aided inertial navigation res

Directional Curvature from Armijo Backtracking: A Low-Cost Sharpness Probe and a Calibration-Free Learning-Rate Safeguard for Adam

arXiv:2607.03998v1 Announce Type: new Abstract: The local sharpness of the loss, the top Hessian eigenvalue lambda_1, determines the largest stable gradient step, but measuring it normally requires La

Drone delivery is about to be cheaper than cars. But the drone is only 15% of the work to get there. A decade after starting in Rwanda flyin…

Drone delivery is about to be cheaper than cars. But the drone is only 15% of the work to get there. A decade after starting in Rwanda flying blood to one hospital, @zipline has flown 140M+ autonomous

safetysonya-huang--x

Integrating Physics-Informed Neural Networks for Safe Reinforcement Learning in a 1-DoF Helicopter System

arXiv:2607.03125v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) offers powerful control for industrial cyber-physical systems (ICPSs), but its 'black-box' exploration risks violating

Interaction Dynamics for Dexterous Manipulation

arXiv:2606.14606v2 Announce Type: replace Abstract: Dexterous manipulation is fundamentally a problem of interaction dynamics: the hand must track precise finger trajectories, regulate the contact for

NavEYE: Vision-Centered Multi-Sensor Fusion-Based Situational Awareness System for Intelligent Surface Vehicles

arXiv:2607.03915v1 Announce Type: new Abstract: With the rapid development of sensor and artificial intelligence (AI) technologies, intelligent surface vehicles (ISVs) have gained increasing attention

Pretraining Curricula Enable Selective Fine-tuning

arXiv:2607.04846v1 Announce Type: cross Abstract: Transformers follow implicit curricula whereby some tasks are learned before others. However, how explicit pretraining curricula influence learning, g

Safe Inference-Time Alignment via Lagrangian Reward Augmentation

arXiv:2607.02781v1 Announce Type: cross Abstract: Inference-time alignment steers a frozen language model during decoding using auxiliary reward signals, avoiding the cost of repeated weight updates.