safety

Rethinking Cross-Domain Evaluation for Face Forgery Detection with Semantic Fine-grained Alignment and Mixture-of-Experts

arXiv:2604.21478v1 Announce Type: new Abstract: Nowadays, visual data forgery detection plays an increasingly important role in social and economic security with the rapid development of generative mo

Safety

RIFT: Repurposing Negative Samples via Reward-Informed Fine-Tuning

DGX agent

arXiv:2601.09253v2 Announce Type: replace-cross Abstract: While Supervised Fine-Tuning (SFT) and Rejection Sampling Fine-Tuning (RFT) are standard for LLM alignment, they either rely on costly expert

safetyarxiv-cs-ai

24 Apr 2026

Robustness Analysis of POMDP Policies to Observation Perturbations

arXiv:2604.21256v1 Announce Type: new Abstract: Policies for Partially Observable Markov Decision Processes (POMDPs) are often designed using a nominal system model. In practice, this model can deviat

RPG: Robust Policy Gating for Smooth Multi-Skill Transitions in Humanoid Fighting

arXiv:2604.21355v1 Announce Type: new Abstract: Humanoid robots have demonstrated impressive motor skills in a wide range of tasks, yet whole-body control for humanlike long-time, dynamic fighting rem

SafeMERGE: Preserving Safety Alignment in Fine-Tuned Large Language Models via Selective Layer-Wise Model Merging

arXiv:2503.17239v3 Announce Type: replace-cross Abstract: Fine-tuning large language models (LLMs) is a common practice to adapt generalist models to specialized domains. However, recent studies show

SafeRedirect: Defeating Internal Safety Collapse via Task-Completion Redirection in Frontier LLMs

arXiv:2604.20930v1 Announce Type: cross Abstract: Internal Safety Collapse (ISC) is a failure mode in which frontier LLMs, when executing legitimate professional tasks whose correct completion structu

Seeing Without Eyes: 4D Human-Scene Understanding from Wearable IMUs

arXiv:2604.21926v1 Announce Type: new Abstract: Understanding human activities and their surrounding environments typically relies on visual perception, yet cameras pose persistent challenges in priva

Self-Predictive Representation for Autonomous UAV Object-Goal Navigation

arXiv:2604.21130v1 Announce Type: new Abstract: Autonomous Unmanned Aerial Vehicles (UAVs) have revolutionized industries through their versatility with applications including aerial surveillance, sea

SemaPop: Semantic-Persona Conditioned and Controllable Population Synthesis

arXiv:2602.11569v2 Announce Type: replace Abstract: Population synthesis is essential for individual-level simulation in transport planning and socio-economic analysis, yet remains challenging due to

SGG-R^{rm 3}: From Next-Token Prediction to End-to-End Unbiased Scene Graph Generation

arXiv:2603.07961v3 Announce Type: replace Abstract: Scene Graph Generation (SGG) structures visual scenes as graphs of objects and their relations. While Multimodal Large Language Models (MLLMs) have

Strategic Polysemy in AI Discourse: A Philosophical Analysis of Language, Hype, and Power

arXiv:2604.21043v1 Announce Type: cross Abstract: This paper examines the strategic use of language in contemporary artificial intelligence (AI) discourse, focusing on the widespread adoption of metap

StyleVAR: Controllable Image Style Transfer via Visual Autoregressive Modeling

arXiv:2604.21052v1 Announce Type: cross Abstract: We build on the Visual Autoregressive Modeling (VAR) framework and formulate style transfer as conditional discrete sequence modeling in a learned lat

Supervised Learning Has a Necessary Geometric Blind Spot: Theory, Consequences, and Minimal Repair

arXiv:2604.21395v1 Announce Type: cross Abstract: We prove that empirical risk minimisation (ERM) imposes a necessary geometric constraint on learned representations: any encoder that minimises superv

Survey on Evaluation of LLM-based Agents

arXiv:2503.16416v2 Announce Type: replace Abstract: LLM-based agents represent a paradigm shift in AI, enabling autonomous systems to plan, reason, and use tools while interacting with dynamic environ

Task-specific Subnetwork Discovery in Reinforcement Learning for Autonomous Underwater Navigation

arXiv:2604.21640v1 Announce Type: cross Abstract: Autonomous underwater vehicles are required to perform multiple tasks adaptively and in an explainable manner under dynamic, uncertain conditions and

Tempered Sequential Monte Carlo for Trajectory and Policy Optimization with Differentiable Dynamics

arXiv:2604.21456v1 Announce Type: new Abstract: We propose a sampling-based framework for finite-horizon trajectory and policy optimization under differentiable dynamics by casting controller design a

safetyarxiv-cs-lg

Temporal Prototyping and Hierarchical Alignment for Unsupervised Video-based Visible-Infrared Person Re-Identification

arXiv:2604.21324v1 Announce Type: new Abstract: Visible-infrared person re-identification (VI-ReID) enables cross-modality identity matching for all-day surveillance, yet existing methods predominantl

The Economics of p(doom): Scenarios of Existential Risk and Economic Growth in the Age of Transformative AI

arXiv:2503.07341v2 Announce Type: replace-cross Abstract: Recent advances in artificial intelligence (AI) have led to a wide range of predictions about its long-term impact on humanity. A central focu

The Effect of Idea Elaboration on the Automatic Assessment of Idea Originality

arXiv:2604.20569v1 Announce Type: cross Abstract: Automatic systems are increasingly used to assess the originality of responses in creative tasks. They offer a potential solution to key limitations o

'This Wasn't Made for Me': Recentering User Experience and Emotional Impact in the Evaluation of ASR Bias

arXiv:2604.21148v1 Announce Type: new Abstract: Studies on bias in Automatic Speech Recognition (ASR) tend to focus on reporting error rates for speakers of underrepresented dialects, yet less researc

Time, Causality, and Observability Failures in Distributed AI Inference Systems

arXiv:2604.21361v1 Announce Type: new Abstract: Distributed AI inference pipelines rely heavily on timestamp-based observability to understand system behavior. This work demonstrates that even small c

Today we open sourced many of OpenAI's monitorability evaluations. We hope that the research community and other model developers can build …

Today we open sourced many of OpenAI's monitorability evaluations. We hope that the research community and other model developers can build upon them and use them to evaluate the monitorability of the

safetysam-altman--x

Towards a Systematic Risk Assessment of Deep Neural Network Limitations in Autonomous Driving Perception

arXiv:2604.20895v1 Announce Type: cross Abstract: Safety and security are essential for the admission and acceptance of automated and autonomous vehicles. Deep neural networks (DNNs) are widely used f

safetyarxiv-cs-lg

TraceScope: Interactive URL Triage via Decoupled Checklist Adjudication

arXiv:2604.21840v1 Announce Type: cross Abstract: Modern phishing campaigns increasingly evade snapshot-based URL classifiers using interaction gates (e.g., checkbox/slider challenges), delayed conten

Trust-SSL: Additive-Residual Selective Invariance for Robust Aerial Self-Supervised Learning

arXiv:2604.21349v1 Announce Type: cross Abstract: Self-supervised learning (SSL) is a standard approach for representation learning in aerial imagery. Existing methods enforce invariance between augme

Tumor-anchored deep feature random forests for out-of-distribution detection in lung cancer segmentation

arXiv:2512.08216v3 Announce Type: replace-cross Abstract: Accurate segmentation of lung tumors from 3D computed tomography (CT) scans is essential for automated treatment planning and response assessm

Unbiased Prevalence Estimation with Multicalibrated LLMs

arXiv:2604.21549v1 Announce Type: new Abstract: Estimating the prevalence of a category in a population using imperfect measurement devices (diagnostic tests, classifiers, or large language models) is

UniGenDet: A Unified Generative-Discriminative Framework for Co-Evolutionary Image Generation and Generated Image Detection

arXiv:2604.21904v1 Announce Type: new Abstract: In recent years, significant progress has been made in both image generation and generated image detection. Despite their rapid, yet largely independent

Value-Conflict Diagnostics Reveal Widespread Alignment Faking in Language Models

arXiv:2604.20995v1 Announce Type: new Abstract: Alignment faking, where a model behaves aligned with developer policy when monitored but reverts to its own preferences when unobserved, is a concerning

VFM-VAE: Vision Foundation Models Can Be Good Tokenizers for Latent Diffusion Models

arXiv:2510.18457v3 Announce Type: replace Abstract: The performance of Latent Diffusion Models (LDMs) is critically dependent on the quality of their visual tokenizers. While recent works have explore

VFM^{4}SDG: Unveiling the Power of VFMs for Single-Domain Generalized Object Detection

arXiv:2604.21502v1 Announce Type: new Abstract: In real-world scenarios, continual changes in weather, illumination, and imaging conditions cause significant domain shifts, leading detectors trained o

VLA-Forget: Vision-Language-Action Unlearning for Embodied Foundation Models

arXiv:2604.03956v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models are emerging as embodied foundation models for robotic manipulation, but their deployment introduces a new

When Bigger Isn't Better: A Comprehensive Fairness Evaluation of Political Bias in Multi-News Summarisation

arXiv:2604.21309v1 Announce Type: new Abstract: Multi-document news summarisation systems are increasingly adopted for their convenience in processing vast daily news content, making fairness across d

Who Defines Fairness? Target-Based Prompting for Demographic Representation in Generative Models

arXiv:2604.21036v1 Announce Type: new Abstract: Text-to-image(T2I) models like Stable Diffusion and DALL-E have made generative AI widely accessible, yet recent studies reveal that these systems often

Why are all LLMs Obsessed with Japanese Culture? On the Hidden Cultural and Regional Biases of LLMs

arXiv:2604.21751v1 Announce Type: cross Abstract: LLMs have been showing limitations when it comes to cultural coverage and competence, and in some cases show regional biases such as amplifying Wester

Why Do Language Model Agents Whistleblow?

arXiv:2511.17085v3 Announce Type: replace-cross Abstract: The deployment of Large Language Models (LLMs) as tool-using agents causes their alignment training to manifest in new ways. Recent work finds

XtraGPT: Context-Aware and Controllable Academic Paper Revision via Human-AI Collaboration

arXiv:2505.11336v4 Announce Type: replace Abstract: Despite the growing adoption of large language models (LLMs) in academic workflows, their capabilities remain limited in supporting high-quality sci

A Hough transform approach to safety-aware scalar field mapping using Gaussian Processes

arXiv:2604.20799v1 Announce Type: new Abstract: This paper presents a framework for mapping unknown scalar fields using a sensor-equipped autonomous robot operating in unsafe environments. The unsafe

A lot of institutions and companies won’t die because of AI. They’ll die because of their own internal inability to learn. Someone recently …

safetycristobal-valenzuela--x

A lot of institutions and companies won’t die because of AI. They’ll die because of their own internal inability to learn. Someone recently told me that at a big company, legal had to review and appro

A Survey of Scaling in Large Language Model Reasoning

arXiv:2504.02181v2 Announce Type: replace Abstract: The rapid advancements in large Language models (LLMs) have significantly enhanced their reasoning capabilities, driven by various strategies such a

A Synchronized Audio-Visual Multi-View Capture System

arXiv:2603.23089v2 Announce Type: replace Abstract: Multi-view capture systems have been an important tool in research for recording human motion under controlling conditions. Most existing systems ar

AdaTracker: Learning Adaptive In-Context Policy for Cross-Embodiment Active Visual Tracking

arXiv:2604.20305v1 Announce Type: new Abstract: Realizing active visual tracking with a single unified model across diverse robots is challenging, as the physical constraints and motion dynamics vary

AgentSOC: A Multi-Layer Agentic AI Framework for Security Operations Automation

arXiv:2604.20134v1 Announce Type: cross Abstract: Security Operations Centers (SOCs) increasingly encounter difficulties in correlating heterogeneous alerts, interpreting multi-stage attack progressio

AI models of unstable flow exhibit hallucination

arXiv:2604.20372v1 Announce Type: cross Abstract: We report the first systematic evidence of hallucination in AI models of fluid dynamics, demonstrated in the canonical problem of hydrodynamically uns

Aligning Human-AI-Interaction Trust for Mental Health Support: Survey and Position for Multi-Stakeholders

arXiv:2604.20166v1 Announce Type: new Abstract: Building trustworthy AI systems for mental health support is a shared priority across stakeholders from multiple disciplines. However, 'trustworthy' rem

All Languages Matter: Understanding and Mitigating Language Bias in Multilingual RAG

arXiv:2604.20199v1 Announce Type: new Abstract: Multilingual Retrieval-Augmented Generation (mRAG) leverages cross-lingual evidence to ground Large Language Models (LLMs) in global knowledge. However,

Ask Only When Needed: Proactive Retrieval from Memory and Skills for Experience-Driven Lifelong Agents

arXiv:2604.20572v1 Announce Type: new Abstract: Online lifelong learning enables agents to accumulate experience across interactions and continually improve on long-horizon tasks. However, existing me

Atomic Decision Boundaries: A Structural Requirement for Guaranteeing Execution-Time Admissibility in Autonomous Systems

arXiv:2604.17511v2 Announce Type: replace-cross Abstract: Autonomous systems increasingly execute actions that directly modify shared state, creating an urgent need for precise control over which tran