safety

When Safety Geometry Collapses: Fine-Tuning Vulnerabilities in Agentic Guard Models

arXiv:2605.02914v1 Announce Type: new Abstract: A guard model fine-tuned on entirely benign data can lose all safety alignment -- not through adversarial manipulation, but through standard domain spec

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When to Think, When to Speak: Learning Disclosure Policies for LLM Reasoning

DGX agent

arXiv:2605.03314v1 Announce Type: new Abstract: In single-stream autoregressive interfaces, the same tokens both update the model state and constitute an irreversible public commitment. This coupling

safetyarxiv-cs-cl

6 May 2026

Will the Carbon Border Adjustment Mechanism Impact European Electricity Prices? A GNN-Based Network Analysis

arXiv:2605.03304v1 Announce Type: new Abstract: The European Union's Carbon Border Adjustment Mechanism (CBAM) creates a complex challenge for the interconnected European electricity market. Tradition

yep, we are about to live in a world where nobody trusts anything. just like Putin always wanted. congratulations! ps it will suck

yep, we are about to live in a world where nobody trusts anything. just like Putin always wanted. congratulations! ps it will suck @GaryMarcus Or very soon no one will take any photo or video seriousl

Zero-Shot Signal Temporal Logic Planning with Disjunctive Branch Selection in Dynamic Semantic Maps

arXiv:2605.01222v1 Announce Type: new Abstract: Signal Temporal Logic (STL) offers verifiable task specifications and is crucial for safety-critical control. Yet STL planning remains challenging: exac

safetyarxiv-cs-ai

A Deep Learning Model for Battery State Prediction towards Intelligent Energy Management

arXiv:2605.00898v1 Announce Type: cross Abstract: Accurate forecasting of battery health indicators, including remaining capacity and lifetime, is of paramount importance for ensuring the reliability,

A Multi-View Media Profiling Suite: Resources, Evaluation, and Analysis

arXiv:2605.01336v1 Announce Type: new Abstract: News outlets shape public opinion at a scale that makes automated detection of political bias and factuality essential. However, the field still lacks u

A Principled Approach for Creating High-fidelity Synthetic Demonstrations for Imitation Learning

arXiv:2605.01232v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting (3DGS) have enabled visually realistic demonstration generation from a single expert trajectory and a short mul

safetyarxiv-cs-ro

A Theoretical Game of Attacks via Compositional Skills

arXiv:2605.01034v1 Announce Type: new Abstract: As large language models grow increasingly capable, concerns about their safe deployment have intensified. While numerous alignment strategies aim to re

A Theory of Generalization in Deep Learning

arXiv:2605.01172v1 Announce Type: new Abstract: We present a non-asymptotic theory of generalization in deep learning where the empirical neural tangent kernel partitions the output space. In directio

A Unified Multi-Dynamics Framework for Perception-Oriented Modeling in Tendon-Driven Continuum Robots

arXiv:2511.18088v2 Announce Type: replace Abstract: Tendon-driven continuum robots offer intrinsically safe and contact-rich interactions owing to their kinematic redundancy and structural compliance.

safetyarxiv-cs-ro

Adaptive Alarm Threshold Prediction in 4G Mobile Networks: A Percentile-Guided Deep Learning Framework with Interpretable Outputs

arXiv:2605.00838v1 Announce Type: cross Abstract: In mobile telecommunications, alarms act as early warning signals. They are triggered when a cell, the basic unit of radio coverage, shuts down or beh

Adaptive GoGI-Skip: Coupling Goal-Gradient Importance with Dynamic Uncertainty for Efficient Reasoning

arXiv:2505.08392v3 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting trades inference speed for reasoning accuracy. Existing compressors force a compromise as static gradient technique

Adaptive Interpolation-Synthesis for Motion In-Betweening on Keyframe-Based Animation

arXiv:2605.02742v1 Announce Type: cross Abstract: Motion in-betweening is one of the most artistically demanding and time consuming stages of 3D animation, where the expressivity and rhythm of motion

Adaptive Pluralistic Alignment: A pipeline for dynamic artificial democracy

arXiv:2605.01642v1 Announce Type: new Abstract: Prevailing alignment methods target a fixed set of preferences and therefore risk forcing value lock-in as societal norms evolve over time. We introduce

Adversarial Imitation Learning with General Function Approximation: Theoretical Analysis and Practical Algorithms

arXiv:2605.01778v1 Announce Type: new Abstract: Adversarial imitation learning (AIL), a prominent approach in imitation learning, has achieved significant practical success powered by neural network a

AFFormer: Adaptive Feature Fusion Transformer for V2X Cooperative Perception under Channel Impairments

arXiv:2605.01888v1 Announce Type: new Abstract: Accurate 3D object detection is essential for ensuring the safety of autonomous vehicles. Cooperative perception, which leverages vehicle-to-everything

Agentic Learner with Grow-and-Refine Multimodal Semantic Memory

arXiv:2511.21678v2 Announce Type: replace-cross Abstract: MLLMs exhibit strong reasoning on isolated queries, yet they operate de novo -- solving each problem independently and often repeating the sam

AgentReputation: A Decentralized Agentic AI Reputation Framework

arXiv:2605.00073v1 Announce Type: new Abstract: Decentralized, agentic AI marketplaces are rapidly emerging to support software engineering tasks such as debugging, patch generation, and security audi

safetyarxiv-cs-ai

AI Alignment via Incentives and Correction

arXiv:2605.01643v1 Announce Type: new Abstract: We study AI alignment through the lens of law-and-economics models of deterrence and enforcement. In these models, misconduct is not treated as an exter

AI music generator Udio just admitted in a court filing that it trained on audio scraped from YouTube videos. It’s already being sued by lab…

AI music generator Udio just admitted in a court filing that it trained on audio scraped from YouTube videos. It’s already being sued by labels & artists for what they say is copyright infringement on

Alex Karp now sounding like @garymarcus. Sooner or later, everyone figures it out.

Alex Karp now sounding like @garymarcus. Sooner or later, everyone figures it out. Palantir CEO Alex Karp goes after AI slop. The fight over AI “slop” is really a fight over whether software is perfor

ALIGNS: Unlocking nomological networks in psychological measurement through a large language model

arXiv:2509.09723v3 Announce Type: replace Abstract: Psychological measurement is critical to many disciplines. Despite advances in measurement, building nomological networks, theoretical maps of how c

Ambient Persuasion in a Deployed AI Agent: Unauthorized Escalation Following Routine Non-Adversarial Content Exposure

arXiv:2605.00055v1 Announce Type: cross Abstract: We report a safety incident in a deployed multi-agent research system in which a primary AI agent installed 107 unauthorized software components, over

safetyarxiv-cs-ai

Analyzing Adversarial Inputs in Deep Reinforcement Learning

arXiv:2402.05284v2 Announce Type: replace Abstract: In recent years, Deep Reinforcement Learning (DRL) has become a popular paradigm in machine learning due to its successful applications to real-worl

ANO: A Principled Approach to Robust Policy Optimization

arXiv:2605.02320v1 Announce Type: cross Abstract: Proximal Policy Optimization (PPO) dominates deep RL but faces a fundamental dilemma. Its 'hard clipping' mechanism discards valuable gradient informa

Anomaly-Preference Image Generation

arXiv:2605.02439v1 Announce Type: new Abstract: Synthesizing realistic and diverse anomalous samples from limited data is vital for robust model generalization. However, existing methods struggle to r

Anticipation-VLA: Solving Long-Horizon Embodied Tasks via Anticipation-based Subgoal Generation

arXiv:2605.01772v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a powerful paradigm for embodied intelligence, enabling robots to perform tasks based on natural l

ARGUS: Policy-Adaptive Ad Governance via Evolving Reinforcement with Adversarial Umpiring

arXiv:2605.02200v1 Announce Type: new Abstract: Online advertising governance faces significant challenges due to the non-stationary nature of regulatory policies, where emerging mandates (e.g., restr

Artificial intelligence language technologies in multilingual healthcare: Grand challenges ahead

arXiv:2605.01441v1 Announce Type: new Abstract: AI language technologies (AILTs), increasingly enabled by large language models (LLMs), are becoming embedded in multilingual healthcare workflows for t

Attention-Based Neural-Augmented Kalman Filter for Legged Robot State Estimation

arXiv:2601.18569v2 Announce Type: replace-cross Abstract: In this letter, we propose an Attention-Based Neural-Augmented Kalman Filter (AttenNKF) for state estimation in legged robots. Foot slip is a

Attention Sinks in Massively Multilingual Neural Machine Translation:Discovery, Analysis, and Mitigation

arXiv:2605.01229v1 Announce Type: cross Abstract: Cross-attention patterns in neural machine translation (NMT) are widely used to study how multilingual models align linguistic structure. We report a

Auditing demographic bias in AI-based emergency police dispatch: a cross-lingual evaluation of eleven large language models

arXiv:2605.01451v1 Announce Type: new Abstract: Large language models (LLMs) are rapidly being integrated into high-stakes public safety systems, including emergency call triage and dispatch decision

Autonomous Drift Learning in Data Streams: A Unified Perspective

arXiv:2605.01295v1 Announce Type: new Abstract: In the pursuit of autonomous learning systems, the foundational assumption of stationarity, the premise that data distributions and model behaviors rema

Autonomous Reliability Qualification of Ga_2O_3-based Hydrogen and Temperature Sensors via Safe Active Learning

arXiv:2605.00868v1 Announce Type: cross Abstract: We present a Safe Active Learning (SAL) framework for autonomous reliability characterization of rectifying Ga_2O_3-based devices under coupled therma

Behavior-Grounded Lane Representation Learning for Multi-Task Traffic Digital Twins

arXiv:2605.01901v1 Announce Type: new Abstract: Traffic digital twins are powerful tools for advanced traffic management, and most systems are built on static geometric representations. However, these

Beyond Crash: Hijacking Your Autonomous Vehicle for Fun and Profit

arXiv:2602.07249v2 Announce Type: replace-cross Abstract: Autonomous Vehicles (AVs), especially vision-based AVs, are rapidly being deployed without human operators. As AVs operate in safety-critical

Beyond Perceptual Shortcuts: Causal-Inspired Debiasing Optimization for Generalizable Video Reasoning in Lightweight MLLMs

arXiv:2605.01324v1 Announce Type: new Abstract: Although reinforcement learning (RL) has significantly advanced reasoning capabilities in large multimodal language models (MLLMs), its efficacy remains

Beyond Semantic Relevance: Counterfactual Risk Minimization for Robust Retrieval-Augmented Generation

arXiv:2605.01302v1 Announce Type: new Abstract: Standard Retrieval-Augmented Generation (RAG) systems predominantly rely on semantic relevance as a proxy for utility. However, this assumption collapse

Beyond Specialization: Robust Reinforcement Learning Navigation via Procedural Map Generators

arXiv:2605.02528v1 Announce Type: cross Abstract: Deep reinforcement learning (DRL) navigation policies often overfit to the structure of their training environments, as environmental diversity is typ

Bi-Level Reinforcement Learning Control for an Underactuated Blimp via Center-of-Mass Reconfiguration

arXiv:2605.01289v1 Announce Type: new Abstract: This paper investigates goal-directed tracking control of underactuated blimps with center-of-mass (CoM) reconfiguration. Unlike conventional overactuat

safetyarxiv-cs-ro

Binary Rewards and Reinforcement Learning: Fundamental Challenges

arXiv:2605.02375v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a standard approach for improving reasoning in language models, yet models trained with

Bolek: A Multimodal Language Model for Molecular Reasoning

arXiv:2605.02745v1 Announce Type: new Abstract: Molecular property models increasingly support high-stakes drug-discovery decisions, but their outputs are often difficult to audit: classical predictor

🚨 BOTH ALTMAN AND BROCKMAN SELF-DEALING ON CEREBRAS >Greg Brockman acquires personal Cerebras ownership in 2017 >Altman, separately, invest…

🚨 BOTH ALTMAN AND BROCKMAN SELF-DEALING ON CEREBRAS >Greg Brockman acquires personal Cerebras ownership in 2017 >Altman, separately, invests in Cerebras >Brockman pushes OpenAI to merge with Cerebras

Breaking the Computational Barrier: Provably Efficient Actor-Critic for Low-Rank MDPs

arXiv:2605.01242v1 Announce Type: new Abstract: Reinforcement learning (RL) is a fundamental framework for sequential decision-making, in which an agent learns an optimal policy through interactions w

Bridging the Gap Between Average and Discounted TD Learning

arXiv:2605.02103v1 Announce Type: new Abstract: The analysis of Temporal Difference (TD) learning in the average-reward setting faces notable theoretical difficulties because the Bellman operator is n

Bringing Order to Asynchronous SGD: Towards Optimality under Data-Dependent Delays with Momentum

arXiv:2605.02043v1 Announce Type: new Abstract: Asynchronous stochastic gradient descent (SGD) enables scalable distributed training but suffers from gradient staleness. Existing mitigation strategies

Brockman confirms that Sam was fired for not being consistently candid. Crazy that @karaswisher blocked me for saying that the board fired S…

Brockman confirms that Sam was fired for not being consistently candid. Crazy that @karaswisher blocked me for saying that the board fired Sam for not being consistently candid, when that is in fact w