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Addressing Longstanding Challenges in Cognitive Science with Language Models

arXiv:2511.00206v3 Announce Type: replace Abstract: Cognitive science faces ongoing challenges in research integration, formalization, conceptual clarity, and other areas, in part due to its multiface

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Advancing youth safety and opportunity through global leadership

DGX agent

OpenAI outlines initiatives and commitments to enhance youth safety while creating educational and economic opportunities for young people globally. The effort emphasizes OpenAI's role in responsible

safetyopenai

2 Jun 2026

Adversarial Attacks on Robot Localization Systems via Deep Feature Perturbation

arXiv:2606.01892v1 Announce Type: new Abstract: Robot localization systems are critical for autonomous navigation and safety. Adversarial perturbations can mislead these systems, resulting in mislocal

Adversarial Feeds Steer LLM Agent Decisions Against Their Defaults

arXiv:2606.00914v1 Announce Type: new Abstract: LLM agents increasingly act after consuming ranked external information streams such as social feeds, search results, retrieval contexts, and email queu

Adversarially Robust Control of Conditional Value-at-Risk via Rockafellar-Uryasev Conformal Inference

arXiv:2606.00320v1 Announce Type: new Abstract: We present an online, distribution-free framework for controlling the Conditional Value-at-Risk (CVaR), extending conformal tail risk control to non-sta

Agent Operating Systems (AOS): Integrating Agentic Control Planes into, and Beyond, Traditional Operating Systems

arXiv:2606.01508v1 Announce Type: cross Abstract: Traditional operating systems were designed around deterministic programs, explicit control flow, and human initiated workflows. Their core abstractio

Agentic Transformers Provably Learn to Search via Reinforcement Learning

arXiv:2606.00183v1 Announce Type: cross Abstract: Tree search is a central abstraction behind many language-agent reasoning and decision-making tasks: agents must explore actions, remember failures, a

Agents on a Tree: Pathwise Coordination for Multi-Objective Molecular Optimization

arXiv:2606.00008v1 Announce Type: new Abstract: Multi-objective molecular optimization requires searching vast chemical spaces under conflicting objectives, where early design decisions strongly const

Agricultural Landscape Understanding At Country-Scale

arXiv:2411.05359v2 Announce Type: replace-cross Abstract: Comprehensive agricultural landscape understanding is critical for addressing global challenges in food security, climate change, and resource

AI From the Margins (AIM): Rethinking Participatory AI Design Through the Lived Experience of Minoritized Communities

arXiv:2606.01171v1 Announce Type: cross Abstract: Artificial intelligence (AI) can reproduce and amplify the structural inequities faced by minoritized communities. Participatory AI has been proposed

AI-PROPELLER: Warehouse-Scale Interprocedural Code Layout Optimization with AlphaEvolve

arXiv:2606.00131v1 Announce Type: cross Abstract: Post-link optimizers (PLOs) such as Propeller and BOLT have demonstrated that precise, profile-guided code layout can extract significant performance

AI Sovereignty as National Learning Capacity: A Human-Centered Learning Mechanics Viewpoint on France, the United States, and China

arXiv:2606.00729v1 Announce Type: new Abstract: Artificial Intelligence is often discussed in France in terms of investment, compute capacity, regulation, employment, sovereignty, and education. These

Algorithmic Authority and the Clinical Standard of Care

arXiv:2606.00044v1 Announce Type: cross Abstract: The integration of artificial intelligence into clinical medicine creates a fundamental tension between algorithmic probabilistic reasoning and the ex

An Enigma of Artificial Reason: Investigating the Production-Evaluation Gap in Large Reasoning Models

arXiv:2606.01462v1 Announce Type: new Abstract: Studies of human reasoning have shown that people are typically stronger at evaluating reasoning than producing it from scratch. In contrast, large reas

An Improved Algorithm for Adversarial Linear Contextual Bandits via Reduction

arXiv:2508.11931v3 Announce Type: replace Abstract: We present an oracle-efficient, near-optimal algorithm for linear contextual bandits with adversarial losses and stochastic action sets, only requir

An NLP-Driven Framework for Curriculum-Labor Market Alignment: Schema-Constrained LLM Extraction, ESCO-Anchored Semantic Matching, and Multi-Dimensional Gap Quantification

arXiv:2606.01982v1 Announce Type: new Abstract: Schema-constrained information extraction from diverse educational and labor-market corpora remains an open challenge in natural language processing bec

ANDES: Agent Native Data Evolving Synthesis Tool for Autonomous Instruction Alignment

arXiv:2606.01279v1 Announce Type: new Abstract: AI agents are increasingly being tasked with automating AI research itself, particularly the critical post-training phase that transforms base LLMs into

AnomSeer: Reinforcing Multimodal LLMs to Reason for Time-Series Anomaly Detection

arXiv:2602.08868v2 Announce Type: replace-cross Abstract: Time-series anomaly detection (TSAD) with multimodal large language models (MLLMs) is an emerging area, yet a persistent challenge remains: ML

Anthropic faces AI spending backlash before IPO https://www.axios.com/2026/06/02/anthropic-ipo-ai-sticker-shock-spending-usage?utm_campaign=…

Anthropic faces AI spending backlash before IPO https://www.axios.com/2026/06/02/anthropic-ipo-ai-sticker-shock-spending-usage?utm_campaign=mrf-utm_campaign=editorial&utm_source=x&utm_medium=owned_soc

safetygary-marcus--x

Approximate Imitation Learning for Event-based Quadrotor Flight in Cluttered Environments

arXiv:2603.07578v2 Announce Type: replace Abstract: Event cameras offer high temporal resolution and low latency, making them ideal sensors for high-speed robotic applications where conventional camer

safetyarxiv-cs-ro

au_0-WM: A Unified Video-Action World Model for Robotic Manipulation

arXiv:2606.01027v1 Announce Type: new Abstract: Robotic manipulation requires models that generate executable actions while anticipating and evaluating their future consequences before physical execut

safetyarxiv-cs-ro

Authenticity Debt and the Synthetic Content Threat Landscape: A Layered Framework for Trust, Provenance, and IP Governance in the Generative AI Era

arXiv:2606.00621v1 Announce Type: cross Abstract: Generative artificial intelligence has fundamentally changed how content is now produced. It has enabled how high-fidelity text, images, audio, and vi

AutoFFS: Adversarial Deformations for Facial Feminization Surgery Planning

arXiv:2603.02288v2 Announce Type: replace Abstract: Facial feminization surgery (FFS) is a key component of gender affirmation for transgender and gender diverse patients, aiming to reshape craniofaci

Automated Essay Scoring and Language Certification: Assessing Generalizability, Agreement and Validity for French

arXiv:2606.02009v1 Announce Type: new Abstract: In Automated Essay Scoring (AES), benchmarking practices have fostered minimalist evaluation practices, in contrast with the broader-view recommendation

safetyarxiv-cs-cl

Balancing Accuracy and Efficiency: Adaptive Dynamics Orchestration for Model Predictive Control

arXiv:2606.00085v1 Announce Type: new Abstract: Model Predictive Control (MPC) for autonomous navigation faces a fundamental trade-off between model accuracy and real-time efficiency. High-fidelity dy

safetyarxiv-cs-ro

Bandit Simulation for Average Reward Inference

arXiv:2606.00913v1 Announce Type: cross Abstract: Multi-arm bandit algorithms are increasingly used in online platforms, clinical trials, and social science experiments, but valid statistical inferenc

Baton: Explicit Semantic Blueprints for Joint Video-Audio Generation

arXiv:2605.25195v2 Announce Type: replace Abstract: Current open-source diffusion models struggle to generate stable and synchronized audio-visual content, particularly in scenarios demanding complex

Behavior Cloning of MPC for 3-DOF Robotic Manipulators

arXiv:2606.00383v1 Announce Type: cross Abstract: While Model Predictive Control (MPC) provides strong stability and robustness, it imposes a significant computational burden on real-time systems. Thi

Behavior-Invariant Task Representation Learning with Transformer-based World Models for Offline Meta-Reinforcement Learning

arXiv:2606.00780v1 Announce Type: cross Abstract: Offline meta-reinforcement learning leverages static datasets to enable agents to generalize to unseen environments by combining offline efficiency wi

Better Source, Better Flow: Learning Condition-Dependent Source Distribution for Flow Matching

arXiv:2602.05951v2 Announce Type: replace-cross Abstract: Flow matching has recently emerged as a promising alternative to diffusion-based generative models, particularly for text-to-image generation.

Beyond Access: Guided LLM Scaffolding for Independent Learning in Undergraduate Statistics

arXiv:2606.01375v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly entering students' learning practices, but their educational value depends on whether they support reaso

Beyond Categories of Caste: Examining Caste Bias and Morality in Text-to-Image AI Models

arXiv:2606.00039v1 Announce Type: cross Abstract: Text-to-Image (T2I) models have shown promising utility across various domains. However, such models are also amplifying harmful societal biases in th

Beyond End-to-End Video Models: An LLM-Based Multi-Agent System for Educational Video Generation

arXiv:2602.11790v2 Announce Type: replace Abstract: Although recent end-to-end video generation models demonstrate impressive performance in visually oriented content creation, they remain limited in

Beyond Independent Manipulation: Individual Fairness-aware Strategic Classification with Peer Imitation

arXiv:2606.00827v1 Announce Type: cross Abstract: Strategic classification (SC) investigates scenarios where agents manipulate their features to obtain favorable decisions from predictive models. Exis

Beyond Procedure: Substantive Fairness in Conformal Prediction

arXiv:2602.16794v2 Announce Type: replace-cross Abstract: Conformal prediction (CP) offers distribution-free uncertainty quantification for machine learning models, yet its interplay with fairness in

Beyond Topical Similarity: Contrastive Evidence Retrieval with Interpretable Attention Alignment in RAG

arXiv:2606.01482v1 Announce Type: new Abstract: Ensuring factuality and interpretability in RAG remains an open and urgent problem. We introduce Contrastive Evidence Rationale Attention (CERA), the fi

safetyarxiv-cs-cl

Both Topology and Text Matter: Revisiting LLM-guided Out-of-Distribution Detection on Text-attributed Graphs

arXiv:2602.11641v2 Announce Type: replace Abstract: Text-attributed graphs (TAGs) associate nodes with textual attributes and graph structure, enabling GNNs to jointly model semantic and structural in

BranPO: Scalable Contrastive Branch Sampling for Long-Horizon Agentic Reinforcement Learning

arXiv:2602.03719v2 Announce Type: replace Abstract: Agentic reinforcement learning enables large language models to perform multi-turn planning and tool use, but long-horizon training remains challeng

safetyarxiv-cs-cl

Breaking the Information Silo: Semantic Personas for Cross-Domain Recommendation

arXiv:2606.01783v1 Announce Type: cross Abstract: Digital platforms increasingly operate as isolated information silos, limiting their ability to construct comprehensive user representations across do

Breaking the Reversal Curse in Autoregressive Language Models via Identity Bridge

arXiv:2602.02470v2 Announce Type: replace Abstract: Autoregressive large language models (LLMs) have achieved remarkable success in many complex tasks, yet they can still fail in very simple logical r

Bridging Reasoning Trajectories in On-Policy Distillation via Near-Future Guidance

arXiv:2606.00305v1 Announce Type: cross Abstract: On-Policy Distillation (OPD) improves large language model reasoning by training a student model on trajectories sampled from its own policy under tea

Bridging the Last Mile of Time Series Forecasting with LLM Agents

arXiv:2606.02497v1 Announce Type: new Abstract: Time series forecasting has advanced rapidly, especially with the emergence of foundation models that show strong zero-shot performance on numerical ext

Calibrating Uncertainty for Zero-Shot Adversarial CLIP

arXiv:2512.12997v2 Announce Type: replace-cross Abstract: CLIP delivers strong zero-shot classification but remains highly vulnerable to adversarial attacks. Prior adversarial fine-tuning work primari

Can AI Review Improve Paper Drafting? An Empirical Study on 20 Computer Architecture Submissions

arXiv:2606.01013v1 Announce Type: new Abstract: Research is advancing faster than ever with artificial intelligence (AI); and so are the corresponding research papers. The exploding volume of AI-gener

CanonCGT: Reference-Based Color Grading via Canonical Pivot Representation

arXiv:2606.01638v1 Announce Type: new Abstract: Reference-based color grading aims to reproduce the tonal mood and lighting of a reference while preserving color harmony and scene structure. Existing

CAPF: Guiding Search-Agent Rollouts with Credit-Attenuated Privileged Feedback

arXiv:2606.01830v1 Announce Type: new Abstract: Recent LLM search agents use reinforcement learning with verifiable rewards (RLVR) to learn search-augmented reasoning from outcome rewards. On hard pro

CAST: Non-Privileged Clipped Asymmetric Self-Teaching with Advantage Flipping for GRPO

arXiv:2606.00172v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR), especially Group Relative Policy Optimization (GRPO), has been widely used to improve reasoning i

CEAR: Certified Ensemble Adversarial Robustness in DNNs

arXiv:2606.01437v1 Announce Type: cross Abstract: Deep Neural Networks (DNNs) are highly susceptible to adversarial perturbations, leading to extensive research on robustness for safety-critical appli