Search: “safety”

UnsOcc: 3D Semantic Occupancy Prediction in Unstructured Scene via Rendering Fusion

arXiv:2606.03581v1 Announce Type: new Abstract: Unstructured scenes present unique challenges for autonomous driving, as irregular obstacles and sparse scene layouts undermine the effectiveness of tra

Using Reward Uncertainty to Induce Diverse Behaviour in Reinforcement Learning

DGX agent

arXiv:2606.03962v1 Announce Type: cross Abstract: Classical reinforcement learning (RL) typically seeks a deterministic policy that maximizes the expected sum of a scalar reward. Yet, modern applicati

safetyarxiv-cs-ai

3 Jun 2026

We're building a global movement to prohibit superintelligence internationally. Our new campaign in Canada is supported by over 30 MPs and S…

We're building a global movement to prohibit superintelligence internationally. Our new campaign in Canada is supported by over 30 MPs and Senators calling for a ban. After our success in the UK, it's

safetyconnor-leahy--x

What are you investing in? Hopium:

What are you investing in? Hopium: Former BlackRock fund manager Ed Dowd on the stock market: 'If 45% of your market cap is AI and there's no profits yet, what are you investing in?' 'You're investing

When Attention Collapses: Stage-Aware Visual Token Pruning from Structure to Semantics

arXiv:2606.03569v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have demonstrated remarkable capabilities but suffer from significant computational overhead during inference. While vis

When Graph Tokens Sink: A Mechanistic Analysis of Graph Language Models

arXiv:2606.03712v1 Announce Type: new Abstract: Graph Language Models (GLMs) have become a promising direction for adapting Large Language Models (LLMs) to graph learning tasks. By transforming graph

when sam quotes the bible, you know things aren’t going well for OpenAI

when sam quotes the bible, you know things aren’t going well for OpenAI one of the quotes i find most inspiring on a hard day: 'Whatever your hand finds to do, do it with all your might, for in the re

When to Re-Plan: Subgoal Persistence in Hierarchical Latent Reasoning

arXiv:2606.03741v1 Announce Type: new Abstract: Long-horizon reasoning requires a system to commit to medium-horizon intent without becoming rigid: re-plan too often and computation never coheres into

Who Deserves the Reward? SHARP: Shapley Credit-based Optimization for Multi-Agent System

arXiv:2602.08335v2 Announce Type: replace Abstract: Integrating Large Language Models (LLMs) with external tools via multi-agent systems offers a promising new paradigm for decomposing and solving com

World Models Meet Language Models: On the Complementarity of Concrete and Abstract Reasoning

arXiv:2606.03603v1 Announce Type: cross Abstract: World models and multimodal large language models (MLLMs) provide complementary capabilities for predicting future outcomes from static visual observa

safetyarxiv-cs-cl

yes

yes @GaryMarcus Like, is this based on ppl actually buying into Musk's truly unhinged pie-in-the-sky timelines for his fantastical sci-fi aspirations, which seem unlikely to even be technologically fe

You don’t need to be @garymarcus to know which way the wind blows.

You don’t need to be @garymarcus to know which way the wind blows. I would be way more bullish on AI if it actually worked and was actually replacing real humans at scale. Nothing is changing and we’r

A Modelling and Evaluation Framework for EuroCrops-Driven Sentinel-2 Crop Segmentation

arXiv:2606.00676v1 Announce Type: new Abstract: This work presents a configurable pipeline for generating semantic-segmentation-ready agricultural datasets from Sentinel-2 imagery and EuroCrops parcel

A Monosemantic Attribution Framework for Stable Interpretability in Clinical Neuroscience Transformer-Based Language Models

arXiv:2601.17952v2 Announce Type: replace-cross Abstract: Interpretability remains a key challenge for deploying language models (LM) in clinical settings such as progression diagnosis of Alzheimer di

A Practical Upper Bound on Selection Bias Effects in Medical Prediction Models

arXiv:2606.00563v1 Announce Type: cross Abstract: Selection bias is a common and often unavoidable aspect of real-world data that challenges the generalizability of machine learning models. When model

A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection)

arXiv:2606.00155v1 Announce Type: cross Abstract: Modern network intrusion detection systems (NIDS) are caught in a structural contradiction: the protocols carrying the highest threat intelligence are

A Shared Valence Axis Across Modern LLMs and Human EEG: The Saturation Regularity

arXiv:2606.00129v1 Announce Type: cross Abstract: Large language models (LLMs) have emerged as powerful representation learners whose internal features increasingly align with human cognition. We stud

Adaptive Order Policies for Masked Diffusion

arXiv:2606.00295v1 Announce Type: new Abstract: Masked diffusion models have seen great success in capturing data distributions over discrete sequences in domains such as text and proteins. These mode

Adaptive Time Series Reasoning via Segment Selection

arXiv:2602.18645v2 Announce Type: replace Abstract: Time series reasoning tasks often start with a natural language question and require targeted analysis of a time series. Evidence may span the full

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

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

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

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