Search: “safety”

Beyond Outcome Rewards: Step-Level Self-Distilled Policy Optimization for Deep Search Agents

arXiv:2608.12764v1 Announce Type: cross Abstract: Deep search agents operate over trajectories spanning dozens of steps, yet standard reinforcement learning provides only a single outcome reward per t

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Bias Mitigation in Face Recognition via Demographic-based Supervised Contrastive Learning

DGX agent

arXiv:2608.12971v1 Announce Type: new Abstract: Face recognition systems have been shown to be biased toward certain demographic groups by exhibiting different error rates across gender, age, or ethni

safetyarxiv-cs-cv

14 Aug 2026

ContactGuard: Pre-Contact Execution Monitoring with Action-Conditioned Latent World Models

arXiv:2608.13438v1 Announce Type: cross Abstract: Contact-rich manipulation failures are often detected only after the robot has committed to contact. This is especially limiting in wrist-camera setup

Context-Matched Distillation: Teacher Causality for Autoregressive Video Distillation

arXiv:2608.13391v1 Announce Type: new Abstract: Interactive autoregressive video generation demands both low-latency rollouts and precise online control. Few-step distillation accelerates generation b

CROP: Task Relevance via Counterfactuals for Selective On-Policy Distillation

arXiv:2608.13387v1 Announce Type: new Abstract: On-policy distillation (OPD) supervises a student language model on trajectories sampled from its current policy, but assigns equal credit to response t

CW-BASS v2: Saturation-Aware Pseudo-Label Selection for Semi-Supervised Segmentation under Foundation-Model Teachers

arXiv:2608.12773v1 Announce Type: new Abstract: Semi-supervised semantic segmentation has long turned on one question, which pseudo-labels to trust, and a generation of selection rules, dynamic thresh

DAPD: Dual-Anchored Policy Distillation

arXiv:2608.01735v2 Announce Type: replace Abstract: On-policy (self) distillation (OPSD) is increasingly adopted for language-model post-training. It strengthens the teacher with privileged informatio

Decoding Task Progress from VLA Representations

arXiv:2608.13474v1 Announce Type: new Abstract: Vision-language-action models (VLAs) are moving rapidly towards deployment as general-purpose manipulation policies, but we currently lack basic tools f

safetyarxiv-cs-ro

Decoupled Contrastive Decoding via Expert-Aligned Drafting

arXiv:2608.12913v1 Announce Type: new Abstract: Contrastive Decoding (CD) improves generation quality, but its amateur-model pass makes decoding expensive. Accelerating CD with speculative decoding ra

DiffGRM: Diffusion-based Generative Recommendation Model

arXiv:2510.21805v2 Announce Type: replace-cross Abstract: Generative recommendation (GR) is an emerging paradigm that represents each item via a tokenizer as an n-digit semantic ID (SID) and predicts

Model Releases

Doctorina MedBench: A Dialogue-Based Benchmark and Evaluation Framework for Agent-Based Medical AI

model-releasesarxiv-cs-ai

arXiv:2603.25821v3 Announce Type: replace-cross Abstract: We present Doctorina MedBench, an evaluation framework for agent-based medical AI based on the simulation of physician-patient interactions. U

Doubly Robust Estimation of Causal Effect on CVR with Targeted Regularization

arXiv:2608.13461v1 Announce Type: new Abstract: Post-click conversion rate (CVR) is a key metric in various scenarios including e-commerce and advertising, reflecting the efficiency and user experienc

Dual-Stream Cross-Anchor Correction Grounding Long-Form Captions and the Domain Limits of Object-Level Anchors

arXiv:2608.12746v1 Announce Type: cross Abstract: Object hallucination in multimodal large language models arises when language priors and corpus co-occurrence bias outweigh the visual evidence, with

Embedding networks with the random walk first return time distribution

arXiv:2512.02694v3 Announce Type: replace-cross Abstract: We propose the first return time distribution (FRTD) of a random walk as an interpretable and mathematically grounded node embedding. The FRTD

Entropy-Augmented Multi-Objective Policy Optimization in Multiagent Systems

arXiv:2608.12534v1 Announce Type: cross Abstract: Autonomous agent teams deployed in settings such as marine and extraterrestrial outposts must coordinate actions to achieve optimal outcomes across mu

safetyarxiv-cs-ro

EU-ETS under attack? The impact of carbon price suppression on the decarbonization of the power sector

arXiv:2608.12363v1 Announce Type: cross Abstract: European countries are debating policies to mitigate the increased energy costs caused by renewed geopolitical tensions, while pursuing decarbonizatio

Evaluation Resolution Confounds Learning-Rule Comparisons in Model-Brain RSA of Early Visual Cortex

arXiv:2608.12408v1 Announce Type: cross Abstract: Representational similarity analysis (RSA) is increasingly used to ask which learning rules give convolutional networks brain-like representations. Be

EvoTale: Continual Character Customization for Expanding Story Worlds

arXiv:2603.16285v2 Announce Type: replace Abstract: Character-centric story visualization aims to synthesize coherent image sequences that depict narrative events and interactions while preserving rec

Finite-Time Minimax Bounds and an Optimal Lyapunov Policy in Queueing Control

arXiv:2506.18278v4 Announce Type: replace-cross Abstract: We introduce an original minimax framework for finite-time performance analysis in queueing control and propose a surprisingly simple Lyapunov

FSGR: Mitigating Token Frequency Bias for Fair SID-Based Generative Recommendation

arXiv:2608.12845v1 Announce Type: cross Abstract: Semantic ID (SID)-based generative recommendation has recently achieved remarkable success. However, existing methods suffer from a previously overloo

Humans are Missing from AI Coding Agent Research

arXiv:2608.12355v1 Announce Type: cross Abstract: Recent progress in AI coding agent research has led to rapid improvements in agents' ability to autonomously perform complex software engineering task

HybridSB-MoE: Dual-Domain Schrodinger Bridges with Scene-Adaptive Expert Routing for Speech Enhancement

arXiv:2608.12715v1 Announce Type: cross Abstract: Generative speech enhancement faces three gaps: spectral models capture harmonic structure but often disrupt phase, waveform models preserve phase but

I follow the AI & math discourse a bit - without understanding the actual math. I thought I might offer some thoughts as a scientist in stru…

I follow the AI & math discourse a bit - without understanding the actual math. I thought I might offer some thoughts as a scientist in structural biology - a field transformed by various tech over th

safetygary-marcus--x

I-SDPO: Instance-Level Adaptive Self-Distillation Policy Optimization

arXiv:2608.12957v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) learns from reward differences within a rollout group, but receives no useful relative signal when every sam

Intern-S2-Preview: Scientific Agentic Foundation Model

arXiv:2608.13505v1 Announce Type: cross Abstract: Scientific discovery increasingly requires AI systems that can reason over scientific evidence of heterogeneous modalities, interact with scientific t

Into the ORBIT for Time Series: Training Regimes for Foundation Models

arXiv:2608.13262v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) have advanced primarily through architectural innovation, while training regimes for large-scale heterogeneous c

It's How You Ask: Gender-Associated Linguistic Bias in LLMs

arXiv:2608.13328v1 Announce Type: cross Abstract: Professional communication is increasingly mediated by LLMs - but do these models serve all users equally? We show that when prompts contain linguisti

Large Language Models Persuade Without Planning Theory of Mind

arXiv:2602.17045v2 Announce Type: replace Abstract: A growing body of work attempts to evaluate the theory of mind (ToM) abilities of humans and large language models (LLMs) using static, non-interact

Latent On-Policy Self-Distillation

arXiv:2608.13040v1 Announce Type: cross Abstract: Enabling agents to learn from experience and internalize it into their policy has become a central problem in self-evolving AI. On-policy self-distill

Learning Under Treatment-Induced Label Indeterminacy with Expert Annotations of Counterfactual Outcomes: A Case Study in Neurological Prognostication

arXiv:2608.12477v1 Announce Type: new Abstract: Clinical prediction models are often developed as if the outcome of interest were cleanly observed for every patient. This assumption fails when treatme

Local Ai

LLM-Assisted Dynamic Threat Analysis for Attacker-Reachable Software Weaknesses in Autonomous Vehicles

arXiv:2608.13450v1 Announce Type: cross Abstract: Autonomous vehicles depend on large safety-critical software stacks, where weaknesses reachable from adversarial inputs may affect steering, braking,

local-aiarxiv-cs-lg

LLMs Know the Constraint But Do Not Use It: Activation Bottlenecks in Pragmatic Constraint Reasoning

arXiv:2608.12321v1 Announce Type: cross Abstract: When a salient surface cue competes with an implicit feasibility constraint, LLMs often fail -- but aggregate accuracy conflates genuine constraint in

LocusGS: Spatially Grounded Tokens for Feed-Forward 3D Gaussian Splatting

arXiv:2608.12825v1 Announce Type: new Abstract: Recent query-based feed-forward 3DGS methods represent a scene using learnable queries, each aggregating multi-view evidence and decoding a group of Gau

Measuring Curriculum-Labor Market Alignment at the Scale of a Program Portfolio

arXiv:2608.12356v1 Announce Type: cross Abstract: A college offering several overlapping computing degrees implicitly assumes that its programs are differentiated in line with how the labor market seg

Mr3D-VL: A generalist vision language foundation model for Multiparametric 3D Magnetic Resonance Imaging

arXiv:2608.12689v1 Announce Type: cross Abstract: Multi-parametric magnetic resonance imaging (mpMRI) is a cornerstone for brain tumor diagnosis and treatment, yet current AI models face critical limi

Multi-AUV Ad-hoc network-based Target Tracking: A Value Gradient Guidance Multi-Agent Diffusion Reinforcement Learning Approach

arXiv:2608.12436v1 Announce Type: new Abstract: Multi-AUV ad-hoc network-based target tracking requires networked autonomous underwater vehicles (AUVs) to cooperatively track maneuvering targets under

Multiview Representation Learning via Distributed Joint Latent Space Structuring

arXiv:2504.18455v2 Announce Type: replace-cross Abstract: We study distributed multiview representation learning, a problem in which K clients each observe a distinct but possibly statistically correl

NestDex: Nested Policy Learning with Copilot Assisted Teleoperation for Dexterous Manipulation

arXiv:2608.13362v1 Announce Type: new Abstract: Dexterous manipulation promises substantially richer robot interaction with the physical world, but learning these behaviours remains constrained by the

safetyarxiv-cs-ro

neurosymbolic world models – exactly what I argued for in 2020 in the Next Decade in AI – for the win.

neurosymbolic world models – *exactly* what I argued for in 2020 in the Next Decade in AI – for the win. Jeremy's excellent work here is a great illustration of a very powerful type of approach: LLM-g

safetygary-marcus--x

OGR-MARL: Option-Guided Residual Multi-Agent Reinforcement Learning for Heterogeneous USV Cooperative Pursuit in Constrained Port Waterways

arXiv:2608.12995v1 Announce Type: new Abstract: Heterogeneous USV cooperative pursuit in constrained port waterways requires evader interception under navigation, traffic, and role constraints. This p

On the global feature importance for interpretable and trustworthy heat demand forecasting

arXiv:2608.13039v1 Announce Type: new Abstract: The paper introduces the ante-hoc Explainable AI methodology to assess the global feature importance of the Machine Learning models used for heat demand

Online Correlation Clustering: Simultaneously Optimizing All ell_p-norms

arXiv:2510.15076v2 Announce Type: replace Abstract: The ell_p-norm objectives for correlation clustering present a fundamental trade-off between minimizing total disagreements (the ell_1-norm) and ens

Position: The Alignment Community is Unintentionally Building a Censor's Toolkit

arXiv:2608.12346v1 Announce Type: new Abstract: This position paper argues that modern AI alignment methods - originally designed to prevent harmful output - are dual-use technologies that may easily

Position: We Need Practical AI Alignment Methods to Mirror Human Reasoning

arXiv:2608.12372v1 Announce Type: new Abstract: AI systems are increasingly employed as decision aids, decision delegates, or autonomous decision-makers. This position paper argues that in many settin

Predictive Memory Localization: Forecasting Selective Intervention Paths from Internal Signals

arXiv:2608.12892v1 Announce Type: new Abstract: Activation steering turns localized representations into control directions, but localization alone does not reveal whether a direction has a selective

ProME: Prototype-Margin Environments with Repair-Aware Selection for Group-Robust Learning

arXiv:2608.13190v1 Announce Type: cross Abstract: Group-robust learning is crucial for maintaining accuracy on rare subpopulations when training-group labels are unavailable. However, existing methods

RAIL: An Automatic Classifier of the Artificial Intelligence Readiness Level

arXiv:2608.13428v1 Announce Type: new Abstract: Assessing the maturity of artificial intelligence technologies is essential for investment decisions, project management, and policy monitoring, yet the

Reconcile Once, Write Anytime: A Trust-Tiered Librarian and a Multi-Agent Writer for Drift-Free, Point-in-Time Research

arXiv:2608.12984v1 Announce Type: cross Abstract: Long-form research reports generated by large language models drift, contradict themselves, and lose provenance: the same metric appears with differen