Search: “safety”

Point Cloud Diffusion with Global and Local Reconstruction for Instance-Level 3D Anomaly Detection

arXiv:2606.25740v1 Announce Type: new Abstract: 3D anomaly detection in point clouds is critical for high-precision industrial manufacturing. Reconstruction-based methods have laid a strong foundation

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Position Spaces and Graphs

DGX agent

arXiv:2606.25719v1 Announce Type: new Abstract: In this paper, we introduce position graphs, a graph-based reasoning framework based on the formalization of position spaces. This framework utilizes tw

safetyarxiv-cs-ai

25 Jun 2026

Power-Budgeted Underwater Vehicle Control via Constrained Reinforcement Learning

arXiv:2606.25680v1 Announce Type: new Abstract: Underwater vehicles operate from a fixed onboard energy budget that propulsion rapidly depletes, so a controller that completes its task while drawing l

Reflective VLA: In-Context Action Consequences Make VLAs Generalize

arXiv:2606.25215v1 Announce Type: new Abstract: Most vision-language-action (VLA) models are reactive: they predict the next action from the current instruction and observation, implicitly assuming th

RGB: RL Guided Whole-Body MPPI for Humanoid Control

arXiv:2606.25123v1 Announce Type: new Abstract: Humanoid robots require whole-body controllers that are both robust and precise in contact-rich environments. While deep reinforcement learning (RL) ach

RN-D: Discretized Categorical Actors for On-Policy Reinforcement Learning

arXiv:2601.23075v2 Announce Type: replace Abstract: On-policy Reinforcement Learning (RL) remains a dominant paradigm for continuous control, yet standard implementations rely on Gaussian actors and r

ROAD-VLA: Robust Online Adaptation via Self-Distillation for Vision-Language-Action Models

arXiv:2606.25800v1 Announce Type: new Abstract: Effective online adaptation of vision-language-action (VLA) models remains challenging, as sparse rewards provide weak supervision for high-dimensional

SAC^2-Net: Semantic Anchoring and Complementary-Consensus Fusion for Multimodal Micro-Expression Recognition

arXiv:2606.25542v1 Announce Type: new Abstract: Micro-expression recognition (MER) is challenging due to subtle facial movements, limited data, and the ambiguous relationship between Action Units (AUs

SAGE-Nav: Leveraging LLM Planning and Alignment Fusion for Hierarchical Scene Graph-Guided Navigation

arXiv:2606.25497v1 Announce Type: new Abstract: Object-Goal Navigation (ObjNav) requires embodied agents to autonomously locate specified targets using only egocentric visual observations. Existing mo

ScalingAR: Scaling Confidence for Autoregressive Image Generation

arXiv:2509.26376v3 Announce Type: replace Abstract: Test-time strategies have shown remarkable success in improving large language models, but their application to next-token prediction (NTP) autoregr

Semantic Consistency Policy Optimization for Reinforcement Learning of LLM Agents

arXiv:2606.25852v1 Announce Type: new Abstract: Group-based reinforcement learning effectively post-trains LLM agents for long-horizon, sparse-reward tasks by deriving step-level credit from trajector

Solving Markov Decision Processes with Future Information via MPC

arXiv:2606.24991v1 Announce Type: cross Abstract: Model Predictive Control (MPC) is widely used in industrial and robotic systems for enforcing constraints and embedding domain knowledge through finit

Specifying AI-SDLC Processes: A Protocol Language for Human-Agent Boundaries

arXiv:2606.20615v2 Announce Type: replace Abstract: AI agents now participate as first-class team members across the software development lifecycle, yet no specification language exists for expressing

StairMaster: Learning to Conquer Risky Hollow Stairs for Agile Quadrupedal Robots

arXiv:2606.25765v1 Announce Type: new Abstract: Climbing hollow stairs remains a challenging problem for quadruped robots due to the high risk of leg trapping, severe depth sparsity, and high-frequenc

Supervised Reinforcement Learning for the Coordination of Distributed Energy Resources

arXiv:2606.24947v1 Announce Type: new Abstract: The increasing integration of distributed energy resources (DERs) is crucial for power system decarbonization, yet unlocking DERs' flexibility is challe

Taxonomy-aware deep learning for hierarchical marine species classification in underwater imagery

arXiv:2606.25989v1 Announce Type: new Abstract: Automated classification of marine species from underwater imagery is essential for scalable ocean biodiversity monitoring and conservation policy. Exis

The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing

arXiv:2606.25108v1 Announce Type: new Abstract: Autonomous AI systems are transitioning from advisory to autonomous roles for medication prescriptions. Recent United States bill H.R. 238 and Utah's pr

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems

arXiv:2606.24937v1 Announce Type: cross Abstract: The Hitchhiker's Guide to Agentic AI is a comprehensive practitioner's reference for building autonomous AI systems. The book covers the full stack fr

safetyarxiv-cs-cl

TIDAL: Temporally Interleaved Diffusion and Action Loop for High-Frequency VLA Control

arXiv:2601.14945v2 Announce Type: replace Abstract: Large-scale Vision-Language-Action (VLA) models offer semantic generalization but suffer from high inference latency, limiting them to low-frequency

Towards Scalable Multi-Task Reinforcement Learning with Large Decision Models

arXiv:2606.24962v1 Announce Type: new Abstract: Recent progress in large-scale sequence modeling has shown that a single model can learn useful representations across highly diverse data distributions

Transferability for General Reasoning: An Automated Curriculum for Multi-Domain RLVR

arXiv:2606.25178v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has been extended from single-domain training to multi-domain reasoning suites spanning mathematic

TTSA3R: Training-Free Temporal-Spatial Adaptive Persistent State for Streaming 3D Reconstruction

arXiv:2601.22615v3 Announce Type: replace Abstract: Streaming recurrent models enable efficient 3D reconstruction by maintaining persistent state representations. However, they suffer from catastrophi

Uncertainty-aware reinforcement learning for chemical language models

arXiv:2606.24990v1 Announce Type: new Abstract: Reinforcement Learning (RL) has become a powerful paradigm for de novo molecular design, enabling Chemical Language Models (CLMs) to navigate and explor

VolSplat: Rethinking Feed-Forward 3D Gaussian Splatting with Voxel-Aligned Prediction

arXiv:2509.19297v3 Announce Type: replace Abstract: Feed-forward 3D Gaussian Splatting (3DGS) has emerged as a highly effective solution for novel view synthesis. Existing methods predominantly rely o

What Does It Mean to Break a Distillation Defense?

arXiv:2606.25059v1 Announce Type: cross Abstract: Black-box LLMs (accessible only via API) are vulnerable to distillation attacks, in which an attacker queries the model and trains a student on its ou

When Do Conservation Laws Survive Learned Representations? Certified Horizons for Latent World Models

arXiv:2606.24945v1 Announce Type: new Abstract: We ask a representation-learning question about physical world models: when does a conservation law remain certifiable after a model learns a latent rep

When Does Synthetic Data Augmentation Improve Score-Based Imbalanced Classification?

arXiv:2606.26053v1 Announce Type: cross Abstract: Synthetic data augmentation is widely used to mitigate class imbalance, but its theoretical effects on score-based classification remain poorly unders

Why Multi-Step Tool-Use Reinforcement Learning Collapses and How Supervisory Signals Fix It

arXiv:2606.26027v1 Announce Type: new Abstract: Tool use enables large language models (LLMs) to perform complex tasks, and recent agentic reinforcement learning (RL) methods show promise for enhancin

safetyarxiv-cs-cl

A Comparative Study of Bayesian Contextual Bandits for Real-Time Warehouse Sorter Optimization

arXiv:2606.23977v1 Announce Type: new Abstract: Efficient sorter diversion control of automated material handling systems (MHS) is critical for optimizing operational efficiency in large-scale warehou

A global log for medical AI

arXiv:2510.04033v2 Announce Type: replace Abstract: Modern computer systems rely on syslog, a universal protocol that records critical events across heterogeneous infrastructure. Medicine's rapidly gr

A Robust Model-Based Approach for Continuous-Time Policy Evaluation with Unknown Levy Process Dynamics

arXiv:2504.01482v3 Announce Type: replace-cross Abstract: This paper develops a model-based framework for continuous-time policy evaluation (CTPE) in reinforcement learning, incorporating both Brownia

Abstractions of Queries in Ontology-Based Data Access

arXiv:2606.24618v1 Announce Type: new Abstract: In ontology-based data access (OBDA), multiple data sources are integrated via mappings to an ontology. We consider an OBDA setting based on existential

Accelerated Stochastic Min-Max Optimization Based on Bias-corrected Momentum

arXiv:2406.13041v3 Announce Type: replace Abstract: Lower-bound analyses for nonconvex strongly-concave minimax optimization problems have shown that stochastic first-order algorithms require at least

Agentic AI for Bilevel Long-Term Optimization of Policy-Driven Physical Layer Systems

arXiv:2606.24416v1 Announce Type: new Abstract: Network operators' changing policies, service requirements, and stringent real-time constraints render existing methods designed with fixed objectives a

Aligning Audio Captions with Human Preferences

arXiv:2509.14659v3 Announce Type: replace-cross Abstract: Current audio captioning relies on supervised learning with paired audio-caption data, which is costly to curate and may not reflect human pre

An Introduction to Causal Reinforcement Learning

arXiv:2606.24160v1 Announce Type: new Abstract: Causal inference provides a set of principles and tools that allow one to combine data and knowledge about an environment to reason with questions of co

An LLM-based Two-Stage Transformer Framework for Cross-Domain Bearing Fault Diagnosis with Limited Data

arXiv:2606.24459v1 Announce Type: cross Abstract: Bearing fault diagnosis faces critical challenges when dataset heterogeneity, operating condition variations, and limited labeled data occur simultane

safetyarxiv-cs-cl

Are LLM Evaluators Really Narcissists? Sanity Checking Self-Preference Evaluations

arXiv:2601.22548v4 Announce Type: replace-cross Abstract: Recent research has shown that large language models (LLMs) favor their own outputs when acting as judges, undermining the integrity of automa

ARIA: Adaptive Region-Based Importance Allocation for Conditional Diffusion Distillation

arXiv:2606.23898v1 Announce Type: cross Abstract: Distilling conditional diffusion models aims to transfer the behavior of a large teacher to a smaller student while preserving alignment across condit

AsyncOPD: How Stale Can On-Policy Distillation Be?

arXiv:2606.24143v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own rollouts guided by teacher feedback and is becoming increasingly important for large language m

Audio-visual Contrastive Alignment for Diffusion-based Visual-conditioned Speech Enhancement

arXiv:2606.23712v1 Announce Type: cross Abstract: Audio-visual speech enhancement (AVSE) exploits visual cues such as lip movements to recover speech in noisy environments. Recent work introduced diff

Beyond Trajectory Imitation: Strategy-Guided Policy Optimization for LLM Reasoning

arXiv:2606.24064v1 Announce Type: new Abstract: Distilling reasoning capabilities from strong to weak language models typically involves imitating specific solution trajectories, effectively transferr

Beyond U-Net: A Latent-Representation-Aligned Skip-Free Backbone for Flow-Matching Speech Enhancement

arXiv:2606.24745v1 Announce Type: cross Abstract: Generative models, particularly diffusion and score-based approaches, have recently achieved strong performance in speech enhancement, but their itera

Boosting Text-Driven Video Segmentation via Geometry-Aware Distillation

arXiv:2606.24464v1 Announce Type: new Abstract: Text-driven Referring Video Object Segmentation (RVOS) aims to locate and segment target objects in videos given natural language. However, existing mod

Breaking Shortcut Learning for Cross-Trial EEG-Guided Target Speech Extraction via Two-Stage Training

arXiv:2606.24164v1 Announce Type: cross Abstract: Recent end-to-end models for EEG-guided target speech extraction report impressive results, underscoring potential for neuro-steered hearing technolog

Breaking the Filter Bubble: A Semantic Pareto-DQN Framework for Multi-Objective Recommendation

arXiv:2606.24042v1 Announce Type: new Abstract: Recommender systems often induce filter bubbles and semantic homogenization by monolithically optimizing for immediate user engagement. Standard single-

Breaking the Mirror: Activation-Based Mitigation of Self-Preference in LLM Evaluators

arXiv:2509.03647v2 Announce Type: replace-cross Abstract: Large language models (LLMs) increasingly serve as automated evaluators, yet they suffer from 'self-preference bias': a tendency to favor thei

Bridging the Manifold Gap: Riemannian Residual Line Search for One-Step Image Editing

arXiv:2606.24844v1 Announce Type: new Abstract: One-step diffusion editors are fast because they avoid inversion and iterative optimization, but a single transport update must be aggressive enough to