Search: “safety”

Modelling Human Values for Value-Aware Multi-Agent Systems

arXiv:2402.06359v2 Announce Type: replace Abstract: One of today's most pressing societal challenges is building AI systems whose behaviour, or the behaviour it enables within communities of interacti

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MOPD: Multi-Teacher On-Policy Distillation for Capability Integration in LLM Post-Training

DGX agent

arXiv:2606.30406v1 Announce Type: new Abstract: Modern large language models (LLMs) rely on reinforcement learning during post-training to push specific capabilities, yet integrating multiple capabili

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30 Jun 2026

MOSAIC: Orchestrating Collaborative Knowledge Tracing with Hierarchical Semantic Alignment

arXiv:2606.29049v1 Announce Type: new Abstract: Knowledge Tracing (KT) is important for personalized education but traditionally suffers from two key limitations: a reliance on shallow ID-based repres

MR-IQA: A Unified Margin View of Regression and Ranking for Blind Image Quality Assessment

arXiv:2606.29760v1 Announce Type: new Abstract: Blind image quality assessment (BIQA) is commonly built on two basic learning paradigms: regression and ranking. Regression calibrates absolute scores,

muFlow: Leveraging Average Images for Improving Generalisation of Deepfake Faces Detectors

arXiv:2606.30528v1 Announce Type: new Abstract: Current generative models, including GANs and diffusion models, have reached an outstanding level of photorealism, posing significant risks to privacy a

Multimodal Large Language Model driven Radiology Report Generation with Clinical Knowledge Enhancement

arXiv:2403.06728v2 Announce Type: replace Abstract: Radiology report generation (RRG) has attracted significant attention due to its potential to reduce the workload of radiologists. The performance o

Multimodal Representation Alignment for Cross-modal Information Retrieval

arXiv:2506.08774v2 Announce Type: replace-cross Abstract: Different machine learning models can represent the same underlying concept in different ways. This variability is particularly valuable for i

Neuromorphic Energy-Aware Learning for Adaptive Deep Brain Stimulation

arXiv:2606.28600v1 Announce Type: cross Abstract: Neuromorphic and edge computing research has focused on reducing the inference cost of neural network controllers, yet in physical closed-loop systems

Node-to-Neighborhood Semantic Consistency: Text-Topology Alignment for TAGs Anomaly Detection

arXiv:2606.30009v1 Announce Type: new Abstract: Graph anomaly detection (GAD) on text-attributed graphs (TAGs) is vital for applications such as fraud detection and academic integrity verification. Ex

NoiseTilt: Noise-Tilted Reverse Kernels for Diffusion Reward Alignment

arXiv:2606.18066v2 Announce Type: replace Abstract: We introduce the Noise-Tilted Reverse Kernel (NTRK), a reward-guided diffusion sampler that injects reward gradients through the noise term, leaving

Offline Reinforcement Learning of High-Quality Behaviors Under Robust Style Alignment

arXiv:2601.22823v2 Announce Type: replace-cross Abstract: We study offline reinforcement learning of style-conditioned policies using explicit style supervision via subtrajectory labeling functions. I

Online Experiential Learning for Language Models

arXiv:2603.16856v2 Announce Type: replace Abstract: The prevailing paradigm for improving large language models relies on offline training with human annotations or simulated environments, leaving the

Persona-Trained Monte Carlo: Estimating Market-Outcome Distributions via Swarms of Persona-Conditioned Neural Policy Bots in a Limit Order Book

arXiv:2606.29556v1 Announce Type: new Abstract: We propose Persona-Trained Monte Carlo (PTMC), a method for estimating distributions of market-outcome statistics by repeatedly simulating limit-order-b

Pessimism's Paradox: Conservative Offline Training Amplifies Reward Hacking During Online Adaptation in Reasoning Models

arXiv:2606.30627v1 Announce Type: cross Abstract: Conservative offline training is widely advocated as a safe foundation for subsequent online adaptation: if a policy stays close to well-supported beh

PHF: Privileged Hidden Flow for On-Policy Self-Distillation

arXiv:2606.29340v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a reasoning model on rollouts sampled from its own policy by matching a privileged teacher that also sees veri

Phonological Perception of Sign Language Models

arXiv:2606.28667v1 Announce Type: new Abstract: Sign languages are compositional systems where meaning arises by combining sublexical phonological parameters, such as handshape, location, and movement

Physics Models for Sim-to-Real Transfer in Professional-Level Robot Table Tennis

arXiv:2606.28805v1 Announce Type: new Abstract: At competitive speeds and spins, a table tennis ball follows complex, counterintuitive trajectories that a robot must track and precisely counter within

PolarAPP: Beyond Polarization Demosaicking for Polarimetric Applications

arXiv:2603.23071v2 Announce Type: replace Abstract: Polarimetric imaging enables advanced vision applications such as normal estimation and de-reflection by capturing unique surface-material interacti

Pondering the Way: Spatial-perceiving World Action Model for Embodied Navigation

arXiv:2606.29908v1 Announce Type: cross Abstract: Existing world model-based planners for visual navigation typically follow a verification-centric paradigm, decoupling goal intent from trajectory syn

Predictive Objectives Discard Exogenous Control-Relevant Features: A Controlled Mechanistic Study

arXiv:2606.30068v1 Announce Type: new Abstract: Joint-embedding predictive (JEPA-style) objectives learn representations by predicting future latents. In doing so they can discard features that are ex

Priced Motion Through Optimal Faces: A Normal-Fan Geometry for Non-Stationary Adversarial MDPs

arXiv:2606.29092v1 Announce Type: cross Abstract: In a changing decision problem, standard dynamic-regret analyses have often equated the cost of non-stationarity to how far loss moves. However, it is

Process Advantage Signal Shaping: A Paradigm-Agnostic Middleware for Process-Supervised RL in LLM Reasoners

arXiv:2606.29296v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) is a default recipe for process-supervised reinforcement learning of LLM reasoners, and dense process supervis

PromptGNN-sim: Deep Fusion and Alignment of GNN and LLMs for Text-Attributed Graph Learning

arXiv:2606.30291v1 Announce Type: new Abstract: Text-Attributed Graphs (TAGs) combine textual semantics with graph structure and are central to many graph learning tasks. However, existing fusion meth

ProSpec RL: Plan Ahead, then Execute

arXiv:2407.21359v2 Announce Type: replace-cross Abstract: Imagining potential outcomes of actions before execution helps agents make more informed decisions, a prospective thinking ability fundamental

PS-PPO: Prefix-Sampling PPO for Critic-Free RLHF

arXiv:2606.29758v1 Announce Type: cross Abstract: Reinforcement Learning from Human Feedback (RLHF) for Large Language Models increasingly relies on critic-free methods as a practical alternative to a

Rank-Aware Hyperbolic Alignment for Vision-Language Dataset Distillation

arXiv:2606.29464v1 Announce Type: cross Abstract: Vision-language dataset distillation (VLDD) compresses a large image-text paired dataset into a small set of synthetic pairs that can efficiently trai

ReactiveBFM: Reactive Closed-Loop Motion Planning Towards Universal Humanoid Whole-Body Control

arXiv:2606.30362v1 Announce Type: cross Abstract: While current Behavior Foundation Models (BFMs) provide robust control priors for humanoids, they only execute pre-defined reference motions. As a res

REAR: Test-time Preference Realignment through Reward Decomposition

arXiv:2606.30339v1 Announce Type: new Abstract: Aligning large language models (LLMs) with diverse user preferences is a critical yet challenging task. While post-training methods can adapt models to

Regime-Aware Peer Specialization for Robust RAG under Heterogeneous Knowledge Conflicts

arXiv:2606.30518v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves language models by grounding generation in external context. However, it can be fragile when the retrieved

ReGuide: From Test-Time Guidance to Self-Improving Diffusion Policies

arXiv:2606.28939v1 Announce Type: new Abstract: Behavior-cloned diffusion policies are expressive but remain vulnerable to covariate shift: small deviations from demonstrated states can compound into

ReMAP-PET: Beyond Visual Understanding -- Learning Region-Guided Metabolic Alignment Semantics from Brain PET

arXiv:2606.29577v1 Announce Type: cross Abstract: Positron Emission Tomography (PET) reveals brain metabolism and is clinically central to neurodegenerative disease assessment, yet existing 3D brain f

RePer-360: Releasing Perspective Priors for 360^irc Depth Estimation via Self-Modulation

arXiv:2603.05999v2 Announce Type: replace Abstract: Recent depth foundation models trained on perspective imagery achieve strong performance, yet generalize poorly to 360^irc images due to the substan

Reproducing FACTER: Fairness via Conformal Thresholding and Prompt Repair

arXiv:2606.28620v1 Announce Type: cross Abstract: Fayyazi et al. (2025) recently proposed FACTER, a model-agnostic framework designed to jointly enforce fairness and statistical coverage in LLM-based

Resolution Thresholds in VLM Detection of Harmful ASCII Art Across Construction Modes and Languages

arXiv:2606.29649v1 Announce Type: new Abstract: Large Vision-Language Models (VLMs) are increasingly deployed as content moderation tools, yet they remain vulnerable to jailbreak attacks in which harm

RetrDex: Efficient Object Retrieval in Cluttered Scenes with a Dexterous Hand

arXiv:2502.18423v3 Announce Type: replace Abstract: Retrieving objects buried beneath clutter is both challenging and time-consuming, as complex support relationships make manipulation particularly di

Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation

arXiv:2602.09305v2 Announce Type: replace Abstract: Large Language Models (LLMs) demonstrate transformative potential, yet their reasoning remains inconsistent and unreliable. Reinforcement learning (

Rigel: Self-Distilled Score Adaptation for Image and Video Captioning Evaluation

arXiv:2606.29997v1 Announce Type: new Abstract: Automatic evaluation of image and video captioning is essential for benchmarking multimodal systems, although standard evaluation metrics show limited a

RoamFlow: Reinforcement-Aligned One-Step Action MeanFlow Policy for Image-Goal Navigation

arXiv:2606.29934v1 Announce Type: new Abstract: Image-goal navigation is a key challenge in embodied robotics, where an agent must reach a target specified solely by a goal image. While existing reinf

RoboPIN: Grounded Embodied Reasoning via Pinned Chain-of-Thought

arXiv:2606.15753v2 Announce Type: replace Abstract: Embodied reasoning requires models to perceive task-relevant objects and spaces in physical environments and maintain consistent visual grounding th

Robotic Arm-Based Spectral Sensing for Strawberry Positioning and Non-Destructive Sweetness Measurement

arXiv:2606.28555v1 Announce Type: new Abstract: Accurate assessment of sweetness is essential for quality control in agriculture, yet conventional methods rely on destructive sampling and are difficul

Robust Extended Kalman Filter for Land Navigation Using Massive Array of MEMS IMUs

arXiv:2606.29271v1 Announce Type: cross Abstract: We propose a robust Extended Kalman Filter (EKF) architecture for land navigation using an array of hundreds of low-cost micro-electromechanical syste

Robust Strategic Classification under Decision-Dependent Cost Uncertainty

arXiv:2606.30136v1 Announce Type: new Abstract: Humans facing algorithmic decision systems have been found to ``game'' them by altering their input data (at a cost to them) in order to favorably chang

Robust Trajectory Distillation: Hybrid Reweighting Meets Teacher-Inspired Targets

arXiv:2606.29837v1 Announce Type: new Abstract: Dataset distillation (DD) condenses large corpora into compact, information-rich subsets for efficient training and reuse. However, under noisy supervis

Robust Zero-shot Anomaly Detection under Limited Auxiliary Anomaly Priors

arXiv:2606.29428v1 Announce Type: new Abstract: Zero-shot anomaly detection aims to identify defects in arbitrary novel domains; however, existing models assume that the auxiliary data contains a rich

Robustness and Structure Preservation in Flow-Based Generative Models via Wasserstein Path-Space Divergences

arXiv:2410.01244v2 Announce Type: replace-cross Abstract: We introduce a novel Wasserstein-1 (W_1) path-space divergence for stochastic and deterministic dynamics and establish a Wasserstein Uncertain

SA-VLA: State-aware tokenizer for improving Vision-Language-Action Models' performance

arXiv:2606.30113v1 Announce Type: cross Abstract: Discrete action tokenization provides a compact interface for autoregressive VLA policies, but accurately recovering continuous robot actions from dis

SAFE-DiT: Semantics-Aware Fast-path Execution for High-Resolution Diffusion Transformers

arXiv:2606.29360v1 Announce Type: new Abstract: High-resolution Diffusion Transformer (DiT) inference contains substantial spatial redundancy, but many spatially adaptive implementations encode region

SARLO-80: Worldwide Slant SAR Language Optic Dataset 80cm

arXiv:2606.20523v2 Announce Type: replace-cross Abstract: Multimodal foundation models have advanced rapidly thanks to large optical benchmarks, but comparable resources for synthetic aperture radar (