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Reasoning Meets Personalization: Unleashing the Potential of Large Reasoning Model for Personalized Generation

arXiv:2505.17571v2 Announce Type: replace Abstract: Personalization is a critical task in modern intelligent systems, with applications spanning diverse domains, including interactions with large lang

safetyarxiv-cs-cl

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Research

ReCoG: Reciprocal Co-Evolution for Multimodal Graph Learning

DGX agent

arXiv:2608.22786v1 Announce Type: new Abstract: Multimodal graph learning requires jointly training over graph structure and heterogeneous node attributes, yet existing methods largely decouple these

researcharxiv-cs-lg

25 Aug 2026

Recovering Weighted Tangent Geometry from a Single-Scale Score Field

arXiv:2608.22334v1 Announce Type: cross Abstract: Near a smooth data manifold, one tangent space summarizes local geometry. At a branch point, the corresponding first-order object is instead a measure

local-aiarxiv-cs-lg

Redteaming Leading Arabic LLMs with ASAS

arXiv:2608.21985v1 Announce Type: new Abstract: As the adoption of large language models (LLMs) grows in Arabic-speaking regions, ensuring their safety and cultural alignment is increasingly critical.

Reference-free Human-Object Interaction Editing

model-releasesarxiv-cs-cv

arXiv:2503.09130v2 Announce Type: replace-cross Abstract: This paper presents InteractEdit, a novel framework for reference-free Human-Object Interaction (HOI) editing that tackles the challenging tas

Region-Weighted Losses and Model Fusion for Cross-Modal PET Attenuation Correction

arXiv:2608.21881v1 Announce Type: new Abstract: We describe our approach to the Big Cross-Modal Attenuation Correction (BIC-MAC) challenge, which asks for a pseudo-CT in Hounsfield Units to be synthes

researcharxiv-cs-cv

Register Shifts Break LLM Safety: A Bengali Benchmark with Culturally Grounded Harms

arXiv:2608.22335v1 Announce Type: cross Abstract: Bengali is the seventh-most-spoken language globally, yet LLM safety evaluation remains overwhelmingly English-centric. We introduce BanglaSafe, a ben

Reinforcement Learning on Benign Facts Amplifies Leakage of Memorized Private Data

arXiv:2608.21727v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is deployed to make models better at reasoning tasks, but its side effect on what models will di

Reinforcing the World's Edge: A Continual Learning Problem in the Multi-Agent-World Boundary

arXiv:2603.06813v2 Announce Type: replace Abstract: In a stationary decentralized Markov game, learning peers generate an episode-indexed sequence of induced MDPs for any focal agent. The joint game r

Relational Structural Causal Models

arXiv:2606.14892v2 Announce Type: replace Abstract: An artificial intelligence must have a model of its environment that is causal, supporting reasoning about interventions and counterfactuals, and al

Reliability- and Anatomy-Consistency-Aware Multimodal Learning for Robust Fracture Classification from Bangladeshi Radiographs

arXiv:2608.21482v1 Announce Type: cross Abstract: Background: Multimodal fracture classifiers may benefit from patient and anatomical metadata, but they can also become brittle when contextual informa

ReMAP: Self-supervised learning to unveil brain representations and vulnerability

arXiv:2608.22042v1 Announce Type: new Abstract: General anesthesia offers a rare opportunity to observe the human brain under a standardized, controlled perturbation. Yet intraoperative electroencepha

Agents

Repo2Skill-Evo: Repository Skills Go Stale in Silence

arXiv:2608.21964v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate over evolving software repositories, where success depends on repository-specific procedural know

agentsarxiv-cs-ai

Reproducible Vision-Guided 6-DoF Robotic Manipulator with a Mixed Stepper-Driver Architecture and Browser-Native Control

model-releasesarxiv-cs-cv

arXiv:2608.22799v1 Announce Type: cross Abstract: We present the NeuralNexus Arm, an open, low-cost 6-DOF robotic manipulator built by an undergraduate engineering team, together with the design decis

Reservoir of Importance: Learning Semi-Structured Sparsity with Differentiable Subset Sampling

arXiv:2608.23048v1 Announce Type: new Abstract: Semi-structured N:M sparsity has emerged as a practical direction for accelerating large language models (LLMs). However, existing learnable-mask approa

Residual-based attention in physics-informed neural networks

arXiv:2307.00379v2 Announce Type: replace Abstract: Driven by the need for more efficient and seamless integration of physical models and data, physics-informed neural networks (PINNs) have seen a sur

local-aiarxiv-cs-lg

Resilient Concurrent Causal Discovery for Topological Event Sequences

arXiv:2608.21815v1 Announce Type: new Abstract: Causal discovery on topological event sequences is crucial for ensuring the reliability of networks. However, existing methods struggle to capture the c

applicationsarxiv-cs-lg

Results of the 1st Asynchronous CASTLE Challenge at the Joint Egocentric Vision Workshop in Conjunction with CVPR 2026

arXiv:2608.22914v1 Announce Type: new Abstract: This report summarizes the contributions and results of the 1st Asynchronous CASTLE Challenge at the Joint Egocentric Vision Workshop in conjunction wit

researcharxiv-cs-cv

Rethinking Communication Metrics: How Should We Measure Meaning?

arXiv:2608.21626v1 Announce Type: new Abstract: Semantic communication shifts the objective of communication systems from accurate symbol reconstruction toward meaning preservation, task accomplishmen

researcharxiv-cs-lg

Retrieval-Augmented Classification of Environmental Mitigations in Hydropower Licensing Documents

arXiv:2608.23241v1 Announce Type: cross Abstract: Identifying and classifying environmental mitigation obligations in Federal Energy Regulatory Commission hydropower licensing documents is a labor-int

Retrieval-Augmented Visual Prompting: Guiding Foundation Models in Two-Photon Imaging

model-releasesarxiv-cs-cv

arXiv:2608.21970v1 Announce Type: new Abstract: Two-photon calcium imaging presents a challenging setting for foundation models: image appearance varies substantially across recordings and experimenta

Retrieval-grounded robot program generation and simulation-based correction via Model Context Protocol

arXiv:2608.21417v1 Announce Type: new Abstract: Flexible manufacturing requires industrial robots to be reprogrammed rapidly as product variants change. This paper presents a language-model-based work

Retrieval Needs Multivectors: An Exponential Separation

arXiv:2608.21494v1 Announce Type: cross Abstract: Recent works have highlighted the expressive limitations of embedding based retrieval models through both theoretical analyses and challenging benchma

RetroDFM-R: Reasoning-Driven Retrosynthesis Prediction with Large Language Models via Reinforcement Learning

arXiv:2507.17448v2 Announce Type: replace-cross Abstract: Retrosynthetic planning is a cornerstone of organic synthesis and drug discovery. Yet existing AI methods often rely on pattern matching rathe

Reviewing Model Collapse and Countermeasures

arXiv:2608.21366v1 Announce Type: new Abstract: Driven by massive amounts of web-scale data, generative AI (GenAI) has achieved remarkable progress, enabling various applications in diverse sectors. T

Reward-Free Continual Adaptation for Resilient Space Robots

arXiv:2608.23452v1 Announce Type: cross Abstract: Space robots operate in extreme environments where hardware degradation can critically compromise traditional control strategies. While continual rein

ReWorld: An Interactive World Model with Long-Horizon Memory

arXiv:2608.23565v1 Announce Type: new Abstract: An interactive world model must follow the user's actions, remember the places it has shown, and stream in real time. The tension is structural: control

applicationsarxiv-cs-ai

RIACT: A Responsible AI System for Personalized Study Habit Tracking and Early Burnout Signal Detection in University Students

arXiv:2608.21379v1 Announce Type: new Abstract: Student burnout is highly prevalent in higher education, with reported rates ranging from 12% to over 70% and consistently exceeding those of the workin

RIBOSPAN: A Long-Context RNA Foundation Model for Versatile RNA Modeling

arXiv:2608.22849v1 Announce Type: new Abstract: Full-length RNAs, particularly messenger RNAs, often exceed the context lengths used to pretrain existing RNA foundation models, limiting complete-trans

Right-Sizing LLM-Agent Decomposition in VAT Determination: A Pilot Controlled Sweep

arXiv:2608.23395v1 Announce Type: cross Abstract: Recent LLM-agent systems make conflicting design bets: decompose work across many narrow agents, or use one strong tool-using agent. This pilot studie

Risk-Sensitive Reinforcement Learning with Smoothed Quantile Objectives

arXiv:2608.22227v1 Announce Type: new Abstract: Reinforcement Learning (RL) has achieved tremendous success in recent years. However, the classical foundations of RL do not account for the risk sensit

safetyarxiv-cs-lg

RiskWorld: Object-Centric Latent World Modeling for Autonomous Driving Risk Identification

arXiv:2608.21414v1 Announce Type: cross Abstract: Autonomous driving risk identification aims to determine which observed object is likely to become safety-critical to the ego vehicle. Existing approa

local-aiarxiv-cs-lg

RoboRacer Arena: Scaling High-Fidelity Autonomous Racing in Isaac Sim

model-releasesarxiv-cs-ro

arXiv:2608.23040v1 Announce Type: new Abstract: RoboRacer offers a standardized platform for research using 1:10-scale autonomous vehicles, but the variety of available tracks hinders the process of a

RoboShape: Information-Theoretic Point Cloud Representations for Privacy-Aware Robot Perception

arXiv:2608.21380v1 Announce Type: cross Abstract: With the increased adoption of robotic agents operating in human environments by scanning and sharing 3D representations (e.g., for fleet learning, cl

applicationsarxiv-cs-ai

Robust Bimanual Vision-Language-Action Models via Embarrassingly Simple Modality Masking

arXiv:2608.22419v1 Announce Type: cross Abstract: Query-based Vision-Language-Action (VLA) models offer low-latency inference that is attractive for bimanual robotic manipulation, but we observe that

safetyarxiv-cs-cv

Robust Global Structure-from-Motion via View Graph Pruning

arXiv:2608.22054v1 Announce Type: new Abstract: Structure-from-Motion (SfM) aims to estimate camera poses and reconstruct 3D structures from a collection of unordered images. Compared with incremental

researcharxiv-cs-cv

Robust Lightweight Deep Learning Models for Oral Cancer Screening

arXiv:2608.21583v1 Announce Type: new Abstract: Oral cancer is a leading cause of mortality in low-to-middle-income countries, where a shortage of specialists delays diagnosis. While point-of-care scr

Robust Multi-Agent Reinforcement Learning for Small UAS Separation Assurance under GPS Degradation and Spoofing

arXiv:2603.28900v2 Announce Type: replace-cross Abstract: We address robust separation assurance for small Unmanned Aircraft Systems (sUAS) under GPS degradation and spoofing via Multi-Agent Reinforce

Robust performance metrics for imbalanced classification problems

arXiv:2404.07661v2 Announce Type: replace-cross Abstract: We show that established performance metrics in binary classification, such as Matthews' correlation coefficient (MCC), Cohen's kappa, the F-s

RobustGS: Unified Boosting of Feedforward 3D Gaussian Splatting under Low-Quality Conditions

arXiv:2508.03077v2 Announce Type: replace Abstract: Feedforward 3D Gaussian Splatting (3DGS) overcomes the limitations of optimization-based 3DGS by enabling fast and high-quality reconstruction witho

applicationsarxiv-cs-cv

Robustness Analysis of Agentic AI to Inconsistent and Incomplete Tool Responses

arXiv:2608.22676v1 Announce Type: new Abstract: Robustness to a bad tool return means answering it in the way that return calls for, which depends on how the tool went wrong. A tool that has failed an

Robustness of Anomaly Detection Models for Industrial Control Systems under Training-Time Data Contamination

arXiv:2608.23547v1 Announce Type: cross Abstract: Machine-learning-based anomaly detection is increasingly used in industrial control systems (ICS), yet most studies assume that detector training data

Robustness of IR Models to Collection Growth

arXiv:2608.23419v1 Announce Type: cross Abstract: Information Retrieval (IR) systems seek to identify relevant documents within a collection. In practical applications, collections are dynamic, with d

researcharxiv-cs-cl

Role-Specialized Mixture-of-Agents with Open-Weight LLMs for Clinical Prediction

arXiv:2608.22176v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly applied to clinical prediction tasks such as in-hospital mortality and readmission from electronic health

local-aiarxiv-cs-ai

ROS2SmolVLA: Enabling Small Vision-Language-Action Models for Integration into Industrial-Grade Lightweight Robots

arXiv:2608.23320v1 Announce Type: new Abstract: Industrial demand changes the paradigms of production. Due to smaller batch sizes and more variations in products, companies face a growing challenge to

applicationsarxiv-cs-ro

RPL: Learning Robust Humanoid Perceptive Locomotion on Challenging Terrains

arXiv:2602.03002v2 Announce Type: replace Abstract: Humanoid perceptive locomotion has made significant progress and shows great promise, yet achieving robust multi-directional locomotion on complex t

safetyarxiv-cs-ro

Hardware

RS^3-Prune: Read-Sparse, Store-Sparse Token Pruning for Video Object Segmentation

arXiv:2608.22526v1 Announce Type: new Abstract: We introduce RS^3-Prune, a training-free token-pruning recipe that instantiates as a small set of inference time hooks atop existing video object segmen

hardwarearxiv-cs-cv

RSTGCN: Railway-centric Spatio-Temporal Graph Convolutional Network for Train Delay Prediction

arXiv:2510.01262v2 Announce Type: replace-cross Abstract: Accurate prediction of train delays is critical for efficient railway operations. While earlier approaches have largely focused on forecasting