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Resolving sources of uncertainty in AI weather forecasting

arXiv:2511.14218v2 Announce Type: replace Abstract: Weather forecast uncertainty arises from imperfect analyses and forecast models, but ensemble spread alone does not reveal how distinct sources rela

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ReST-RL: Reinforcing LLM Reasoning through Unified Self-Training and Value-Guided Search

DGX agent

arXiv:2508.19576v3 Announce Type: replace-cross Abstract: With respect to improving the reasoning accuracy of LLMs, the representative reinforcement learning (RL) method - Group Relative Policy Optimi

safetyarxiv-cs-lg

9 Sept 2026

Rethinking Learned Occupancy in Autonomous Active Mapping with Observation-Gated Filtering

arXiv:2609.09069v1 Announce Type: cross Abstract: Autonomous 3D active mapping requires a space robot to choose where to sense while building the geometry needed for navigation. Learned occupancy comp

Rethinking One-Shot Federated Graph Learning: Training-Free Statistical Estimation

arXiv:2609.06154v1 Announce Type: new Abstract: One-shot federated graph learning generally aims to train Graph Neural Networks (GNNs) across clients with disconnected subgraphs in a single communicat

Rethinking Safety for Generalist Robots

arXiv:2609.06326v1 Announce Type: cross Abstract: Generalist robots promise to transform our society: the same system that prepares a meal or folds laundry might also repair a car, inspect infrastruct

Rethinking the Evaluation of Efficiency Methods for Multi-Agent Systems

arXiv:2609.05933v1 Announce Type: new Abstract: Efficiency is increasingly important for Large Language Model (LLM)-based multi-agent systems (MAS), as larger models and more agents introduce substant

Retrieval-augmented Decoding for Improving Truthfulness in Open-ended Generation

arXiv:2508.02184v3 Announce Type: replace Abstract: Ensuring truthfulness in large language models (LLMs) remains a critical challenge for reliable text generation. While supervised fine-tuning and re

REVA-PO: Stabilizing Reinforcement Learning for Chest X-ray Report Generation

arXiv:2607.10147v2 Announce Type: replace Abstract: Automated chest X-ray report generation has recently benefited from reinforcement learning (RL) and large language models. However, RL training ofte

safetyarxiv-cs-cv

RevalExo: A Functional Daily-Activity Benchmark for Inertial and Visual Locomotion Mode Recognition in Older Adults and Clinical Cohorts

arXiv:2609.08090v1 Announce Type: cross Abstract: Assistive devices for people with mobility impairments, such as powered exoskeletons, rely on accurate locomotion mode recognition to adapt control st

Revisiting Spectral Representations in Generative Diffusion Models

arXiv:2609.08253v1 Announce Type: new Abstract: Diffusion models have shown remarkable performance on diverse generation tasks. Recent work finds that imposing representation alignment on the hidden s

Revisiting Thinning Methods for Kernel Learning Problems

arXiv:2609.07432v1 Announce Type: new Abstract: Kernel methods are widely used because of their strong theoretical guarantees and empirical performance. However, their high computational cost limits t

RFS-UNet: Decoder-Conditioned High-Resolution Skip Recalibration for Bone-Selective DRR Synthesis

arXiv:2609.08044v1 Announce Type: new Abstract: Bone-selective digitally reconstructed radiograph (DRR) synthesis depends on high-resolution encoder detail, yet static skips cannot condition reuse on

researcharxiv-cs-cv

RGB Input Pipelines: Throughput, GPU Memory, and Transformation Coverage

arXiv:2609.06635v1 Announce Type: cross Abstract: An image-augmentation pipeline must deliver a complete batch before a model can use it. We compare seven input paths from five libraries, starting wit

Agents

Riemannian Optimization for Multi-Player Quantum Games on Product Unitary Manifolds

arXiv:2609.07397v1 Announce Type: cross Abstract: Quantum game theory is an extension of classical game theory that uses quantum principles in game theory. The Eisert-Wilkens-Lewenstein (EWL) quantum

agentsarxiv-cs-lg

Risk-Conditioned Fine-Tuning of Large Language Models

arXiv:2609.08064v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in settings where rare but severe harmful generations can have significant consequences. Existing

RoboCousin: Build Your Own Simulation Playground for Robust Bimanual Robotic Manipulation

arXiv:2609.08339v1 Announce Type: new Abstract: Bimanual manipulation policies require large and diverse training datasets, yet collecting demonstrations on physical robots is expensive and difficult

researcharxiv-cs-ro

RoboDreamer: Anticipatory Humanoid Locomotion with Predictive State-Space Models

arXiv:2609.07096v1 Announce Type: new Abstract: Humanoid locomotion requires control policies that remain stable under imperfect sensing while exploiting temporal context for consistent motion. We pre

RoboSense: Leveraging Robotaxi Fleets as Drive-by Sensors for Urban Traffic Monitoring

arXiv:2609.06813v1 Announce Type: new Abstract: Urban traffic monitoring plays a critical role in safety analysis, congestion management, and incident response. The growing deployment of robotaxis cre

Robots Influencing Humans to Reveal their Goals during Collaboration and Competition

arXiv:2609.05519v1 Announce Type: new Abstract: We propose a unified strategy for fast goal inference in human-robot interaction. The core idea is to drive the human toward Critical Decision Points (C

Robust conditional dimension reduction for dissimilarity data

arXiv:2609.06284v1 Announce Type: cross Abstract: Conditional dimension reduction (cDR) learns low-dimensional latent coordinates while accounting for observed covariates that represent known sources

Agents

Robust Conformal Consensus: Multi-Agent LLM-as-a-Judge Interval Evaluation with Conformal Prediction

arXiv:2609.06367v1 Announce Type: new Abstract: LLM-as-a-Judge has emerged as a promising paradigm for evaluating natural language generation. However, the uncertainty associated with such evaluations

agentsarxiv-cs-lg

Applications

Robust Decentralized Federated Distillation via Multi-Modality Knowledge Collaboration

arXiv:2609.07230v1 Announce Type: new Abstract: This paper propose a robust decentralized federated distillation method that enables clients with heterogeneous models to collaborate through prediction

applicationsarxiv-cs-lg

Local Ai

Robust Decentralized Personalized Federated Learning via Prediction-Constrained Neighborhood Collaboration

arXiv:2609.07312v1 Announce Type: new Abstract: This paper proposes a robust decentralized personalized federated learning method R-DPFL, that enables clients to reduce the impact of Byzantine attacks

local-aiarxiv-cs-lg

Robust Dynamic Expansion for Continual Learning under Backdoor Attacks via Purification and Selective Recovery

arXiv:2609.06346v1 Announce Type: new Abstract: Continual learning (CL) enables models to acquire new knowledge from sequentially arriving tasks while retaining previously learned knowledge. However,

Robust Immersive Bilateral Teleoperation of Beyond-Human-Scale Systems with Enhanced Transparency and Sense of Embodiment

arXiv:2505.14486v3 Announce Type: replace Abstract: This paper presents an immersive bilateral teleoperation framework for beyond-human-scale manipulators, combining motion/force transparency with enh

researcharxiv-cs-ro

Applications

Robust Optical Flow Computation: A Higher-Order Differential Approach

arXiv:2410.09563v2 Announce Type: replace Abstract: In the domain of computer vision, optical flow stands as a cornerstone for unraveling dynamic visual scenes. However, the challenge of accurately es

applicationsarxiv-cs-cv

Robust Vision Systems for Connected and Autonomous Vehicles: Security Challenges and Attack Vectors

arXiv:2602.09740v3 Announce Type: replace Abstract: Connected and Autonomous Vehicles (CAVs), which is critical for achieving Level-5 autonomous driving. Safe and reliable CAV navigation depends on ro

Robustness of LLM-Generated SystemVerilog Assertions to Semantics-Preserving RTL Transformations

arXiv:2609.05658v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being explored for automating SystemVerilog Assertion (SVA) generation, yet most evaluations report correc

Hardware

RoLA: Rotary-Positioned Low-Rank Linear Attention for Efficient Diffusion Transformers

arXiv:2609.06712v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) achieve strong video generation quality, but their dense spatiotemporal self-attention scales quadratically with sequence

hardwarearxiv-cs-cv

Role-Specific Predictive Geometries for Nonstationary Multivariate Graph-Signal Forecasting

arXiv:2609.06519v1 Announce Type: new Abstract: Forecasting multivariate graph signals is challenging when node-level trajectories are nonstationary but stable relations persist across nodes and featu

Rollcast: Proper-Score Gated Rolling Anchors for Adaptive Probabilistic Time-Series Forecasting

arXiv:2609.05561v1 Announce Type: cross Abstract: Rollcast is a probabilistic forecasting method for univariate time series that combines a compact set of rolling statistical anchors rather than relyi

Agents

RoMu4o: A Robotic Manipulation Unit For Orchard Operations Automating Proximal Hyperspectral Leaf Sensing

arXiv:2501.10621v2 Announce Type: replace-cross Abstract: Driven by the need to address labor shortages and meet the demands of a rapidly growing population, robotic automation has become a critical c

agentsarxiv-cs-cv

RoPE attention is an exact forward-pass gradient step with softmax intact

arXiv:2609.06685v1 Announce Type: cross Abstract: We derive an exact gradient-step representation of the RoPE-softmax forward pass. For every deterministic RoPE-softmax attention head with arbitrary a

Rotation-free Online Handwritten Character Recognition Using Linear Recurrent Units

arXiv:2602.01533v2 Announce Type: replace Abstract: Online handwritten character recognition leverages stroke order and dynamic features, which generally provide higher accuracy and robustness compare

researcharxiv-cs-cv

Routing Dense Layouts with History-Aware Offline Reinforcement Learning using LSTM

arXiv:2609.08232v1 Announce Type: cross Abstract: Detailed routing remains a dominant runtime bottleneck in physical design due to increasing complexity of design rules. Modern routers can struggle to

S^3F-Net: A Multi-Modal Approach to Medical Image Classification via Spatial-Spectral Summarizer Fusion Network

arXiv:2509.23442v2 Announce Type: replace-cross Abstract: Convolutional Neural Networks have become a cornerstone of medical image analysis due to their proficiency in learning hierarchical spatial fe

researcharxiv-cs-cv

SAEs Can Improve Unlearning: Dynamic Sparse Autoencoder Guardrails for Precision Unlearning in LLMs

arXiv:2504.08192v2 Announce Type: replace Abstract: Machine unlearning is a promising approach to improve LLM safety by removing unwanted knowledge from the model. However, prevailing gradient-based u

SAEScientist-Bench: Can AI Agents Conduct Autonomous SAE Interpretability Research?

arXiv:2609.09113v1 Announce Type: cross Abstract: While research on recursive self-improvement (RSI) has predominantly automated model training pipelines, reliable autonomous development demands a mis

Safe Consensus of Cooperative Manipulation with Hierarchical Event-Triggered Control Barrier Functions

arXiv:2603.06356v2 Announce Type: replace Abstract: Cooperative transport and manipulation of heavy or bulky payloads by multiple manipulators requires coordinated formation tracking, while simultaneo

Safe Task Planning with Long-Term Graph Memory for Embodied Agents

model-releasesarxiv-cs-ro

arXiv:2609.08444v1 Announce Type: new Abstract: Large language models (LLMs) and vision-language models (VLMs) have significantly advanced zero-shot task planning for embodied agents. However, most LL

SAFEGuard: Detect Optimization-Based Jailbreak Attacks Through Harmful Semantic Analysis and Fluency Measurement

arXiv:2609.05850v1 Announce Type: new Abstract: Despite the significant efforts devoted to aligning large language models (LLMs) with human values and ensuring safe deployment, recent work has reveale

SAFER-Activities: A Dataset for Smart Assessment of Fall Events and Routine Activities

arXiv:2609.08038v1 Announce Type: new Abstract: Smart healthcare monitoring systems require precise action recognition to ensure well-being and timely intervention in critical situations such as falls

SAFIRE: Safety-Critical Benchmark for Fine-grained Fire and Smoke Understanding in Multimodal LLMs

arXiv:2609.07823v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) show strong progress on vision-language tasks, yet their reliability in safety-critical settings remains undere

Local Ai

SAM3-O2D2: Zero-Shot Object Out-of-Distribution Detection by Object Class Prompting of the SAM3-Image Model

arXiv:2609.08281v1 Announce Type: new Abstract: Object detectors have shown remarkable performance in various fields, among these medical imaging, surveillance, and autonomous driving. However, they a

local-aiarxiv-cs-cv

Scalability Analysis of Distributed Kolmogorov-Arnold Network Training on High-Performance Computing Systems

arXiv:2609.07740v1 Announce Type: cross Abstract: Kolmogorov-Arnold Networks (KANs) replace the fixed activation functions and linear weights of Multi-Layer Perceptrons (MLPs) with learnable univariat

Scaling 3D Generative Priors to Large-Scale Scene Meshes from Multi-View Images

arXiv:2609.06385v1 Announce Type: new Abstract: Pretrained 3D generative models produce detailed geometry and appearance but are primarily designed for object-centric generation within a limited spati

safetyarxiv-cs-cv

Scaling Optimal Classification Trees via Adaptive Feature and Sample Reduction

arXiv:2609.05826v1 Announce Type: new Abstract: Dynamic programming for optimal classification trees becomes computationally expensive as the numbers of features and training samples increase. We deve

Scene Graph-Driven Haptic Feedback for Safety Enhancement in Robotic Ophthalmic Surgery via Physically Simulated iOCT

arXiv:2609.07857v1 Announce Type: cross Abstract: Robotic ophthalmic surgery offers high precision but introduces a 'sensory gap' by decoupling the surgeon from their instrument, resulting in a loss o

safetyarxiv-cs-cv