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arXiv:2510.04724v2 Announce Type: replace Abstract: This paper introduces a methodology for task-specific design optimization of multirotor Micro Aerial Vehicles. By leveraging reinforcement learning,

applicationsarxiv-cs-ro

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Performance uncertainty in medical image analysis: a large-scale investigation of confidence intervals

DGX agent

arXiv:2601.17103v2 Announce Type: replace Abstract: Performance uncertainty quantification is essential for reliable validation and eventual clinical translation of medical imaging artificial intellig

researcharxiv-cs-cv

27 Aug 2026

Applications

Phantom Navigator: Stealthy and Precise Unmanned Aerial Vehicle Redirection with Real-Time Tracking and GPS Spoofing

arXiv:2608.26011v1 Announce Type: new Abstract: Redirecting unmanned aerial vehicles (UAVs) from their intended mission trajectories has been an active area of research. However, existing UAV redirect

applicationsarxiv-cs-ro

Phase-Consistent Magnetic Spectral Learning for Multi-View Clustering

arXiv:2602.18728v2 Announce Type: replace-cross Abstract: Unsupervised multi-view clustering (MVC) aims to partition data into meaningful groups by leveraging complementary information from multiple v

safetyarxiv-cs-cv

PhaseShift: Topology-Aware Data Harmonization and Model Consolidation Across Signalized Intersections

arXiv:2608.25275v1 Announce Type: cross Abstract: Learned traffic-behavior models are commonly trained separately for each intersection, creating model portfolios that cannot share evidence across sit

researcharxiv-cs-ro

Physics-Informed Error Field Learning: A Post-Training Optimization Framework for Physics-Informed Neural Networks

arXiv:2608.24970v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) have emerged as an important class of numerical methods for solving partial differential equations (PDEs). Howe

Physics-Informed Foresight Pruning for Sparse PINN Solvers of Nonlinear PDEs

arXiv:2608.25564v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) often rely on over-parameterized models to optimize coupled solution and differential-residual objectives, leav

PIVOT: A Multi-Trajectory Dataset and Testbed for Pose, Intrinsics, and Novel Viewpoint Evaluation in Real-World 3D Reconstruction

model-releasesarxiv-cs-cv

arXiv:2608.25401v1 Announce Type: new Abstract: Neural radiance fields (NeRFs), 3D Gaussian Splatting (3DGS), and related novel-view synthesis methods are commonly evaluated under capture and reconstr

Local Ai

Planetary Prediction Engine: Autonomous Geospatial Prediction via Intelligent Data Selection and Foundation Model Embeddings

arXiv:2608.26088v1 Announce Type: cross Abstract: Addressing critical global challenges, from food security and disaster risk to disease outbreaks and socio-economic vulnerability, demands high-fideli

local-aiarxiv-cs-lg

Plans You Can Check: Verifier-Grounded Learning of an Open-Weight Planner for Executable Video-Editing

arXiv:2608.25622v1 Announce Type: cross Abstract: Practical video editing is not only pixel generation: an editor must turn a brief, a clip pool, music metadata, and hard constraints into an executabl

PlanSightRAG: A Visual-First Multimodal RAG for Automating Question Answering and Compliance Checking for Civil Standard Plans

arXiv:2608.26091v1 Announce Type: cross Abstract: Civil infrastructure compliance checking has long relied on engineers manually reading legacy 2D plans; however, OCR-based automation strips away the

Pointing the Way, Hiding the Destination: Practical Private Dense Retrieval at Scale

arXiv:2608.25735v1 Announce Type: cross Abstract: Hosted retrieval-augmented generation (RAG) and semantic search allow users to query valuable provider-held corpora, raising two competing demands: to

PointRL: Learning Point-Level Vision-Language Grounding from Verifiable Annotation Evidence

arXiv:2608.25299v1 Announce Type: new Abstract: Vision-language models (VLMs) increasingly rely on point coordinates as a compact and executable interface for visual grounding in GUI interaction, robo

researcharxiv-cs-cv

PonsRAG: A Pons-Inspired RAG Bridging Cognitive Islands for Coordinated Long Narrative Reasoning

arXiv:2608.25486v1 Announce Type: cross Abstract: Long Narrative Reasoning is an essential capability for processing and reasoning over complex narratives. While retrieval-augmented generation provide

Pose-Anchored Optical Flow for Low-Latency Human Action Anticipation in Human-Robot Teaming

model-releasesarxiv-cs-cv

arXiv:2608.25495v1 Announce Type: new Abstract: Human-robot interaction (HRI) requires robots to interpret human actions early in their execution in order to respond safely, efficiently, and naturally

Precipitation Downscaling Using Foundation Model-Conditioned Diffusion

arXiv:2608.25858v1 Announce Type: new Abstract: High-resolution precipitation fields are essential for hydrological impact assessment, yet global climate model outputs are too coarse and biased for di

researcharxiv-cs-cv

Prefix-Denoising Consistency: Test-Time Verification for Diffusion Language Models

arXiv:2608.25311v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) have recently become increasingly competitive with autoregressive (AR) models, and even outperform them on certain task

Prefix Sliding for efficient test-time scaling

arXiv:2608.26070v1 Announce Type: new Abstract: Test-time scaling uses extra test-time compute to improve performance, such as letting language models reason longer when solving a problem. As models k

PreResQ-R1: Response-Preference Disentangled Ranking-and-Scoring Reinforcement Optimization for Robust Visual Quality Assessment

arXiv:2511.05393v2 Announce Type: replace Abstract: Visual Quality Assessment (QA) seeks to predict human perceptual judgments of visual fidelity. While recent multimodal large language models (MLLMs)

safetyarxiv-cs-cv

PRISM: Projection-Integrated Sampling-Based MPC with Bayesian Cost Tuning for Bimanual Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.25666v1 Announce Type: new Abstract: Bimanual manipulation in cluttered, contact-rich environments remains challenging because it requires coordinated motion generation, interaction-aware p

Provable Privacy Attacks on Trained Shallow Neural Networks

arXiv:2410.07632v3 Announce Type: replace Abstract: We study what provable privacy attacks can be shown for trained 2-layer ReLU neural networks, focusing on two types of attacks: membership inference

safetyarxiv-cs-lg

Provenance Before Prose: Claim-Locked Reporting

arXiv:2608.25336v1 Announce Type: new Abstract: Large language models (LLMs) can fluently verbalize statistical evidence, yet statistical reports can still drift numerical values, invert effect direct

Agents

Quantum-Inspired Modeling of Driving Behavior

arXiv:2608.25907v1 Announce Type: new Abstract: Driver behavior is heterogeneous, context-dependent, and changes over time, and these properties shape the traffic phenomena we observe. Most models, ho

agentsarxiv-cs-lg

Quantum Scrambling Born Machine

arXiv:2602.17281v2 Announce Type: replace-cross Abstract: Quantum generative modeling, where the Born rule naturally defines probability distributions through measurement of parameterized quantum stat

Query-Side Attacks on GNN-Based KGQA: Tracing Failures from Entity Linking to Answer Generation

arXiv:2608.25922v1 Announce Type: new Abstract: GNN-based Knowledge Graph Question Answering (KGQA) pipelines process queries through four discrete stages: entity linking, subgraph retrieval, GNN reas

Tutorials

R^3: Training Robots to Reason in Natural Language via Reinforcement Learning

arXiv:2608.26053v1 Announce Type: cross Abstract: Reasoning in language allows foundation models to spend more test-time compute on hard problems, such as those requiring decomposition, constraint tra

tutorialsarxiv-cs-cl

RA-VLA: Retrieval-Augmented VLA for Test-Time Adaptation

model-releasesarxiv-cs-ro

arXiv:2608.25585v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models provide a versatile foundation for general robotic manipulation, yet they exhibit significant brittleness when confr

RAEM: Robust Autonomous Exploration for Multi-Floor Environments with a Quadruped Robot

arXiv:2608.25366v1 Announce Type: new Abstract: In this paper, we propose RAEM, a robust autonomous exploration framework for quadruped robots operating in multi-floor environments. Most existing grou

safetyarxiv-cs-ro

Rare Diseases, Common Dilemmas: LLMs Prioritize Equal Resource Distribution over Patient Benefit in Decision-Making

arXiv:2608.25236v1 Announce Type: cross Abstract: Clinical decision-making often involves prioritizing ethical values, such as beneficence, non-maleficence, respecting a patient's autonomy, and justic

Reasoning or Rambling? Exploring the Effect of Thinking on Agent Persuasion

arXiv:2509.21054v2 Announce Type: replace-cross Abstract: Understanding persuasion is critical for the safety and reliability of multi-agent systems built on large language models (LLMs). This paper s

safetyarxiv-cs-cl

Recognising BSL Fingerspelling in Continuous Signing Sequences

arXiv:2603.19523v2 Announce Type: replace Abstract: Fingerspelling is a critical component of British Sign Language (BSL), used to spell proper names, technical terms, and words that lack established

researcharxiv-cs-cv

Reconstructing the Right Episode: Evaluating Interleaved Conversational Memory Beyond Long Context

arXiv:2608.25655v1 Announce Type: new Abstract: Conversations with chat assistants increasingly span many topics in a single long-running thread, challenging memory systems. Existing long-context and

Recurrence Meets Transformers for Universal Multimodal Retrieval

arXiv:2509.08897v2 Announce Type: replace-cross Abstract: With the rapid advancement of multimodal retrieval and its application in LLMs and multimodal LLMs, increasingly complex retrieval tasks have

Applications

Recurrent Neural Networks in Linguistic Theory: Revisiting Pinker and Prince (1988) and the Past Tense Debate

arXiv:1807.04783v3 Announce Type: replace Abstract: Can advances in NLP help advance cognitive modeling? We examine the role of artificial neural networks, the current state of the art in many common

applicationsarxiv-cs-cl

ReFIne: A Framework for Trustworthy Large Reasoning Models with Reliability, Faithfulness, and Interpretability

arXiv:2510.09062v2 Announce Type: replace Abstract: Recent advances in long chain-of-thought (CoT) reasoning have largely prioritized answer accuracy and token efficiency, while overlooking aspects cr

RefLAM: A Reference-Grounded Line Annotation Pipeline for Historical Arabic Manuscripts

arXiv:2608.25140v1 Announce Type: cross Abstract: Existing approaches to building line-level Arabic handwritten-text-recognition (HTR) training data either rely on fully manual annotation, which does

Reflection Steering: Disentangling Reflection from Reasoning in Activation Space for Token-Efficient Inference

arXiv:2608.25542v1 Announce Type: cross Abstract: Large reasoning models often produce reasoning traces with verification, revision, and backtracking. When reflection merely re-checks established resu

Refusal geometry reflects refusal training: diverse refusal prefixes can raise stable rank and weaken refusal vector ablation attacks

arXiv:2608.25390v1 Announce Type: new Abstract: Refusal training protects AI models from jailbreaks by training models to decline unsafe queries, reducing the risk of misuse. Recent work finds that re

safetyarxiv-cs-lg

Tutorials

RefVideo-6M: A Reliable Reference-Based Dataset for Instructional Video Editing

arXiv:2608.26101v1 Announce Type: new Abstract: Recent advances in video editing have been largely driven by large-scale instruction-based datasets. However, existing datasets still suffer from two cr

tutorialsarxiv-cs-cv

Regularized Latent Dynamics Prediction is a Strong Baseline For Behavioral Foundation Models

arXiv:2603.15857v2 Announce Type: replace-cross Abstract: Behavioral Foundation Models (BFMs) produce agents with the capability to adapt to any unknown reward or task. These methods, however, are onl

ReliableRAG: Combating Misinformation in Retrieval-Augmented Generation via Reliability-Guided Reasoning Chains

arXiv:2608.25487v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has emerged as a powerful architecture for Question Answering (QA) by integrating external information into Large L

safetyarxiv-cs-cl

Representing MAX functions using two-hidden-layer ReLU networks

arXiv:2608.25221v1 Announce Type: new Abstract: We study exact representations of MAX_N(x)=max{x_1,ldots,x_N} using two-hidden-layer ReLU neural networks. This problem has been studied in recent years

Local Ai

Resilient Decentralized Wireless Federated Learning via Gradient Tracking with AdamW

arXiv:2608.25535v1 Announce Type: new Abstract: Wireless Internet-of-Things (IoT) edge networks require decentralized learning (DecL) methods that can operate reliably under both heterogeneous local d

local-aiarxiv-cs-lg

Resolving Multi-Modal Regression by Difference-Quotient-Based Clustering:Fast Coarse Conditional-Label Assignment

arXiv:2608.25467v1 Announce Type: new Abstract: Multimodal regression suffers from the mean-collapse pathology: under squared loss, an unconstrained regressor converges to the conditional mean, which

Resource-Efficient Pruning for Transformer via Low-Rank Importance Estimation

arXiv:2608.24973v1 Announce Type: new Abstract: With the rapid development of large-scale pre-trained language models based on Transformer architectures, their high computational and memory costs have

Rethinking the Transferable Adversarial Attacks and Robust Defense in Federated Learning

arXiv:2608.25133v1 Announce Type: new Abstract: The development of federated learning (FL) techniques has helped improve the privacy preservation of users' data and extended the applications of machin

Agents

Retrieve, Match, Escalate: Accurate and Scalable Product Linking with VLM-Distilled Cross-Encoders and Agentic VLMs

arXiv:2608.25037v1 Announce Type: cross Abstract: Product linking, the entity-resolution task of mapping merchant product records to canonical catalog products, consolidates fragmented listings so dow

agentsarxiv-cs-cl

Retrieved But Not Reliable: A Survey on Attacks, and Defenses in Retrieval-Augmented Generation

arXiv:2608.24977v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances large language models by grounding outputs in external knowledge, improving factuality and reducing hall

safetyarxiv-cs-cl