Search: “framework”

Efficient Banzhaf-Based Data Valuation for k-Nearest Neighbors Classification

arXiv:2605.21033v1 Announce Type: new Abstract: Data valuation, the task of quantifying the contribution of individual data points to model performance, has emerged as a fundamental challenge in machi

applicationsarxiv-cs-lg

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End-to-End Unmixing with Material Prompts for Hyperspectral Object Tracking

DGX agent

arXiv:2605.20569v1 Announce Type: new Abstract: Hyperspectral imagery encodes rich material properties that can improve tracking robustness under appearance ambiguity, illumination change, and backgro

local-aiarxiv-cs-cv

21 May 2026

Federated Learning of Nonlinear Temporal Dynamics with Graph Attention-based Cross-Client Interpretability

arXiv:2602.13485v2 Announce Type: replace Abstract: Networks of modern industrial systems are increasingly monitored by distributed sensors, where each system comprises multiple subsystems generating

local-aiarxiv-cs-lg

Fine-grained Claim-level RAG Benchmark for Law

model-releasesarxiv-cs-cl

arXiv:2605.21071v1 Announce Type: new Abstract: The rapid progress of large language models (LLMs) is shifting semantic search toward a question-answering paradigm, where users ask questions and LLMs

For How Long Should We Be Punching? Learning Action Duration in Fighting Games

arXiv:2605.20911v1 Announce Type: cross Abstract: Fighting games such as Street Fighter II present unique challenges to reinforcement learning (RL) agents due to their fast-paced, real-time nature. In

agentsarxiv-cs-lg

FruitEnsemble: MLLM-Guided Arbitration for Heterogeneous ensemble in Fine-Grained Fruit Recognition

arXiv:2605.20892v1 Announce Type: new Abstract: Fine-grained fruit classification is a critical yet challenging task in agricultural computer vision, primarily hindered by a severe shortage of high-qu

applicationsarxiv-cs-cv

Group-Algebraic Tensors: Provably-optimal Equivariant Learning and Physical Symmetry Discovery

model-releasesarxiv-cs-lg

arXiv:2605.20440v1 Announce Type: new Abstract: We introduce the star_G tensor algebra, in which any finite group G defines the multiplication rule, making equivariance an intrinsic algebraic property

GROW: Aligning GRPO with State-Action Modeling for Open-World VLM Agents

arXiv:2605.20246v1 Announce Type: new Abstract: Recently, vision-language model (VLM) agents have shown promising progress in open-world tasks, where successful task completion often requires multiple

Hyper-V2X: Hypernetworks for Estimating Epistemic and Aleatoric Uncertainty in Cooperative Bird's-Eye-View Semantic Segmentation

arXiv:2605.21309v1 Announce Type: new Abstract: Cooperative perception enabled by Vehicle-to-Everything (V2X) communication enhances autonomous driving safety by creating a unified environmental repre

Informationally Compressive Anonymization: Non-Degrading Sensitive Input Protection for Privacy-Preserving Supervised Machine Learning

arXiv:2603.15842v2 Announce Type: replace Abstract: Modern machine learning systems increasingly rely on sensitive data, creating significant privacy, security, and regulatory risks that existing priv

applicationsarxiv-cs-lg

InternBootcamp Technical Report: Boosting LLM Reasoning with Verifiable Task Scaling

model-releasesarxiv-cs-cl

arXiv:2508.08636v2 Announce Type: replace Abstract: Large language models (LLMs) have revolutionized artificial intelligence by enabling complex reasoning capabilities. While recent advancements in re

iReasoner: Trajectory-Aware Intrinsic Reasoning Supervision for Self-Evolving Large Multimodal Models

arXiv:2601.05877v3 Announce Type: replace Abstract: Recent work shows that large multimodal models (LMMs) can self-improve from unlabeled data via self-play and intrinsic feedback. Yet existing self-e

researcharxiv-cs-cl

Learning Incentive Structures for Cooperative Resilience in Multi-Agent Systems under Social Dilemmas

arXiv:2601.22292v2 Announce Type: replace-cross Abstract: Multi-agent social dilemmas, such as the tragedy of the commons, capture settings where individual incentives conflict with collective well-be

agentsarxiv-cs-lg

Llamas on the Web: Memory-Efficient, Performance-Portable, and Multi-Precision LLM Inference with WebGPU

model-releasesarxiv-cs-lg

arXiv:2605.20706v1 Announce Type: cross Abstract: Running language models in the browser presents a unique opportunity to build efficient, private, and portable AI applications, but requires contendin

LoCar: Localization-Aware Evaluation of In-Vehicle Assistants through Fine-Grained Sociolinguistic Control

arXiv:2605.21086v1 Announce Type: new Abstract: While Large Language Models (LLMs) are increasingly integrated into in-vehicle conversational systems, identifying the optimal model remains challenging

local-aiarxiv-cs-cl

MedCRP-CL: Continual Medical Image Segmentation via Bayesian Nonparametric Semantic Modality Discovery

arXiv:2605.20297v1 Announce Type: new Abstract: Medical image segmentation faces a fundamental challenge in continual learning: data arrives sequentially from heterogeneous sources, yet effective cont

Multimodal LLMs under Pairwise Modalities

arXiv:2605.21059v1 Announce Type: new Abstract: Despite the impressive results achieved by multimodal large language models (MLLMs), their training typically relies on jointly curated multimodal data,

safetyarxiv-cs-cv

Nonlocal operator learning for fMRI encoding and decoding tasks

arXiv:2605.20389v1 Announce Type: new Abstract: Functional MRI data exhibit high-dimensional spatiotemporal structure, making both prediction and decoding challenging. In this work, we investigate neu

One-Step Distillation of Discrete Diffusion Image Generators via Fixed-Point Iteration

arXiv:2605.21484v1 Announce Type: new Abstract: Discrete diffusion models excel at visual synthesis but rely on slow, iterative decoding. Existing single-step distillation methods attempt to bypass th

local-aiarxiv-cs-cv

Ordering Matters: Rank-Aware Selective Fusion for Blended Emotion Recognition

arXiv:2605.21417v1 Announce Type: new Abstract: Blended emotion recognition is challenging because emotions are often expressed as mixtures of subtle and overlapping multimodal cues rather than a sing

researcharxiv-cs-cv

Tutorials

PACD-Net: Pseudo-Augmented Contrastive Distillation for Glycemic Control Estimation from SMBG

arXiv:2605.20751v1 Announce Type: new Abstract: Effective diabetes management requires continuous monitoring of glycemic levels. Clinically, glycemic control is assessed using metrics such as Time in

tutorialsarxiv-cs-lg

Plug-and-Play Spiking Operators: Breaking the Nonlinearity Bottleneck in Spiking Transformers

arXiv:2605.20289v1 Announce Type: new Abstract: ANN-to-SNN conversion offers a practical, training-free route to spiking large language models. However, current pipelines primarily focus on spike-driv

Polynomial-Time Robust Multiclass Linear Classification under Gaussian Marginals

arXiv:2605.21428v1 Announce Type: new Abstract: We study the task of agnostic learning of multiclass linear classifiers under the Gaussian distribution. Given labeled examples (x, y) from a distributi

ProCrit: Self-Elicited Multi-Perspective Reasoning with Critic-Guided Revision for Multimodal Sarcasm Detection

arXiv:2605.20867v1 Announce Type: cross Abstract: Multimodal sarcasm detection requires reasoning over cross-modal incongruities between literal expression and intended meaning, yet the specific analy

agentsarxiv-cs-cv

Tutorials

Q-Net: Queue Length Estimation via Kalman-based Neural Networks

arXiv:2509.24725v3 Announce Type: replace Abstract: Estimating queue lengths at signalized intersections is a long-standing challenge in traffic management. Partial observability of vehicle flows comp

tutorialsarxiv-cs-lg

Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation

arXiv:2605.20801v1 Announce Type: new Abstract: Adaptive robot navigation in dynamic environments requires policies that can reach the target reliably while producing efficient and stable trajectories

safetyarxiv-cs-ro

Quadratic Characterizations for Reachability Analysis of Neural Networks

arXiv:2605.20482v1 Announce Type: new Abstract: Quadratic constraints (QCs) are widely used to characterize nonlinearities and uncertainties, but generic analytical characterizations can be conservati

RadProPoser: Probabilistic Radar Tensor Human Pose Estimation That Knows Its Limits

arXiv:2508.03578v2 Announce Type: replace Abstract: Radar-based human pose estimation enables privacy-preserving motion tracking for ambient intelligence, yet the noisy nature of radar sensing makes u

Reasoning-Trace Collapse: Evaluating the Loss of Explicit Reasoning During Fine-Tuning

arXiv:2605.21127v1 Announce Type: new Abstract: Explicit reasoning models are trained to produce intermediate reasoning traces before final answers, but downstream fine-tuning is often performed on or

Refining and Reusing Annotation Guidelines for LLM Annotation

model-releasesarxiv-cs-cl

arXiv:2605.20809v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate remarkable performance on zero-shot annotation tasks, they often struggle with the specialized convention

REFLECTOR: Internalizing Step-wise Reflection against Indirect Jailbreak

arXiv:2605.20654v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate remarkable capabilities, they remain susceptible to sophisticated, multi-step jailbreak attacks that circ

Reinforcement Learning for Risk Adaptation via Differentiable CVaR Barrier Functions

arXiv:2605.21257v1 Announce Type: new Abstract: Planning through crowded environments under uncertain obstacle motions remains difficult, as stochastic interactions often induce overly conservative be

safetyarxiv-cs-ro

rePIRL: Learn PRM with Inverse RL for LLM Reasoning

arXiv:2602.07832v2 Announce Type: replace Abstract: Process rewards have been widely used in deep reinforcement learning to improve training efficiency, reduce variance, and prevent reward hacking. In

Resolving Long-Tail Ambiguity in Unsupervised 3D Point Cloud Segmentation with Language Priors

arXiv:2605.20737v1 Announce Type: new Abstract: Existing approaches for unsupervised 3D point cloud segmentation predominantly rely on a purely visual similarity-based learning-by-clustering paradigm,

Retrieval-Augmented Code Generation: A Survey with Focus on Repository-Level Approaches

arXiv:2510.04905v3 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have significantly improved automated code generation. While existing approaches have achieved

agentsarxiv-cs-cl

SAM-Sode: Towards Faithful Explanations for Tiny Bacteria Detection

arXiv:2605.21186v1 Announce Type: new Abstract: Interpretability in object detection provides crucial confidence support for clinical auxiliary diagnosis. However, in tiny bacteria detection, traditio

safetyarxiv-cs-cv

Time-Dependent PDE-Constrained Optimization via Weak-Form Latent Dynamics

model-releasesarxiv-cs-lg

arXiv:2605.20639v1 Announce Type: cross Abstract: Optimization problems constrained by high-dimensional, time-dependent partial differential equations require repeated forward and sensitivity solves,

Time-Prompt: Integrated Heterogeneous Prompts for Unlocking LLMs in Time Series Forecasting

arXiv:2506.17631v4 Announce Type: replace Abstract: Time series forecasting aims to model temporal dependencies among variables for future state inference, holding significant importance and widesprea

torchtune: PyTorch native post-training library

arXiv:2605.21442v1 Announce Type: new Abstract: Modern LLMs typically require multistage training pipelines to achieve strong downstream performance, with post-training serving as the main interface f

Uncertainty-Calibrated Explainable Artificial Intelligence for Fetal Ultrasound Plane Classification: A Systematic Review

arXiv:2601.00990v2 Announce Type: replace-cross Abstract: Fetal ultrasound is the cornerstone of antenatal care, and accurate recognition of a small set of standard anatomical planes underpins biometr

safetyarxiv-cs-cv

UniT: Unified Geometry Learning with Group Autoregressive Transformer

arXiv:2605.21131v1 Announce Type: new Abstract: Recent feed-forward models have significantly advanced geometry perception for inferring dense 3D structure from sensor observations. However, its essen

researcharxiv-cs-cv

Validating Navmesh using Geometry: Voxel-Based Analysis with Prioritized Exploration

arXiv:2605.21397v1 Announce Type: cross Abstract: Navigation mesh (Navmesh) inconsistencies affect the player experience by directly impacting the navigation systems used by non-playable characters (N

applicationsarxiv-cs-ro

3D Modeling and Automated Measurement of Concrete Cracks via Segment Anything Refinement and Visual Inertial LiDAR Fusion

arXiv:2501.09203v2 Announce Type: replace Abstract: Visual-Spatial Systems has become increasingly essential in concrete crack inspection. However, existing methods often lacks adaptability to diverse

local-aiarxiv-cs-cv

An Integrated Forecasting Prototype for Emergency Department Boarding Time to Support Proactive Operational Decision Making

arXiv:2605.18839v1 Announce Type: cross Abstract: Overcrowding in emergency departments (ED) remains a persistent operational challenge worldwide, causing delays in care delivery and downstream conges

applicationsarxiv-cs-ai

Benchmarking and Evolving Reason-Reflect-Rectify for Reflective Visual Generation

arXiv:2605.19639v1 Announce Type: new Abstract: Text-to-Image (T2I) models and Unified Multimodal Models (UMMs) have achieved remarkable progress in visual generation. However, their reliance on a sin

CEER: Compliant End-Effector and Root Control as a Unified Interface for Hierarchical Humanoid Loco-Manipulation

arXiv:2605.19981v1 Announce Type: new Abstract: Humanoid robots have achieved impressive locomotion performance, yet contact-rich and long-horizon manipulation remains a major bottleneck. Manipulation

safetyarxiv-cs-ro

CLUE: Adaptively Prioritized Contextual Cues by Leveraging a Unified Semantic Map for Effective Zero-Shot Object-Goal Navigation

arXiv:2605.19206v1 Announce Type: new Abstract: Zero-shot object-goal navigation (ZSON) is a challenging problem in robotics that requires a comprehensive understanding of both language and visual obs

agentsarxiv-cs-ro

Hardware

CODA: Rewriting Transformer Blocks as GEMM-Epilogue Programs

arXiv:2605.19269v1 Announce Type: new Abstract: Transformer training systems are built around dense linear algebra, yet a nontrivial fraction of end-to-end time is spent on surrounding memory-bound op

hardwarearxiv-cs-lg