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A holomorphic neural network framework for 3D boundary value problems governed by harmonic potentials

arXiv:2605.31231v1 Announce Type: cross Abstract: We present a neural-network-based framework for the solution of three-dimensional boundary value problems where the solution is expressible in terms o

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A Kinetic Energy Perspective of Flow Matching

DGX agent

arXiv:2602.07928v2 Announce Type: replace-cross Abstract: Flow-based generative models can be viewed through a physics lens: sampling transports a particle from noise to data by integrating a learned

model-releasesarxiv-cs-ai

1 Jun 2026

A Lecture Note on Offline RL and IRL, Part II: Foundations of Inverse Reinforcement Learning and Dynamic Discrete Choice Models

arXiv:2605.30843v1 Announce Type: new Abstract: In the forward reinforcement-learning problem, the reward is fixed and known; the learner is asked to find a good policy or value function. Here we turn

safetyarxiv-cs-lg

A Lightweight Ensemble-Based Face Image Quality Assessment Method with Correlation-Aware Loss

model-releasesarxiv-cs-cv

arXiv:2509.10114v2 Announce Type: replace Abstract: Face image quality assessment (FIQA) plays a critical role in face recognition and verification systems, especially in uncontrolled, real-world envi

A Novel Computer Vision Approach for Assessing Fish Responses to Intrusive Objects in Aquaculture

arXiv:2605.30399v1 Announce Type: cross Abstract: The aquaculture industry needs to address several challenges to secure sustainable seafood production that can serve an increasing global demand. One

A Novel Evaluation Metric for Unsupervised Learning in AIS-Based Maritime Anomaly Detection: MADQI

arXiv:2605.30388v1 Announce Type: new Abstract: This paper introduces a new systematic framework for detecting anomalies in maritime Automatic Identification System (AIS) datasets. These anomalies inc

A Novel Global Context-aware Deep Neural Network for Enhanced Brain Tumor Segmentation using Magnetic Resonance Images

model-releasesarxiv-cs-ai

arXiv:2605.30510v1 Announce Type: cross Abstract: Brain cancer's severity necessitates precise brain tumor segmentation, which is crucial for effective brain tumor diagnosis. Manual identification, bu

A Padding Method for Enhanced Encoding of Inorganic Structures with Varying Chemical Compositions

arXiv:2605.30743v1 Announce Type: cross Abstract: Designing novel inorganic materials through generative models remains an important challenge for material science, driven by the complexity and divers

researcharxiv-cs-cl

A Persona-Based Evaluation Framework for Pluralistic Alignment in Generative AI

arXiv:2605.31021v1 Announce Type: new Abstract: Current alignment paradigms for generative artificial intelligence rely predominantly on monolithic benchmarking frameworks that reduce the plurality of

A Perturbation Approach to Unconstrained Linear Bandits

arXiv:2603.28201v2 Announce Type: replace Abstract: We revisit the standard perturbation-based approach of Abernethy et al. (2008) in the context of unconstrained Bandit Linear Optimization (uBLO). We

A Pilot Study on Curator-Guided Multilingual Art Description for Blind and Low-Vision Audiences with Small Vision-Language Models

arXiv:2605.31080v1 Announce Type: cross Abstract: Blind and low-vision (BLV) audiences remain underserved by visual art descriptions, particularly across languages and in museum settings where privacy

researcharxiv-cs-ai

A study on a Real-Time VR-Based Teleoperation Framework for Manipulator in Dynamic Environment

arXiv:2605.30989v1 Announce Type: new Abstract: Robot teleoperation enables safe, non-contact task execution in hazardous environments where direct human access is difficult, and its application has e

safetyarxiv-cs-ro

A Survey on Semantic Communication for Vision: Categories, Frameworks, Enabling Techniques, and Applications

arXiv:2601.22202v2 Announce Type: replace-cross Abstract: Semantic communication (SemCom) emerges as a transformative paradigm for traffic-intensive visual data transmission, shifting focus from raw d

researcharxiv-cs-cv

A Tight Theory of Error Feedback Algorithms in Distributed Optimization

arXiv:2605.31594v1 Announce Type: new Abstract: Communication costs are a major bottleneck in distributed learning and first-order optimization. A common approach to alleviate this issue is to compres

agentsarxiv-cs-lg

A Unified and Reproducible Experimentation Framework for Speech Understanding

arXiv:2605.30899v1 Announce Type: cross Abstract: Speech foundation models and Speech LLMs have advanced speech understanding, yet deployment-oriented model selection is hindered by non-comparable eva

agentsarxiv-cs-ai

A Unified Framework for Gradient Aggregation in Multi-Objective Optimization

arXiv:2605.30452v1 Announce Type: cross Abstract: Many machine learning problems involve multiple inherent trade-offs that are best addressed by gradient-based multi-objective optimization (MOO) algor

A Unifying View of Anchoring via Operator-Side Tikhonov Regularization

arXiv:2605.30905v1 Announce Type: cross Abstract: Anchored fixed point and monotone equation methods, including Halpern iteration, extra anchored gradient, and their relatives, add a vanishing pull to

A Unifying View of Variational Generative Wasserstein Flows

arXiv:2605.31369v1 Announce Type: cross Abstract: Many modern generative models can be viewed as minimizing divergences between probability distributions, yet they rely on different algorithmic and ge

researcharxiv-cs-cv

A Visually Impaired Assistance Benchmark for VLM-as-a-Judge Evaluation

model-releasesarxiv-cs-cl

arXiv:2605.31351v1 Announce Type: new Abstract: AI-based Visually Impaired Assistance (VIA) remains challenging, largely due to the high cost of human evaluation. The VLM-as-a-Judge paradigm may offer

AbstainGNN: Teaching Graph Neural Networks to Abstain for Graph Classification

model-releasesarxiv-cs-lg

arXiv:2605.30786v1 Announce Type: new Abstract: Graph classification is a core task in graph data mining with widespread real-world applications. Recent advances in graph neural networks (GNNs) have l

Accelerated Multiple Wasserstein Gradient Flows for Multi-objective Distributional Optimization

arXiv:2601.19220v2 Announce Type: replace Abstract: We study multi-objective optimization over probability distributions in Wasserstein space. Recently, Nguyen et al. (2025) introduced Multiple Wasser

Active Timepoint Selection for Learning Measure-Valued Trajectories

arXiv:2605.30625v1 Announce Type: cross Abstract: Inferring continuous probability paths from sparse snapshots is a fundamental challenge in domains like single-cell biology, where high-fidelity data

Actuator-Aware Inverse Kinematics with Joint-Limit Admissibility for Torque-Controlled Redundant Robots

arXiv:2605.31436v1 Announce Type: new Abstract: This paper proposes actuator-aware inverse kinematics for torque-controlled redundant robots under joint-limit constraints. In the considered architectu

researcharxiv-cs-ro

Adaptive Artificial Time-Delay Control with Barrier Lyapunov Constraints for Euler-Lagrange Robots

arXiv:2605.31405v1 Announce Type: new Abstract: This paper addresses the challenge of simultaneously compensating for state-dependent uncertainties and enforcing time-varying state constraints in Eule

safetyarxiv-cs-ro

Adaptive NAD: Online and Self-adaptive Unsupervised Network Anomaly Detector

model-releasesarxiv-cs-lg

arXiv:2410.22967v5 Announce Type: replace Abstract: The widespread usage of the Internet of Things (IoT) has raised the risks of cyber threats; thus, developing Anomaly Detection Systems (ADSs) that c

Local Ai

Adaptive Physics Transformer with Fused Global-Local Attention for Subsurface Energy Systems

arXiv:2602.11208v2 Announce Type: replace Abstract: The Earth's subsurface is a cornerstone of modern society, providing essential energy resources like hydrocarbons, geothermal, and minerals while se

local-aiarxiv-cs-lg

AdaptR1: Reinforcement Learning Based Adaptive Interleaved Thinking in Multi-hop Question Answering

arXiv:2605.31062v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable performance in complex reasoning tasks through Chain-of-Thought (CoT) prompting. However, this app

researcharxiv-cs-cl

Advances and Challenges in Meta-Learning: A Technical Review

arXiv:2307.04722v2 Announce Type: replace Abstract: Meta-learning empowers learning systems with the ability to acquire knowledge from multiple tasks, enabling faster adaptation and generalization to

AdvScene: Rethinking Adversarial Patch Evaluation Through Scene Robustness

arXiv:2605.30578v1 Announce Type: cross Abstract: Adversarial patches are physical patterns attached to real objects to mislead AI vision systems. Their real-world risk is not determined by a single s

applicationsarxiv-cs-cv

Aggregation Buffer: Revisiting DropEdge with a New Parameter Block

model-releasesarxiv-cs-lg

arXiv:2505.20840v2 Announce Type: replace Abstract: We revisit DropEdge, a data augmentation technique for GNNs which randomly removes edges to expose diverse graph structures during training. While b

AI for Monitoring and Classifying Data Used in Research Literature

arXiv:2605.30582v1 Announce Type: new Abstract: While platforms like Google Scholar and Semantic Scholar track citations for academic papers, no comparable infrastructure exists for monitoring dataset

researcharxiv-cs-cl

AI Loss of Control Incident Management: Response & Resilience

arXiv:2605.30406v1 Announce Type: cross Abstract: Recent research demonstrating AI systems exhibiting deception and shutdown resistance suggests that AI loss of control (LOC) is an urgent policy conce

Algorithmic Recourse of In-Context Learning for Tabular Data

arXiv:2605.31272v1 Announce Type: new Abstract: As predictive models are increasingly deployed in high-stakes settings such as credit approval, there is a growing need for post-hoc methods that provid

AMix-2: Establishing Protein as a Native Modality in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2605.30963v1 Announce Type: cross Abstract: We present AMix-2, a protein-text foundation model that establishes protein as a native modality in large language models (LLMs), unifying protein und

AMNESIA: A Large Scale Medical Unlearning Benchmark Suite with Disease-Informed Analysis

model-releasesarxiv-cs-cl

arXiv:2605.30599v1 Announce Type: cross Abstract: Medical knowledge is continuously evolving. This creates a need to update or selectively forget information encoded in already-trained medical LLMs. M

An Efficient and Scalable Graph Condensation with Structure-Preserving

arXiv:2605.31016v1 Announce Type: new Abstract: Graph condensation (GC) is pivotal for enabling Graph Neural Networks (GNNs) deployment in resource-constrained scenarios by compressing large-scale gra

An Odd Estimator for Shapley Values

model-releasesarxiv-cs-ai

arXiv:2602.01399v2 Announce Type: replace-cross Abstract: The Shapley value is a ubiquitous framework for attribution in machine learning, encompassing feature importance, data valuation, and causal i

Local Ai

An Organization-Scoped LLM Agent Runtime Architecture for Regulated Cybersecurity Operations

arXiv:2605.30604v1 Announce Type: cross Abstract: Regulated cybersecurity workflows lack a runtime substrate that enforces organization-level scope across retrieval, tool calls, memory, findings, repo

local-aiarxiv-cs-ai

Anchoring LLM Gender Bias to Human Baselines: A Cross-Lingual Audit

model-releasesarxiv-cs-cl

arXiv:2605.30804v1 Announce Type: new Abstract: We audit six large language models (LLMs) for gender stereotyping across English, Korean, Chinese, and Japanese. Three were developed primarily for Engl

AnchorSteer: Self-Discovered Concept Injection for Structure-Preserving Music Editing

arXiv:2605.31053v1 Announce Type: cross Abstract: Controllable music editing is to modify high-level attributes while strictly preserving rhythmic and melodic structures. However, this task is challen

researcharxiv-cs-ai

Annealed Softmax Greedy in Many-Armed Bayesian Bandits

arXiv:2605.31034v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) and group-based policy optimization methods such as GRPO update a stochastic policy by sampling

Annotations Are Not All You Need: A Cross-modal Knowledge Transfer Network for Unsupervised Temporal Sentence Grounding

arXiv:2605.30742v1 Announce Type: new Abstract: This paper addresses the task of temporal sentence grounding (TSG). Although many respectable works have made decent achievements in this important topi

safetyarxiv-cs-cv

Answer-Set-Programming-based Abstractions for Reinforcement Learning

arXiv:2605.31444v1 Announce Type: new Abstract: Reinforcement Learning (RL) enables autonomous agents to learn policies from experience, but realistic problems often involve enormous state spaces, mak

agentsarxiv-cs-ai

Any-ttach: Quick End-effector Swapping Enables Manipulation Dexterity with Simplicity

arXiv:2605.30569v1 Announce Type: new Abstract: Robotic manipulation dexterity is often pursued by building increasingly complex high-DoF multifingered hands. While many robotic hands are designed to

agentsarxiv-cs-ro

Tutorials

Appropriateness of Empathy in AI: A Signal-Cost Perspective

arXiv:2605.31340v1 Announce Type: cross Abstract: The appropriateness of empathy in AI has emerged as a critical concern, as excessive empathy risks seeming manipulative while insufficient empathy app

tutorialsarxiv-cs-ai

Tutorials

Approximation and learning of anisotropic and mixed smooth functions by deep ReLU neural networks

arXiv:2605.31152v1 Announce Type: cross Abstract: This paper studies how efficiently deep ReLU neural networks can approximate and learn smooth functions. When the error is measured in L^p([0,1]^d) no

tutorialsarxiv-cs-lg

AR Forcing: Towards Long-Horizon Robot Navigation World Model

arXiv:2605.31314v1 Announce Type: new Abstract: The diffusion based robot navigation world models are typically trained using parallel supervision, while autoregressive inference is employed during pa

researcharxiv-cs-ro

Are Full Rollouts Necessary for On-Policy Distillation?

arXiv:2605.31490v1 Announce Type: new Abstract: On-policy distillation (OPD) provides dense teacher feedback along rollouts generated by the student and has emerged as a promising post-training paradi

safetyarxiv-cs-cl