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arXiv:2602.15239v2 Announce Type: replace Abstract: Transformers have achieved remarkable success across domains, motivating the rise of Graph Transformers (GTs) as attention-based architectures for g

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Research

Solved in Unit Domain: JacobiNet for Differentiable Coordinate-Transformed PINNs

DGX agent

arXiv:2508.02537v3 Announce Type: replace Abstract: Physics-Informed Neural Networks (PINNs) offer a powerful framework for solving PDEs by embedding physical laws into the learning process. However,

researcharxiv-cs-lg

29 May 2026

Source-Grounded Semantic Reinforcement Learning for Low-Resource Target-Language Generation

arXiv:2605.29502v1 Announce Type: cross Abstract: Low-resource target-language generation is often limited by scarce parallel data, while high-resource source-language monolingual data is abundant but

Structured Prompt Optimization Meets Reinforcement Learning for Global and Local Interpretability over Complex Text

arXiv:2605.29076v1 Announce Type: cross Abstract: LLMs have advanced text classification, yet existing paradigms face a trade-off: supervised (label only) fine-tuning is scalable but offers limited re

Subcortical Shape Variations and Their Associations with Cognition Across the 8th Decade of Life. A Study in the Lothian Birth Cohort 1936

arXiv:2605.29703v1 Announce Type: cross Abstract: The study of brain morphology changes in normal individuals may capture aspects of functionally-relevant brain aging not fully indicated by gross volu

Sustainable Metal-Organic Framework Water Harvesters in the Artificial Intelligence Era

arXiv:2605.29179v1 Announce Type: cross Abstract: Metal-organic frameworks (MOFs) are excellent candidates for water harvesting due to their tunable pore environments, which can be precisely engineere

The Sample Complexity of Multiclass and Sparse Contextual Bandits

arXiv:2605.29645v1 Announce Type: cross Abstract: We study contextual bandits in the stochastic i.i.d. setting, where a learner observes contexts drawn from an unknown distribution, selects actions fr

TraceCodec: A Compiler-Backed Neural Codec for Stateful Multi-Flow Network Traffic Traces

arXiv:2605.29941v1 Announce Type: cross Abstract: Critical networking workflows require high-fidelity packet captures (PCAPs) for testing, security analysis, and protocol validation, not just statisti

safetyarxiv-cs-lg

Traditional machine learning vs. deep learning from dynamic graph representations of proteins' 3D folds in the task of protein structure classification

arXiv:2605.29228v1 Announce Type: new Abstract: Protein structure classification (PSC) uses supervised learning to predict a protein's CATH/SCOP(e) class from the protein's sequence or 3D structural f

Trajectory Constraints for Imaging Inverse Problems

arXiv:2605.29012v1 Announce Type: new Abstract: Diffusion-based and iterative methods have become effective tools for solving imaging inverse problems. Their reconstruction process naturally forms a t

unix-ctf: Procedural Environments for Unix-Competence Reinforcement Learning

arXiv:2605.29115v1 Announce Type: cross Abstract: Unix competence is the ability to use shell and operating-system primitives as first-class tools, not merely to write programs through a terminal. Cur

agentsarxiv-cs-ai

Hardware

VideoMLA: Low-Rank Latent KV Cache for Minute-Scale Autoregressive Video Diffusion

arXiv:2605.30351v1 Announce Type: cross Abstract: Long-rollout causal video diffusion has converged on a fixed-size sliding-window KV cache, with recent progress innovating within this layout by chang

hardwarearxiv-cs-ai

Wasserstein Contraction of Coordinate Ascent Variational Inference

arXiv:2605.30253v1 Announce Type: cross Abstract: We study the contraction in Wasserstein distance of the coordinate ascent variational inference algorithm. This is shown to hold under a transport-inf

What Exactly do Children Receive in Language Acquisition? A Case Study on CHILDES with Automated Detection of Filler-Gap Dependencies

arXiv:2603.02082v2 Announce Type: replace Abstract: Children's acquisition of filler-gap dependencies has been argued by some to depend on innate grammatical knowledge, while others suggest that the d

tutorialsarxiv-cs-cl

A Comparative Study of Rule-Based and Data-Driven Approaches in Industrial Monitoring

arXiv:2509.15848v2 Announce Type: replace Abstract: Industrial monitoring systems, especially when deployed in Industry 4.0 environments, are experiencing a shift in paradigm from traditional rule-bas

Local Ai

A Generalized Tikhonov Layer for Interpretable-by-design Graph Neural Networks

arXiv:2605.28578v1 Announce Type: new Abstract: We propose the Tikhonov layer, a graph neural network layer that is interpretable by design: once trained, its learned parameters directly reveal which

local-aiarxiv-cs-lg

A Patient-Specific Pulmonary Arterial Tree Digital Twin to Extract Pulmonary Embolism Biomarkers

arXiv:2605.28217v1 Announce Type: new Abstract: Pulmonary embolism, the obstruction of a pulmonary artery by a blood clot, is one of the leading causes of acute cardiovascular syndrome. In clinical pr

A Road-Conditioned Traffic Movie Prediction Network with Spatiotemporal and Structure-Consistent Learning

arXiv:2605.27884v1 Announce Type: new Abstract: City-wide traffic forecasting is important for congestion management, route guidance, and intelligent transportation systems, but accurate prediction re

Applications

A Wolf in Sheep's Clothing: Targeted Routing Hijacking in Federated RAG

arXiv:2605.28112v1 Announce Type: cross Abstract: Federated Retrieval-Augmented Generation (FedRAG) is attractive for privacy-sensitive applications because raw data remain local. As a result, routing

applicationsarxiv-cs-cl

Adaptive Sampling and Clipping for Private Worst-Case Group Optimization

arXiv:2602.10820v2 Announce Type: replace Abstract: A central requirement for the acceptance of machine learning methods for human-centric tasks is that they should be fair, in the sense that they sho

tutorialsarxiv-cs-lg

Adaptive Temporal Gating of Longitudinal Magnetic Resonance Imaging for Alzheimer's Prediction

arXiv:2605.28397v1 Announce Type: new Abstract: Predicting conversion from Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) is critical for early intervention. Current deep learning paradig

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients

arXiv:2605.27412v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) have emerged with promising energy-efficient property, yet a substantial performance gap persists compared to Artificia

Agentic Language-to-Objective Synthesis for Optofluidic Assembly

arXiv:2605.27643v1 Announce Type: new Abstract: Light-based advanced manufacturing increasingly requires programmable, closed-loop tools that translate human design intent into executable operations a

agentsarxiv-cs-ro

AI Research Agents Narrow Scientific Exploration

arXiv:2605.27905v1 Announce Type: new Abstract: AI research agents can now generate research ideas, design experiments, run code, and draft papers, raising the possibility of large-scale AI-assisted s

agentsarxiv-cs-cl

AI, Take the Wheel: What Drives Delegation and Trust in Human-Computer Cooperative Question Answering?

arXiv:2605.28255v1 Announce Type: new Abstract: AI systems are fallible, and humans can make mistakes in deciding whether to trust AI over their own judgment. Thus, improving human-AI collaboration re

An Empirical Study on Variance-based MC Dropout Uncertainty-Error Correlation in 2D Brain Tumor Segmentation

arXiv:2510.15541v2 Announce Type: replace-cross Abstract: Accurate brain tumor segmentation from MRI is vital for diagnosis and treatment planning. Although Monte Carlo (MC) Dropout is widely used to

Artemis: Structured Visual Reasoning for Perception Policy Learning

arXiv:2512.01988v2 Announce Type: replace Abstract: Recent reinforcement-learning frameworks for visual perception policy usually incorporate intermediate reasoning chains expressed in natural languag

safetyarxiv-cs-cv

Attention Projection Mixing with Exogenous Anchors

arXiv:2601.08131v4 Announce Type: replace Abstract: Cross-layer reuse of early attention projections can improve optimization and data efficiency, but it creates a structural conflict: the first layer

researcharxiv-cs-cl

BiasEdit: A Training-Free Bias-Detect-and-Edit Framework for Learning Fair Visual Classifiers

arXiv:2605.28450v1 Announce Type: cross Abstract: Visual data from the Web power image classifiers, which often underpin many web services, such as recommendation and content moderation. However, the

CALM-IT: Generating Realistic Long-Form Motivational Interviewing Dialogues with Dual-Actor Conversational Dynamics Tracking

arXiv:2601.10085v2 Announce Type: replace Abstract: Therapeutic dialogue is not a sequence of isolated responses: client goals, motivation, resistance, and therapeutic alliance evolve over time. Yet c

researcharxiv-cs-cl

CircuitLM: A Multi-Agent LLM-Aided Design Framework for Generating Circuit Schematics from Natural Language Prompts

arXiv:2601.04505v3 Announce Type: replace Abstract: Generating accurate circuit schematics from high-level natural language descriptions remains a persistent challenge in electronic design automation

agentsarxiv-cs-ai

CLEAR-NeRF: Collinearity and Local-region Enhanced Accurate 3D Reconstruction in Unbounded Scenes

arXiv:2605.28125v1 Announce Type: new Abstract: Many real-world 3D reconstruction applications demand photorealism and metric accuracy across unbounded, complex scenes with challenging lighting and im

tutorialsarxiv-cs-cv

CodeGENCAT: Generative Computerized Adaptive Testing for Open-ended Coding Problems

arXiv:2602.20020v2 Announce Type: replace Abstract: Existing Computerized Adaptive Testing (CAT) frameworks typically select questions based on the predicted likelihood that the student will answer co

safetyarxiv-cs-cl

Colosseum: Auditing Collusion in Cooperative Multi-Agent Systems

arXiv:2602.15198v2 Announce Type: replace-cross Abstract: Multi-agent systems, where LLM agents communicate through free-form language, enable sophisticated coordination for solving complex cooperativ

Comonadic Morphophonology: A Compositional Framework for Context-Dependent Morphological Rules in Finnish

arXiv:2605.28484v1 Announce Type: new Abstract: Composing finite-state transducers (FSTs) for context-dependent morphophonological rules -- consonant gradation, vowel harmony, possessive suffix assimi

researcharxiv-cs-cl

Applications

Conveyance: A Versatile Framework for Learning in Structured Class Spaces

arXiv:2605.28420v1 Announce Type: new Abstract: While machine learning (ML) architectures have evolved rapidly to account for complex data, loss functions like cross-entropy remain mostly structure-ag

applicationsarxiv-cs-lg

Cross-Modal Action Recognition in Egocentric Video Using Mamba: Integrating RGB and Hand Skeleton Streams via CLS Token Fusion Strategies

arXiv:2605.24302v2 Announce Type: replace Abstract: Egocentric action recognition is a challenging task due to erratic camera motion, frequent hand occlusion, and the difficulty of maintaining consist

CubePart: An Open-Vocabulary Part-Controllable 3D Generator

arXiv:2605.28763v1 Announce Type: new Abstract: Interactive 3D assets used in games and simulation are typically decomposed into specific semantic parts to support animation, physics, and scripted beh

Cyberbullying Governance on Social Media: A Unified Framework from Content Identification to Intervention

arXiv:2605.27584v1 Announce Type: new Abstract: The proliferation of social media platforms and online communities has inadvertently catalyzed the spread of cyberbullying, hate speech, and other forms

D^2Turb: Depth-Aware Simulation and Decoupled Learning for Single-Frame Atmospheric Turbulence Mitigation

arXiv:2605.27460v1 Announce Type: new Abstract: Single-frame atmospheric turbulence mitigation is inherently ill-posed due to spatially varying blur coupled with non-rigid geometric distortion. Existi

tutorialsarxiv-cs-cv

Deconstructing Spatial Complexity: Hierarchical Decomposition for LLM Spatial Reasoning

arXiv:2605.28144v1 Announce Type: new Abstract: LLMs have shown remarkable proficiency in general language understanding and reasoning. However, they consistently underperform in spatial reasoning tha

Decoupling Variance and Scale-Invariant Updates in Adaptive Gradient Descent for Unified Vector and Matrix Optimization

arXiv:2602.06880v2 Announce Type: replace Abstract: Adaptive methods like Adam have become the extit{de facto} standard for large-scale vector and Euclidean optimization due to their coordinate-wise a

Deep Learning Strain Estimation: Is Physics-Based Simulation the Solution?

arXiv:2605.28697v1 Announce Type: cross Abstract: Speckle tracking echocardiography (STE) is the clinical standard for myocardial strain estimation. Despite good performance on global strain (GLS), it

Deep Neural Network Training as Random Effects: An Optimization-Inference Duality

arXiv:2605.27991v1 Announce Type: cross Abstract: Deep neural networks (DNNs) have achieved remarkable empirical success, yet their training dynamics remain understood mainly from optimization rather

Delay-Aware Reinforcement Learning for Highway On-Ramp Merging under Stochastic Communication Latency

arXiv:2403.11852v5 Announce Type: replace-cross Abstract: Delayed and partially observable state information poses significant challenges for reinforcement learning (RL)-based control in real-world au

DiagramRAG: A Lightweight Framework to Retrieve Scientific Diagram for Figure Generation

arXiv:2605.27931v1 Announce Type: new Abstract: Scientific diagrams are essential for communicating complex methodologies in academic papers. A natural way for researchers to specify such diagrams is

tutorialsarxiv-cs-ai

DiscoForcing: A Unified Framework for Real-Time Audio-Driven Character Control with Diffusion Forcing

arXiv:2605.28491v1 Announce Type: new Abstract: We study real-time audio-responsive character control as a deployment-faithful problem: strictly causal, bounded-latency streaming that must generate co

safetyarxiv-cs-cv

Discovery Agents for Real-Time Analytics: Toward Proactive Insight Systems

arXiv:2605.27571v1 Announce Type: new Abstract: Modern analytics systems are fundamentally reactive, requiring users to define queries over increasingly complex and continuously evolving data. In real

agentsarxiv-cs-ai