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A Unified Fractional Regularization Framework for Sparse Recovery

arXiv:2604.23184v1 Announce Type: cross Abstract: We propose a unified fractional regularization framework for sparse signal recovery based on the ell_1/ell_p^q model. Our main theoretical contributio

researcharxiv-cs-lg

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A2DEPT: Large Language Model-Driven Automated Algorithm Design via Evolutionary Program Trees

DGX agent

arXiv:2604.24043v1 Announce Type: new Abstract: Designing heuristics for combinatorial optimization problems (COPs) is a fundamental yet challenging task that traditionally requires extensive domain e

researcharxiv-cs-ai

28 Apr 2026

Accelerating Eigenvalue Dataset Generation via Chebyshev Subspace Filter

arXiv:2510.23215v2 Announce Type: replace-cross Abstract: Eigenvalue problems are among the most important topics in many scientific disciplines. With the recent surge and development of machine learn

researcharxiv-cs-ai

Accelerating Frequency Domain Diffusion Models with Error-Feedback Event-Driven Caching

arXiv:2604.22901v1 Announce Type: new Abstract: Diffusion models achieve remarkable success in time series generation. However, slow inference limits their practical deployment. We propose E^2-CRF (Er

researcharxiv-cs-lg

Accelerating New Product Introduction for Visual Quality Inspection via Few-Shot Diffusion-Based Defect Synthesis

arXiv:2604.22850v1 Announce Type: new Abstract: Industrial visual inspection systems often suffer from a severe scarcity of labeled defect data, particularly during the early stages of New Product Int

researcharxiv-cs-cv

Accelerating Quantum Materials Characterization: Hybrid Active Learning for Autonomous Spin Wave Spectroscopy

model-releasesarxiv-cs-lg

arXiv:2604.23821v1 Announce Type: cross Abstract: Autonomous neutron spectroscopy must solve three distinct tasks: detection (where is the signal?), inference (which Hamiltonian governs it?), and refi

Accelerating Reinforcement Learning for Wind Farm Control via Expert Demonstrations

arXiv:2604.22794v1 Announce Type: cross Abstract: Reinforcement learning (RL) offers a promising approach for adaptive wind farm flow control, yet its practical deployment is hindered by slow training

agentsarxiv-cs-lg

Active Inference: A method for Phenotyping Agency in AI systems?

arXiv:2604.23278v1 Announce Type: new Abstract: The proliferation of agentic artificial intelligence has outpaced the conceptual tools needed to characterize agency in computational systems. Prevailin

AD-Relight: Training-Free Banner Relighting via Illumination Translation with Diffusion Priors

arXiv:2604.24407v1 Announce Type: new Abstract: The recent surge in content consumption through streaming services has driven a growing demand for personalized content. Personalized advertisements (ad

researcharxiv-cs-cv

AdaComp: Extractive Context Compression with Adaptive Predictor for Retrieval-Augmented Large Language Models

arXiv:2409.01579v2 Announce Type: replace-cross Abstract: Retrieved documents containing noise will hinder RAG from detecting answer clues and make the inference process slow and expensive. Therefore,

researcharxiv-cs-ai

Applications

AdaMamba: Adaptive Frequency-Gated Mamba for Long-Term Time Series Forecasting

arXiv:2604.23239v1 Announce Type: new Abstract: Accurate long-term time series forecasting (LTSF) requires the capture of complex long-range dependencies and dynamic periodic patterns. Recent advances

applicationsarxiv-cs-ai

AdapTime: Enabling Adaptive Temporal Reasoning in Large Language Models

arXiv:2604.24175v1 Announce Type: cross Abstract: Large language models have demonstrated strong reasoning capabilities in general knowledge question answering. However, their ability to handle tempor

researcharxiv-cs-ai

Adaptive-Distribution Randomized Neural Networks for PDEs: A Low-Dimensional Distribution-Learning Framework

model-releasesarxiv-cs-lg

arXiv:2604.23999v1 Announce Type: cross Abstract: Randomized neural networks (RaNNs) are attractive for partial differential equations (PDEs) because they replace expensive end-to-end training with a

Adaptive Multi-Subspace Representation Steering for Attribute Alignment in Large Language Models

arXiv:2508.10599v4 Announce Type: replace Abstract: Activation steering offers a promising approach to controlling the behavior of Large Language Models by directly manipulating their internal activat

Adaptive ToR: Complexity-Aware Tree-Based Retrieval for Pareto-Optimal Multi-Intent NLU

arXiv:2604.24219v1 Announce Type: new Abstract: Multi-intent natural language understanding requires retrieval systems that simultaneously achieve high accuracy and computational efficiency, yet exist

AdaRubric: Task-Adaptive Rubrics for LLM Agent Evaluation

arXiv:2603.21362v2 Announce Type: replace Abstract: LLM-as-Judge evaluation fails agent tasks because a fixed rubric cannot capture what matters for this task: code debugging demands Correctness and E

Additive Control Variates Dominate Self-Normalisation in Off-Policy Evaluation

arXiv:2602.14914v2 Announce Type: replace Abstract: Off-policy evaluation (OPE) is essential for assessing ranking and recommendation systems without costly online interventions. Self-Normalised Inver

safetyarxiv-cs-lg

Advancing Ligand-based Virtual Screening and Molecular Generation with Pretrained Molecular Embedding Distance

arXiv:2604.24474v1 Announce Type: new Abstract: Molecular similarity plays a central role in ligand-based drug discovery, such as virtual screening, analog searching, and goal-directed molecular gener

researcharxiv-cs-lg

Advancing Remote Medical Palpation through Cognition and Emotion

arXiv:2407.05595v3 Announce Type: replace Abstract: Medical palpation is more than force transmission. It is a bidirectional cognitive and emotional exchange between doctor and patient. We model two c

researcharxiv-cs-ro

Adversary-Free Counterfactual Prediction via Information-Regularized Representations

arXiv:2510.15479v2 Announce Type: replace Abstract: We study counterfactual prediction under assignment bias and propose a mathematically grounded, information-theoretic approach that removes treatmen

safetyarxiv-cs-lg

AeSlides: Incentivizing Aesthetic Layout in LLM-Based Slide Generation via Verifiable Rewards

model-releasesarxiv-cs-cl

arXiv:2604.22840v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong potential in agentic tasks, particularly in slide generation. However, slide generation poses a

Affordance-R1: Reinforcement Learning for Generalizable Affordance Reasoning in Multimodal Large Language Model

model-releasesarxiv-cs-cv

arXiv:2508.06206v4 Announce Type: replace-cross Abstract: Affordance grounding focuses on predicting the specific regions of objects that are associated with the actions to be performed by robots. It

Agent-Aided Design for Dynamic CAD Models

arXiv:2604.15184v2 Announce Type: replace Abstract: In the past year, researchers have created agentic systems that can design real-world CAD-style objects in a training-free setting, a new variety of

Agent-Centric Visual Reinforcement Learning under Dynamic Perturbations

model-releasesarxiv-cs-ro

arXiv:2604.24661v1 Announce Type: new Abstract: Visual reinforcement learning aims to empower an agent to learn policies from visual observations, yet it remains vulnerable to dynamic visual perturbat

AgentEval: DAG-Structured Step-Level Evaluation for Agentic Workflows with Error Propagation Tracking

arXiv:2604.23581v1 Announce Type: cross Abstract: Agentic systems that chain reasoning, tool use, and synthesis into multi-step workflows are entering production, yet prevailing evaluation practices l

agentsarxiv-cs-cl

AgentHER: Hindsight Experience Replay for LLM Agent Trajectory Relabeling

arXiv:2603.21357v3 Announce Type: replace Abstract: LLM agents fail on the majority of real-world tasks -- GPT-4o succeeds on fewer than 15% of WebArena navigation tasks and below 55% pass@1 on ToolBe

Agentic Adversarial Rewriting Exposes Architectural Vulnerabilities in Black-Box NLP Pipelines

arXiv:2604.23483v1 Announce Type: new Abstract: Multi-component natural language processing (NLP) pipelines are increasingly deployed for high-stakes decisions, yet no existing adversarial method can

Agentic AI platforms for autonomous training and rule induction of human-human and virus-human protein-protein interactions

arXiv:2604.23924v1 Announce Type: new Abstract: We instruct an AI agent to construct two separate agentic AI platforms: one for autonomous training of predictive ML models for human-human and virus-hu

Agentic clinical reasoning over longitudinal myeloma records: a retrospective evaluation against expert consensus

arXiv:2604.24473v1 Announce Type: new Abstract: Multiple myeloma is managed through sequential lines of therapy over years to decades, with each decision depending on cumulative disease history distri

Hardware

Agentic Fusion of Large Atomic and Language Models to Accelerate Materials Discovery

arXiv:2604.23758v1 Announce Type: new Abstract: The discovery of novel materials is critical for global energy and quantum technology transitions. While deep learning has fundamentally reshaped this l

hardwarearxiv-cs-lg

Agentic Hives: Equilibrium, Indeterminacy, and Endogenous Cycles in Self-Organizing Multi-Agent Systems

arXiv:2603.00130v2 Announce Type: replace-cross Abstract: Current multi-agent AI systems operate with a fixed number of agents whose roles are specified at design time. No formal theory governs when a

Agentic Witnessing: Pragmatic and Scalable TEE-Enabled Privacy-Preserving Auditing

arXiv:2604.24203v1 Announce Type: cross Abstract: Auditing the semantic properties of proprietary data creates a fundamental tension: verification requires transparent access, while proprietary rights

Local Ai

AgenticCache: Cache-Driven Asynchronous Planning for Embodied AI Agents

arXiv:2604.24039v1 Announce Type: cross Abstract: Embodied AI agents increasingly rely on large language models (LLMs) for planning, yet per-step LLM calls impose severe latency and cost. In this pape

local-aiarxiv-cs-ai

AgentPulse: A Continuous Multi-Signal Framework for Evaluating AI Agents in Deployment

arXiv:2604.24038v1 Announce Type: new Abstract: Static benchmarks measure what AI agents can do at a fixed point in time but not how they are adopted, maintained, or experienced in deployment. We intr

AgentRVOS for MeViS-Text Track of 5th PVUW Challenge: 3rd Method

arXiv:2604.22836v1 Announce Type: new Abstract: This report describes a Ref-VOS pipeline centered on Sa2VA and organized with explicit agent roles. The key idea is that Sa2VA should provide the first

agentsarxiv-cs-cv

AgentWard: A Lifecycle Security Architecture for Autonomous AI Agents

arXiv:2604.24657v1 Announce Type: cross Abstract: Autonomous AI agents extend large language models into full runtime systems that load skills, ingest external content, maintain memory, plan multi-ste

Agri-CPJ: A Training-Free Explainable Framework for Agricultural Pest Diagnosis Using Caption-Prompt-Judge and LLM-as-a-Judge

arXiv:2604.23701v1 Announce Type: cross Abstract: Crop disease diagnosis from field photographs faces two recurring problems: models that score well on benchmarks frequently hallucinate species names,

Applications

AI-Assisted Code Review as a Scaffold for Code Quality and Self-Regulated Learning: An Experience Report

arXiv:2604.23251v1 Announce Type: cross Abstract: Code review is central to software engineering education but hard to scale in capstone projects due to tight deadlines, uneven peer feedback, and limi

applicationsarxiv-cs-ai

AI Identity: Standards, Gaps, and Research Directions for AI Agents

arXiv:2604.23280v1 Announce Type: new Abstract: AI agents are now running real transactions, workflows, and sub-agent chains across organizational boundaries without continuous human supervision. This

AI Safety Training Can be Clinically Harmful

arXiv:2604.23445v1 Announce Type: cross Abstract: Large language models are being deployed as mental health support agents at scale, yet only 16% of LLM-based chatbot interventions have undergone rigo

AI Security Beyond Core Domains: Resume Screening as a Case Study of Adversarial Vulnerabilities in Specialized LLM Applications

arXiv:2512.20164v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) excel at text comprehension and generation, making them ideal for automated tasks like code review and content mo

Local Ai

AI use in American newspapers is widespread, uneven, and rarely disclosed

arXiv:2510.18774v4 Announce Type: replace Abstract: AI is rapidly transforming journalism, but the extent of its use in published newspaper articles remains unclear. We address this gap by auditing a

local-aiarxiv-cs-cl

AIPsy-Affect: A Keyword-Free Clinical Stimulus Battery for Mechanistic Interpretability of Emotion in Language Models

arXiv:2604.23719v1 Announce Type: cross Abstract: Mechanistic interpretability research on emotion in large language models -- linear probing, activation patching, sparse autoencoder (SAE) feature ana

Airspeed Forward-Invariance for Unpowered Fixed-Wing Aircraft

arXiv:2604.22860v1 Announce Type: new Abstract: Autonomous fixed-wing flight is becoming a key capability in aerial robotics, enabling sensing, mobility, and contingency operations across both small-s

agentsarxiv-cs-ro

Algorithmic Administration and the EU AI Act: Legal Principles for Public Sector Use of AI

arXiv:2604.22765v1 Announce Type: cross Abstract: The increasing use of artificial intelligence (AI) by public authorities introduces both opportunities for innovation and significant challenges for t

Aligned Multi-View Scripts for Universal Chart-to-Code Generation

arXiv:2604.24559v1 Announce Type: cross Abstract: Chart-to-code generation converts a chart image into an executable plotting script, enabling faithful reproduction and editable visualizations. Existi

Aligning with Your Own Voice: Self-Corrected Preference Learning for Hallucination Mitigation in LVLMs

arXiv:2604.24395v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) frequently suffer from hallucinations. Existing preference learning-based approaches largely rely on proprietary mo

All That Glitters Is Not Audio: Rethinking Text Priors and Audio Reliance in Audio-Language Evaluation

arXiv:2604.24401v1 Announce Type: cross Abstract: Large Audio-Language Models show consistent performance gains across speech and audio benchmarks, yet high scores may not reflect true auditory percep