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Accelerating Vision Transformers with Adaptive Patch Sizes

arXiv:2510.18091v2 Announce Type: replace-cross Abstract: Vision Transformers (ViTs) partition input images into uniformly sized patches regardless of their content, resulting in long input sequence l

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Accurate predictive model of band gap with selected important features based on explainable machine learning

DGX agent

arXiv:2503.04492v3 Announce Type: replace-cross Abstract: In the rapidly advancing field of materials informatics, nonlinear machine learning models have demonstrated exceptional predictive capabiliti

researcharxiv-cs-lg

24 Apr 2026

Achieving the Kesten-Stigum bound in the non-uniform hypergraph stochastic block model

arXiv:2604.20907v1 Announce Type: cross Abstract: We study the community detection problem in the non-uniform hypergraph stochastic block model (HSBM), where hyperedges of varying sizes coexist. This

Active Data

arXiv:2604.21044v1 Announce Type: new Abstract: In some complex domains, certain problem-specific decompositions can provide advantages over monolithic designs by enabling comprehension and specificat

Active Learning for Planet Habitability Classification under Extreme Class Imbalance

arXiv:2602.23666v2 Announce Type: replace-cross Abstract: The increasing size and heterogeneity of exoplanet catalogs have made systematic habitability assessment challenging, particularly given the e

Adaptive Defense Orchestration for RAG: A Sentinel-Strategist Architecture against Multi-Vector Attacks

arXiv:2604.20932v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) systems are increasingly deployed in sensitive domains such as healthcare and law, where they rely on private, do

Tutorials

Adaptive Instruction Composition for Automated LLM Red-Teaming

arXiv:2604.21159v1 Announce Type: cross Abstract: Many approaches to LLM red-teaming leverage an attacker LLM to discover jailbreaks against a target. Several of them task the attacker with identifyin

tutorialsarxiv-cs-ai

Adaptive Moments are Surprisingly Effective for Plug-and-Play Diffusion Sampling

arXiv:2603.16797v2 Announce Type: replace-cross Abstract: Guided diffusion sampling relies on approximating often intractable likelihood scores, which introduces significant noise into the sampling dy

safetyarxiv-cs-cv

Adaptive Soft Error Protection for Neural Network Processing

arXiv:2407.19664v3 Announce Type: replace Abstract: Previous research on selective protection for neural network components typically exploits only static vulnerability differences. Although these met

Adaptive Test-Time Compute Allocation with Evolving In-Context Demonstrations

arXiv:2604.21018v1 Announce Type: new Abstract: While scaling test-time compute can substantially improve model performance, existing approaches either rely on static compute allocation or sample from

Addressing divergent representations from causal interventions on neural networks

arXiv:2511.04638v5 Announce Type: replace-cross Abstract: A common approach to mechanistic interpretability is to causally manipulate model representations via targeted interventions in order to under

Addressing Image Authenticity When Cameras Use Generative AI

arXiv:2604.21879v1 Announce Type: cross Abstract: The ability of generative AI (GenAI) methods to photorealistically alter camera images has raised awareness about the authenticity of images shared on

ADS-POI: Agentic Spatiotemporal State Decomposition for Next Point-of-Interest Recommendation

arXiv:2604.20846v1 Announce Type: cross Abstract: Next point-of-interest (POI) recommendation requires modeling user mobility as a spatiotemporal sequence, where different behavioral factors may evolv

Applications

Adversarial Evasion in Non-Stationary Malware Detection: Minimizing Drift Signals through Similarity-Constrained Perturbations

arXiv:2604.21310v1 Announce Type: cross Abstract: Deep learning has emerged as a powerful approach for malware detection, demonstrating impressive accuracy across various data representations. However

applicationsarxiv-cs-ai

AEL: Agent Evolving Learning for Open-Ended Environments

arXiv:2604.21725v1 Announce Type: cross Abstract: LLM agents increasingly operate in open-ended environments spanning hundreds of sequential episodes, yet they remain largely stateless: each task is s

AFRILANGTUTOR: Advancing Language Tutoring and Culture Education in Low-Resource Languages with Large Language Models

model-releasesarxiv-cs-cl

arXiv:2604.20996v1 Announce Type: new Abstract: How can language learning systems be developed for languages that lack sufficient training resources? This challenge is increasingly faced by developers

AgentDoG: A Diagnostic Guardrail Framework for AI Agent Safety and Security

arXiv:2601.18491v2 Announce Type: replace Abstract: The rise of AI agents introduces complex safety and security challenges arising from autonomous tool use and environmental interactions. Current gua

AgentGL: Towards Agentic Graph Learning with LLMs via Reinforcement Learning

arXiv:2604.05846v2 Announce Type: replace Abstract: Large Language Models (LLMs) increasingly rely on agentic capabilities-iterative retrieval, tool use, and decision-making-to overcome the limits of

safetyarxiv-cs-cl

Agentic AI-assisted coding offers a unique opportunity to instill epistemic grounding during software development

arXiv:2604.21744v1 Announce Type: cross Abstract: The capabilities of AI-assisted coding are progressing at breakneck speed. Chat-based vibe coding has evolved into fully fledged AI-assisted, agentic

Agentic AI for Personalized Physiotherapy: A Multi-Agent Framework for Generative Video Training and Real-Time Pose Correction

arXiv:2604.21154v1 Announce Type: new Abstract: At-home physiotherapy compliance remains critically low due to a lack of personalized supervision and dynamic feedback. Existing digital health solution

AgenticQwen: Training Small Agentic Language Models with Dual Data Flywheels for Industrial-Scale Tool Use

arXiv:2604.21590v1 Announce Type: new Abstract: Modern industrial applications increasingly demand language models that act as agents, capable of multi-step reasoning and tool use in real-world settin

agentsarxiv-cs-cl

AGNT2: Autonomous Agent Economies on Interaction-Optimized Layer 2 Infrastructure

arXiv:2604.21129v1 Announce Type: cross Abstract: Current blockchain Layer 2 solutions, including Optimism, Arbitrum, zkSync, and their derivatives, optimize for human-initiated financial transactions

AI for software engineering: from probable to provable

arXiv:2511.23159v2 Announce Type: replace-cross Abstract: Vibe coding, the much-touted use of AI techniques for programming, faces two overwhelming obstacles: the difficulty of specifying goals ('prom

AI Governance under Political Turnover: The Alignment Surface of Compliance Design

arXiv:2604.21103v1 Announce Type: new Abstract: Governments are increasingly interested in using AI to make administrative decisions cheaper, more scalable, and more consistent. But for probabilistic

AI-Gram: When Visual Agents Interact in a Social Network

arXiv:2604.21446v1 Announce Type: new Abstract: We present AI-Gram, a live platform enabling image-based interactions, to study social dynamics in a fully autonomous multi-agent visual network where a

AITP: Traffic Accident Responsibility Allocation via Multimodal Large Language Models

model-releasesarxiv-cs-cl

arXiv:2604.20878v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress in Traffic Accident Detection (TAD) and Traffic Accident Understanding (TAU).

Algebraic Language Models for Inverse Design of Metamaterials via Diffusion Transformers

arXiv:2507.15753v2 Announce Type: replace-cross Abstract: Generative machine learning models have revolutionized material discovery by capturing complex structure-property relationships, yet extending

Align Generative Artificial Intelligence with Human Preferences: A Novel Large Language Model Fine-Tuning Method for Online Review Management

arXiv:2604.21209v1 Announce Type: new Abstract: Online reviews have played a pivotal role in consumers' decision-making processes. Existing research has highlighted the significant impact of manageria

Alignment has a Fantasia Problem

arXiv:2604.21827v1 Announce Type: new Abstract: Modern AI assistants are trained to follow instructions, implicitly assuming that users can clearly articulate their goals and the kind of assistance th

An effective variant of the Hartigan k-means algorithm

arXiv:2604.21798v1 Announce Type: new Abstract: The k-means problem is perhaps the classical clustering problem and often synonymous with Lloyd's algorithm (1957). It has become clear that Hartigan's

Local Ai

an interpretable vision transformer framework for automated brain tumor classification

arXiv:2604.21311v1 Announce Type: new Abstract: Brain tumors represent one of the most critical neurological conditions, where early and accurate diagnosis is directly correlated with patient survival

local-aiarxiv-cs-cv

An Overlay Multicast Routing Method Based on Network Situational Awareness and Hierarchical Multi-Agent Reinforcement Learning

arXiv:2602.13211v2 Announce Type: replace-cross Abstract: Compared with IP multicast, Overlay Multicast (OM) offers better compatibility and flexible deployment in heterogeneous, cross-domain networks

Analytical FFN-to-MoE Restructuring via Activation Pattern Analysis

arXiv:2502.04416v3 Announce Type: replace-cross Abstract: Scaling large language models (LLMs) improves performance but significantly increases inference costs, with feed-forward networks (FFNs) consu

Anatomy-Aware Text-Visual Fusion with Dual-Perspective Prompts for Fine-Grained Lumbar Spine Segmentation

arXiv:2504.03476v2 Announce Type: replace Abstract: Accurate lumbar spine segmentation is crucial for diagnosing spinal disorders. Existing methods typically use coarse-grained segmentation strategies

researcharxiv-cs-cv

Applications

Anomaly Detection in Smart Power Grids with Graph-Regularized MS-SVDD: a Multimodal Subspace Learning Approach

arXiv:2502.15793v2 Announce Type: replace Abstract: Anomaly detection in smart power grids is a critical challenge due to the complexity, heterogeneity, and dynamic nature of sensor data streams. Exis

applicationsarxiv-cs-lg

APCoTTA: Continual Test-Time Adaptation for Semantic Segmentation of Airborne LiDAR Point Clouds

model-releasesarxiv-cs-cv

arXiv:2505.09971v3 Announce Type: replace Abstract: Airborne laser scanning (ALS) point cloud semantic segmentation is a fundamental task for large-scale 3D scene understanding. Fixed models deployed

Tutorials

Architecture of an AI-Based Automated Course of Action Generation System for Military Operations

arXiv:2604.20862v1 Announce Type: new Abstract: The automation system for Course of Action (CoA) planning is an essential element in future warfare. As maneuver speeds increase, surveillance ranges ex

tutorialsarxiv-cs-ai

Architectures for Robust Self-Organizing Energy Systems under Information and Control Constraints

arXiv:2604.21529v1 Announce Type: cross Abstract: Applying the concept of controlled self-organization in agent-based Cyber-Physical Energy Systems (CPES) is a promising approach to ensure system robu

ARFBench: Benchmarking Time Series Question Answering Ability for Software Incident Response

model-releasesarxiv-cs-cv

arXiv:2604.21199v1 Announce Type: cross Abstract: Time series question-answering (TSQA), in which we ask natural language questions to infer and reason about properties of time series, is a promising

Artificial intelligence for methane detection: from continuous monitoring to verified mitigation

arXiv:2511.21777v2 Announce Type: replace Abstract: Methane is a potent greenhouse gas, responsible for roughly 30% of warming since pre-industrial times. A small number of large point sources account

Assessing Emulator Design and Training for Modal Aerosol Microphysics Parameterizations in E3SMv2

arXiv:2604.21233v1 Announce Type: cross Abstract: Toward the goal of using Scientific Machine Learning (SciML) emulators to improve the numerical representation of aerosol processes in global atmosphe

Hardware

Association Is Not Similarity: Learning Corpus-Specific Associations for Multi-Hop Retrieval

arXiv:2604.20850v1 Announce Type: cross Abstract: Dense retrieval systems rank passages by embedding similarity to a query, but multi-hop questions require passages that are associatively related thro

hardwarearxiv-cs-ai

ATATA: One Algorithm to Align Them All

arXiv:2601.11194v2 Announce Type: replace Abstract: We suggest a new multi-modal algorithm for joint inference of paired structurally aligned samples with Rectified Flow models. While some existing me

safetyarxiv-cs-cv

ATLAS: AI-Assisted Threat-to-Assertion Learning for System-on-Chip Security Verification

arXiv:2603.01170v2 Announce Type: replace-cross Abstract: This work presents ATLAS, an LLM-driven framework that bridges standardized threat modeling and property-based formal verification for System-

ATOM: A Pretrained Neural Operator for Multitask Molecular Dynamics

arXiv:2510.05482v2 Announce Type: replace Abstract: Molecular dynamics (MD) simulations underpin modern computational drug discovery, materials science, and biochemistry. Recent machine learning model

AtomicRAG: Atom-Entity Graphs for Retrieval-Augmented Generation

arXiv:2604.20844v1 Announce Type: cross Abstract: Recent GraphRAG methods integrate graph structures into text indexing and retrieval, using knowledge graph triples to connect text chunks, thereby imp

AttDiff-GAN: A Hybrid Diffusion-GAN Framework for Facial Attribute Editing

arXiv:2604.21289v1 Announce Type: new Abstract: Facial attribute editing aims to modify target attributes while preserving attribute-irrelevant content and overall image fidelity. Existing GAN-based m

safetyarxiv-cs-cv

Attention-based multiple instance learning for predominant growth pattern prediction in lung adenocarcinoma wsi using foundation models

arXiv:2604.21530v1 Announce Type: cross Abstract: Lung adenocarcinoma (LUAD) grading depends on accurately identifying growth patterns, which are indicators of prognosis and can influence treatment de