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Enhancing Cross-Problem Vehicle Routing via Federated Learning

arXiv:2604.10652v1 Announce Type: new Abstract: Vehicle routing problems (VRPs) constitute a core optimization challenge in modern logistics and supply chain management. The recent neural combinatoria

local-aiarxiv-cs-ai

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Enhancing Fine-Grained Spatial Grounding in 3D CT Report Generation via Discriminative Guidance

DGX agent

arXiv:2604.10437v1 Announce Type: new Abstract: Vision--language models (VLMs) for radiology report generation (RRG) can produce long-form chest CT reports from volumetric scans and show strong potent

safetyarxiv-cs-cv

14 Apr 2026

Enhancing Geo-localization for Crowdsourced Flood Imagery via LLM-Guided Attention

arXiv:2512.11811v3 Announce Type: replace-cross Abstract: Crowdsourced social media imagery provides real-time visual evidence of urban flooding but often lacks reliable geographic metadata for emerge

local-aiarxiv-cs-ai

Enhancing Multilingual RAG Systems with Debiased Language Preference-Guided Query Fusion

arXiv:2601.02956v3 Announce Type: replace Abstract: Multilingual Retrieval-Augmented Generation (mRAG) systems often exhibit a perceived preference for high-resource languages, particularly English, r

local-aiarxiv-cs-cl

Enhancing Multimodal Large Language Models for Ancient Chinese Character Evolution Analysis via Glyph-Driven Fine-Tuning

arXiv:2604.11299v1 Announce Type: cross Abstract: In recent years, rapid advances in Multimodal Large Language Models (MLLMs) have increasingly stimulated research on ancient Chinese scripts. As the e

Environmental Footprint of GenAI Research: Insights from the Moshi Foundation Model

arXiv:2604.11154v1 Announce Type: new Abstract: New multi-modal large language models (MLLMs) are continuously being trained and deployed, following rapid development cycles. This generative AI frenzy

Escaping the Context Bottleneck: Active Context Curation for LLM Agents via Reinforcement Learning

arXiv:2604.11462v1 Announce Type: new Abstract: Large Language Models (LLMs) struggle with long-horizon tasks due to the 'context bottleneck' and the 'lost-in-the-middle' phenomenon, where accumulated

Agents

Evaluating Cooperation in LLM Social Groups through Elected Leadership

arXiv:2604.11721v1 Announce Type: cross Abstract: Governing common-pool resources requires agents to develop enduring strategies through cooperation and self-governance to avoid collective failure. Wh

agentsarxiv-cs-ai

Evaluating Memory Capability in Continuous Lifelog Scenario

model-releasesarxiv-cs-cl

arXiv:2604.11182v1 Announce Type: new Abstract: Nowadays, wearable devices can continuously lifelog ambient conversations, creating substantial opportunities for memory systems. However, existing benc

Evaluating Reliability Gaps in Large Language Model Safety via Repeated Prompt Sampling

arXiv:2604.09606v1 Announce Type: new Abstract: Traditional benchmarks for large language models (LLMs), such as HELM and AIR-BENCH, primarily assess safety risk through breadth-oriented evaluation ac

Evaluating Scene-based In-Situ Item Labeling for Immersive Conversational Recommendation

arXiv:2604.09698v1 Announce Type: cross Abstract: The growing ubiquity of Extended Reality (XR) is driving Conversational Recommendation Systems (CRS) toward visually immersive experiences. We formali

Evaluating Small Open LLMs for Medical Question Answering: A Practical Framework

model-releasesarxiv-cs-cl

arXiv:2604.10535v1 Announce Type: cross Abstract: Incorporating large language models (LLMs) in medical question answering demands more than high average accuracy: a model that returns substantively d

Evaluating the Impact of Medical Image Reconstruction on Downstream AI Fairness and Performance

arXiv:2604.10904v1 Announce Type: cross Abstract: AI-based image reconstruction models are increasingly deployed in clinical workflows to improve image quality from noisy data, such as low-dose X-rays

Evaluating Visual Prompts with Eye-Tracking Data for MLLM-Based Human Activity Recognition

arXiv:2604.09585v1 Announce Type: cross Abstract: Large Language Models (LLMs) have emerged as foundation models for IoT applications such as human activity recognition (HAR). However, directly applyi

Tutorials

EviCare: Enhancing Diagnosis Prediction with Deep Model-Guided Evidence for In-Context Reasoning

arXiv:2604.10455v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled promising progress in diagnosis prediction from electronic health records (EHRs). However,

tutorialsarxiv-cs-cl

EviRCOD: Evidence-Guided Probabilistic Decoding for Referring Camouflaged Object Detection

model-releasesarxiv-cs-cv

arXiv:2604.10894v1 Announce Type: new Abstract: Referring Camouflaged Object Detection (Ref-COD) focuses on segmenting specific camouflaged targets in a query image using category-aligned references.

EvoDiagram: Agentic Editable Diagram Creation via Design Expertise Evolution

model-releasesarxiv-cs-cl

arXiv:2604.09568v1 Announce Type: cross Abstract: High-fidelity diagram creation requires the complex orchestration of semantic topology, visual styling, and spatial layout, posing a significant chall

EvoESAP: Non-Uniform Expert Pruning for Sparse MoE

arXiv:2603.06003v2 Announce Type: replace Abstract: Sparse Mixture-of-Experts (SMoE) language models achieve strong capability at low per-token compute, yet deployment remains constrained by memory fo

researcharxiv-cs-lg

Evolutionary Profiles for Protein Fitness Prediction

arXiv:2510.07286v3 Announce Type: replace-cross Abstract: Predicting the fitness impact of mutations is central to protein engineering but constrained by limited assays relative to the size of sequenc

Evolutionary Token-Level Prompt Optimization for Diffusion Models

arXiv:2604.09861v1 Announce Type: new Abstract: Text-to-image diffusion models exhibit strong generative performance but remain highly sensitive to prompt formulation, often requiring extensive manual

Agents

Evolving Many Worlds: Towards Open-Ended Discovery in Petri Dish NCA via Population-Based Training

arXiv:2604.11248v1 Announce Type: cross Abstract: The generation of sustained, open-ended complexity from local interactions remains a fundamental challenge in artificial life. Differentiable multi-ag

agentsarxiv-cs-ai

EvoNash-MARL: A Closed-Loop Multi-Agent Reinforcement Learning Framework for Medium-Horizon Equity Allocation

arXiv:2604.10911v1 Announce Type: new Abstract: Medium-to-long-horizon stock allocation presents significant challenges due toveak predictive structures, non-stadonary market regimes, and the degradat

Exact Certification of Neural Networks and Partition Aggregation Ensembles against Label Poisoning

arXiv:2604.11416v1 Announce Type: new Abstract: Label-flipping attacks, which corrupt training labels to induce misclassifications at inference, remain a major threat to supervised learning models. Th

researcharxiv-cs-lg

Exact Finite-Sample Variance Decomposition of Subagging: A Spectral Filtering Perspective

arXiv:2604.10469v1 Announce Type: new Abstract: Standard resampling ratios (e.g., alpha approx 0.632) are widely used as default baselines in ensemble learning for three decades. However, how these ra

researcharxiv-cs-lg

Examining EAP Students' AI Disclosure Intention: A Cognition-Affect-Conation Perspective

arXiv:2604.10991v1 Announce Type: cross Abstract: The growing use of generative artificial intelligence (AI) in academic writing has raised increasing concerns regarding transparency and academic inte

ExecTune: Effective Steering of Black-Box LLMs with Guide Models

arXiv:2604.09741v1 Announce Type: cross Abstract: For large language models deployed through black-box APIs, recurring inference costs often exceed one-time training costs. This motivates composed age

ExPath: Targeted Pathway Inference for Biological Knowledge Bases via Graph Learning and Explanation

arXiv:2502.18026v3 Announce Type: replace-cross Abstract: Retrieving targeted pathways in biological knowledge bases, particularly when incorporating wet-lab experimental data, remains a challenging t

Expect the Unexpected? Testing the Surprisal of Salient Entities

arXiv:2604.10724v1 Announce Type: new Abstract: Previous work examining the Uniform Information Density (UID) hypothesis has shown that while information as measured by surprisal metrics is distribute

researcharxiv-cs-cl

ExpertEdit: Learning Skill-Aware Motion Editing from Expert Videos

arXiv:2604.10466v1 Announce Type: new Abstract: Visual feedback is critical for motor skill acquisition in sports and rehabilitation, and psychological studies show that observing near-perfect version

researcharxiv-cs-cv

Explainability and Certification of AI-Generated Educational Assessments

arXiv:2604.09622v1 Announce Type: cross Abstract: The rapid adoption of generative artificial intelligence (AI) in educational assessment has created new opportunities for scalable item creation, pers

Applications

Explainable Human Activity Recognition: A Unified Review of Concepts and Mechanisms

arXiv:2604.09799v1 Announce Type: cross Abstract: Human activity recognition (HAR) has become a key component of intelligent systems for healthcare monitoring, assistive living, smart environments, an

applicationsarxiv-cs-ai

Explainable Planning for Hybrid Systems

arXiv:2604.09578v1 Announce Type: new Abstract: The recent advancement in artificial intelligence (AI) technologies facilitates a paradigm shift toward automation. Autonomous systems are fully or part

Exploring Cross-Modal Flows for Few-Shot Learning

model-releasesarxiv-cs-cv

arXiv:2510.14543v4 Announce Type: replace Abstract: Aligning features from different modalities, is one of the most fundamental challenges for cross-modal tasks. Although pre-trained vision-language m

Exploring Knowledge Conflicts for Faithful LLM Reasoning: Benchmark and Method

arXiv:2604.11209v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved remarkable success across a wide range of applications especially when augmented by external knowledge thro

Exploring Knowledge Purification in Multi-Teacher Knowledge Distillation for LLMs

arXiv:2602.01064v2 Announce Type: replace Abstract: Knowledge distillation has emerged as a pivotal technique for transferring knowledge from stronger large language models (LLMs) to smaller, more eff

researcharxiv-cs-cl

Applications

Exploring Structural Complexity in Normative RAG with Graph-based approaches: A case study on the ETSI Standards

arXiv:2604.09868v1 Announce Type: cross Abstract: Industrial standards and normative documents exhibit intricate hierarchical structures, domain-specific lexicons, and extensive cross-referential depe

applicationsarxiv-cs-ai

Exploring the best way for UAV visual localization under Low-altitude Multi-view Observation Condition: a Benchmark

model-releasesarxiv-cs-cv

arXiv:2503.10692v2 Announce Type: replace Abstract: Absolute Visual Localization (AVL) enables an Unmanned Aerial Vehicle (UAV) to determine its position in GNSS-denied environments by establishing ge

Exploring the impact of fairness-aware criteria in AutoML

arXiv:2604.10224v1 Announce Type: cross Abstract: Machine Learning (ML) systems are increasingly used to support decision-making processes that affect individuals. However, these systems often rely on

ExpressMM: Expressive Mobile Manipulation Behaviors in Human-Robot Interactions

arXiv:2604.05320v2 Announce Type: replace Abstract: Mobile manipulators are increasingly deployed in human-centered environments to perform tasks. While completing such tasks, they should also be able

safetyarxiv-cs-ro

F2F-AP: Flow-to-Future Asynchronous Policy for Real-time Dynamic Manipulation

arXiv:2604.02408v2 Announce Type: replace Abstract: Asynchronous inference has emerged as a prevalent paradigm in robotic manipulation, achieving significant progress in ensuring trajectory smoothness

safetyarxiv-cs-ro

F3G-Avatar : Face Focused Full-body Gaussian Avatar

arXiv:2604.09835v1 Announce Type: cross Abstract: Existing full-body Gaussian avatar methods primarily optimize global reconstruction quality and often fail to preserve fine-grained facial geometry an

Face Density as a Proxy for Data Complexity: Quantifying the Hardness of Instance Count

arXiv:2604.09689v1 Announce Type: cross Abstract: Machine learning progress has historically prioritized model-centric innovations, yet achievable performance is frequently capped by the intrinsic com

FACT-E: Causality-Inspired Evaluation for Trustworthy Chain-of-Thought Reasoning

arXiv:2604.10693v1 Announce Type: new Abstract: Chain-of-Thought (CoT) prompting has improved LLM reasoning, but models often generate explanations that appear coherent while containing unfaithful int

Factorizing formal contexts from closures of necessity operators

arXiv:2604.09582v1 Announce Type: new Abstract: Factorizing datasets is an interesting process in a multitude of approaches, but many times it is not possible or efficient the computation of a factori

Applications

Failure Ontology: A Lifelong Learning Framework for Blind Spot Detection and Resilience Design

arXiv:2604.10549v1 Announce Type: new Abstract: Personalized learning systems are almost universally designed around a single objective: help people acquire knowledge and skills more efficiently. We a

applicationsarxiv-cs-ai

Fairboard: a quantitative framework for equity assessment of healthcare models

arXiv:2604.09656v1 Announce Type: cross Abstract: Despite there now being more than 1,000 FDA-authorised AI medical devices, formal equity assessments -- whether model performance is uniform across pa

local-aiarxiv-cs-ai

Fairness is Not Flat: Geometric Phase Transitions Against Shortcut Learning

arXiv:2604.11704v1 Announce Type: cross Abstract: Deep Neural Networks are highly susceptible to shortcut learning, frequently memorizing low-dimensional spurious correlations instead of underlying ca

FAITH: Factuality Alignment through Integrating Trustworthiness and Honestness

arXiv:2604.10189v1 Announce Type: new Abstract: Large Language Models (LLMs) can generate factually inaccurate content even if they have corresponding knowledge, which critically undermines their reli

safetyarxiv-cs-cl