All entries

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

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

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

DGX agent

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

model-releasesarxiv-cs-cl

14 Apr 2026

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

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

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

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

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

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

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

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

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

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

Local 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

Fake-HR1: Rethinking Reasoning of Vision Language Model for Synthetic Image Detection

arXiv:2602.10042v3 Announce Type: replace-cross Abstract: Recent studies have demonstrated that incorporating Chain-of-Thought (CoT) reasoning into the detection process can enhance a model's ability

FashionMV: Product-Level Composed Image Retrieval with Multi-View Fashion Data

arXiv:2604.10297v1 Announce Type: cross Abstract: Composed Image Retrieval (CIR) retrieves target images using a reference image paired with modification text. Despite rapid advances, all existing met

Fast-SegSim: Real-Time Open-Vocabulary Segmentation for Robotics in Simulation

arXiv:2604.10951v1 Announce Type: new Abstract: Open-vocabulary panoptic reconstruction is crucial for advanced robotics and simulation. However, existing 3D reconstruction methods, such as NeRF or Ga

researcharxiv-cs-ro

FastSHADE: Fast Self-augmented Hierarchical Asymmetric Denoising for Efficient inference on mobile devices

arXiv:2604.10275v1 Announce Type: new Abstract: Real-time image denoising is essential for modern mobile photography but remains challenging due to the strict latency and power constraints of edge dev

Fatigue-PINN: Physics-Informed Fatigue-Driven Motion Modulation and Synthesis

arXiv:2502.19056v2 Announce Type: replace-cross Abstract: Fatigue modeling is essential for motion synthesis tasks to model human motions under fatigued conditions and biomechanical engineering applic

safetyarxiv-cs-lg

FatigueFusion: Latent Space Fusion for Fatigue-Driven Motion Synthesis

arXiv:2604.10199v1 Announce Type: cross Abstract: Investigating the impact of fatigue on human physiological function and motor behavior is crucial for developing biomechanics and medical applications

FEDBUD: Joint Incentive and Privacy Optimization for Resource-Constrained Federated Learning

arXiv:2604.10499v1 Announce Type: cross Abstract: Federated learning has become a popular paradigm for privacy protection and edge-based machine learning. However, defending against differential attac

applicationsarxiv-cs-lg

Federated Single-Agent Robotics: Multi-Robot Coordination Without Intra-Robot Multi-Agent Fragmentation

arXiv:2604.11028v1 Announce Type: cross Abstract: As embodied robots move toward fleet-scale operation, multi-robot coordination is becoming a central systems challenge. Existing approaches often trea

FedKLPR: KL-Guided Pruning-Aware Federated Learning for Person Re-Identification

arXiv:2508.17431v3 Announce Type: replace-cross Abstract: Person re-identification (re-ID) is a fundamental task in intelligent surveillance and public safety. Federated learning (FL) provides a priva

Local Ai

FedQUIT: On-Device Federated Unlearning via a Quasi-Competent Virtual Teacher

arXiv:2408.07587v4 Announce Type: replace Abstract: Federated Learning (FL) enables the collaborative training of machine learning models without requiring centralized collection of user data. To comp

local-aiarxiv-cs-lg