Search: “applications”

EigeNet: Geometry-Informed Multi-Modal Learning for Few-shot Novel View RIR Prediction

arXiv:2605.28101v1 Announce Type: cross Abstract: Predicting spatially varying Room Impulse Response (RIR) from sparse observations is a critical but highly challenging inverse problem for immersive s

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Applications

FinBoardBench: Benchmarking Dynamic Wealth Management and Strategic Financial Reasoning of LLMs via Board Game Simulations

DGX agent

arXiv:2605.27896v1 Announce Type: new Abstract: Recently, large language models (LLMs) have achieved superior performance in static financial reasoning and simple dynamic trading tasks. However, exist

applicationsarxiv-cs-cl

28 May 2026

FLUID: From Ephemeral IDs to Multimodal Semantic Codes for Industrial-Scale Livestreaming Recommendation

arXiv:2605.21832v2 Announce Type: replace Abstract: Modern recommender systems rely heavily on ID-based collaborative filtering: each item is represented by a unique ID embedding that accumulates coll

GEM: Generative Supervision Helps Embodied Intelligence

arXiv:2605.28548v1 Announce Type: new Abstract: Embodied Vision-Language Models (VLMs) have demonstrated impressive performance and generalization in robotics, particularly within Vision-Language-Acti

GraD-IBD: Graph Representation Learning from Diagnosis Trajectories for Early Detection of Inflammatory Bowel Disease

arXiv:2605.27799v1 Announce Type: new Abstract: International Classification of Diseases (ICD) is a globally recognized coding system that records diagnostic events during each patient encounter, prov

GraphSteal: Structural Knowledge Stealing from Graph RAG via Traversal Reconstruction

arXiv:2605.28645v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances LLMs by grounding generation in query-relevant external evidence. Beyond unstructured text corpora, Grap

applicationsarxiv-cs-cl

IGADA-IoT: IoT Sensor Energy Optimization in Wireless Sensor Networks Driven by Automatic Data Augmentation

arXiv:2605.27397v1 Announce Type: new Abstract: In wireless sensor networks (WSNs), data augmentation is a novel method to improve sampling-frequency decision performance, thereby enabling energy opti

Learning after COVID-19 and the ICT career aspirations: Are students entering the AI era with weaker skills?

arXiv:2605.27391v1 Announce Type: cross Abstract: This paper examines whether students are entering the generative AI era with sufficiently strong educational foundations, focusing on the relationship

Learning to target with network interference

arXiv:2605.27794v1 Announce Type: cross Abstract: This paper studies adaptive targeting under network interference in a bandit setting, where treatments applied to one individual may affect others thr

LLM-assisted sentiment analysis for integrated computational and qualitative mixed methods education research: A case study of students' written reflection assignments

arXiv:2605.27403v1 Announce Type: cross Abstract: Written reflection assignments give students valuable opportunities for critical self-assessment, meaning making, and learning processing. Additionall

MaskClaw: Edge-Side Personalized Privacy Arbitration for GUI Agents with Behavior-Driven Skill Evolution

model-releasesarxiv-cs-cl

arXiv:2605.28646v1 Announce Type: cross Abstract: GUI agents rely on screenshots to infer intent and operate across applications, but these screenshots often contain private messages, medical records,

Measuring Massive Multitask Chinese Understanding

arXiv:2304.12986v3 Announce Type: replace-cross Abstract: The development of large-scale Chinese language models is flourishing, yet there is a lack of corresponding capability assessments. Therefore,

MIRAGE: Context-Aware Prompt Injection against Mobile GUI Agents via User-Generated Content

model-releasesarxiv-cs-ai

arXiv:2605.28116v1 Announce Type: cross Abstract: Mobile graphical user interface (GUI) agents driven by vision-language models (VLMs) perceive the screen as rendered pixels and choose actions from wh

Multi-Teacher Knowledge Distillation via Teacher-Informed Mixture Priors

arXiv:2605.27967v1 Announce Type: cross Abstract: Knowledge distillation is a powerful method for model compression, enabling the efficient deployment of complex deep learning models (teachers), inclu

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels

model-releasesarxiv-cs-ai

arXiv:2511.18894v5 Announce Type: replace-cross Abstract: Medical image segmentation is crucial for clinical applications, but it is frequently disrupted by noisy annotations and ambiguous anatomical

OphIn-500K: Curating Web-Scale Visual Instructions for Scaling Ophthalmic Multimodal Large Language Models

arXiv:2605.27916v1 Announce Type: cross Abstract: The advancement of general medical Multimodal Large Language Models (MLLMs) has shown great potential for building conversational assistants to suppor

applicationsarxiv-cs-cl

Principled Algorithms for Optimizing Generalized Metrics in Multi-Label Learning

arXiv:2605.28767v1 Announce Type: new Abstract: Many real-world classification tasks require predicting multiple labels per instance, necessitating the optimization of complex evaluation metrics such

QuITE: Query-Based Irregular Time Series Embedding

arXiv:2605.28166v1 Announce Type: cross Abstract: Irregular Multivariate Time Series (IMTS) are common in practice, yet their irregular sampling complicates effective modeling. Existing approaches typ

ResearchLoop: An Evidence-Gated Control Plane for AI-Assisted Research

arXiv:2605.28282v1 Announce Type: new Abstract: AI-assisted research compresses ideation, implementation, evaluation, and manuscript writing into a single interactive loop. This compression is useful,

SMILE-Next: Teaching Large Language Models to Detect, Classify, and Reason about Laughter

arXiv:2605.28084v1 Announce Type: cross Abstract: Laughter is a complex social signal that conveys communicative intent beyond amusement. While prior work has focused on isolated laughter analysis tas

Structure of Classifier Boundaries: Case Study for a Naive Bayes Classifier

arXiv:2212.04382v5 Announce Type: replace-cross Abstract: For a Bayes classifier whose input space is a graph, we study the structure of the boundary, which comprises those points for which at least o

Surprising Performances of Students with Autism in Classroom with NAO Robot

arXiv:2407.12014v1 Announce Type: cross Abstract: Autism is a developmental disorder that manifests in early childhood and persists throughout life, profoundly affecting social behavior and hindering

applicationsarxiv-cs-ro

T-GINEE: A Tensor-Based Multilayer Graph Representation Learning

arXiv:2605.28300v1 Announce Type: new Abstract: Traditional network analysis focuses on single-layer networks, real-world systems often form multilayer networks with multiple relationship types. Howev

Research

Tell Me a Story! Narrative-Driven XAI with Large Language Models

arXiv:2309.17057v3 Announce Type: replace Abstract: In many AI applications today, the predominance of black-box machine learning models, due to their typically higher accuracy, amplifies the need for

researcharxiv-cs-ai

Temporal Hyperbolic Graph Representation Learning for Scale-Free Internet Routing and Delay Prediction

arXiv:2605.28155v1 Announce Type: new Abstract: Predicting Internet round-trip time (RTT) is critical for routing optimization, quality-of-service (QoS) provisioning, and traffic engineering, yet rema

Safety

Towards Unified Vision-Language Models with Incomplete Multi-Modal Inputs

arXiv:2605.27894v1 Announce Type: new Abstract: Video-Language Models (VLMs) have demonstrated impressive multi-modal reasoning capabilities across diverse computer vision applications. However, these

safetyarxiv-cs-cv

XTransfer: Modality-Agnostic Few-Shot Model Transfer for Human Sensing at the Edge

model-releasesarxiv-cs-cv

arXiv:2506.22726v4 Announce Type: replace Abstract: Deep learning for human sensing on edge systems presents significant potential for smart applications. However, its training and development are hin

You Are in Control of Your State: Why Human Outcomes Are Controllable Through Causal State Intervention

arXiv:2605.27580v1 Announce Type: new Abstract: A central puzzle for the behavioural sciences and for human-facing artificial intelligence is the persistence of within-person variability. The same ind

Agile Online Model Selection: Resolving Adaptation Lag via Safeguarded Large Learning Rates

arXiv:2605.26919v1 Announce Type: new Abstract: Maintaining predictive accuracy in non-stationary environments requires online model selection to adapt autonomously to unknown distribution shifts. How

Augment Engineering: A Methodology for Multi-Tool AI Orchestration Across Professional Domains

arXiv:2605.26146v1 Announce Type: cross Abstract: Organizations increasingly deploy separate purpose-built AI tools across professional domains, often hiring domain specialists for each, recreating th

Balancing Plasticity and Stability with Fast and Slow Successor Features

arXiv:2605.26357v1 Announce Type: new Abstract: A hallmark of intelligence is the ability to adapt in non-stationary environments, yet deep Reinforcement Learning (RL) agents often struggle in such se

Bridging Classification and Reconstruction: Cooperative Time Series Anomaly Detection

model-releasesarxiv-cs-ai

arXiv:2605.26193v1 Announce Type: cross Abstract: Time series anomaly detection (TSAD) has long been a hot research topic in data mining due to its various applications. Recent studies challenge the e

Certified Causal Attribution for Real-Time Attack Forensics in 6G Network Slicing

arXiv:2605.26679v1 Announce Type: cross Abstract: Cross-slice attack attribution in 6G networks requires identifying causal propagation chains through shared infrastructure in under 100 ms. Existing m

Closing the Loop in Teleoperation: Episode-Level Data Quality Assessment and Feedback for High-Quality Demonstration Collection

arXiv:2605.26349v1 Announce Type: new Abstract: Industrial automation is at a pivotal moment, as Physical AI is driving a transition from rigid, hand-engineered automation systems toward more flexible

applicationsarxiv-cs-ro

Comparative Study of Vision-Based Metric Measurement for Large-Scale Planar Scenes

arXiv:2605.26475v1 Announce Type: cross Abstract: Vision-based metric distance and area measurement remains challenging in large-scale outdoor environments due to long-range sensing, camera zoom, and

Conceptual Schema Inference for Tabular Datasets using Large Language Models

arXiv:2509.04632v2 Announce Type: replace-cross Abstract: Large collections of tabular data from data lakes, web tables and open data portals often originate from heterogeneous sources, leading to rep

DinoComplete: 3D Shape Completion with Distilled Semantic Priors and State Space Models

arXiv:2605.26949v1 Announce Type: new Abstract: 3D shape completion from partial scans remains challenging for unseen categories and noisy real-world observations, where geometry alone is often insuff

Do Modern Post-Hoc Watermarking Methods Beat Broken-Arrows?

arXiv:2605.27135v1 Announce Type: cross Abstract: With the rapid proliferation of generative models, such as diffusion models, digital watermarking has emerged as a crucial solution for identifying AI

Examining the Challenges of Intellectual Property in AI-Generated Productions

arXiv:2605.26590v1 Announce Type: cross Abstract: With the advancement of artificial intelligence systems capable of autonomously generating artistic, literary, musical works, and even inventions with

Function-Valued Causal Influence in Nonlinear Time Series

arXiv:2605.26408v1 Announce Type: new Abstract: Causal discovery in time series is increasingly performed using nonlinear machine-learning models, yet the resulting causal relationships are almost alw

G3T Up! Gravity Aligned Coordinate Frames Simplify Pointmap Processing

arXiv:2605.27372v1 Announce Type: new Abstract: Modern feed-forward 3D reconstruction methods like VGGT predict pixel-aligned pointmaps in camera-centric coordinate frames. However, this choice of coo

Gaussian Process-based learning with new MCMC-based implementation of Wishart prior on correlation matrix

arXiv:2605.27093v1 Announce Type: cross Abstract: In probabilstic supervised learning of an input-output relationship - as a sample function of a Gaussian Process (GP) - priors are typically specified

Gaussian-Voxel Duet: A Dual-Scaffolding Hybrid Representation for Fast and Accurate Monocular Surface Reconstruction

arXiv:2605.26616v1 Announce Type: new Abstract: While 3D Gaussian Splatting has achieved remarkable success in photorealistic novel view synthesis, its pursuit of fast and high-fidelity 3D reconstruct

Generative Animations: A Multi-Model Pipeline for Prompt-Driven Motion Synthesis

arXiv:2605.27203v1 Announce Type: cross Abstract: Animation elevates digital documents into immersive experiences, yet creating custom motion paths remains cumbersome, requiring designers to manually

Generative artificial intelligence and the marginalization of minoritized knowledges in higher education: the case of disability

arXiv:2605.26769v1 Announce Type: cross Abstract: Generative artificial intelligence redefines higher education by restructuring the processes through which scientific knowledge is produced and valida

ICCU: In-Context Continual Unlearning via Pattern-Induced Refusal Rules

arXiv:2605.27138v1 Announce Type: new Abstract: Machine unlearning aims to remove the influence of specific data from trained language models. In real-world deployments, unlearning requests often arri

Implementation of Big Data Analytics for Diabetes Management: Needs Assessment in the Rwanda Healthcare System

arXiv:2605.26786v1 Announce Type: cross Abstract: Diabetes is a chronic metabolic disease that can lead to serious health problems if not diagnosed and managed early. Big Data Analytics (BDA) and mach

Leveraging Visual Signals for Robust Token-Level Uncertainty in Vision-Language Generation

arXiv:2605.27136v1 Announce Type: new Abstract: Uncertainty quantification (UQ) remains a critical challenge in Large Vision Language Models (LVLMs) for reliable predictions and real-world deployment.