Search: “context”

AusSmoke meets MultiNatSmoke: a fully-labelled diverse smoke segmentation dataset

arXiv:2604.23542v1 Announce Type: new Abstract: Wildfires are an escalating global concern due to the devastating impacts on the environment, economy, and human health, with notable incidents such as

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BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal

DGX agent

arXiv:2604.24428v1 Announce Type: cross Abstract: Electroencephalography (EEG) is highly susceptible to artifact contamination, such as electrooculographic (EOG) and electromyographic (EMG) interferen

model-releasesarxiv-cs-ai

28 Apr 2026

Benchmarking Pathology Foundation Models for Breast Cancer Survival Prediction

arXiv:2604.24679v1 Announce Type: new Abstract: Pathology foundation models (PFMs) have recently emerged as powerful pretrained encoders for computational pathology, enabling transfer learning across

Benchmarking Testing in Automated Theorem Proving

model-releasesarxiv-cs-cl

arXiv:2604.23698v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have shown promise in formal theorem proving, yet evaluating semantic correctness remains challenging. E

Beyond Match Maximization and Fairness: Retention-Optimized Two-Sided Matching

arXiv:2602.15752v2 Announce Type: replace Abstract: On two-sided matching platforms such as online dating and recruiting, recommendation algorithms often aim to maximize the total number of matches. H

safetyarxiv-cs-lg

Beyond the Attention Stability Boundary: Agentic Self-Synthesizing Reasoning Protocols

arXiv:2604.24512v1 Announce Type: new Abstract: As LLM agents transition to autonomous digital coworkers, maintaining deterministic goal-directedness in non-linear multi-turn conversations emerged as

Breaking the Resource Wall: Geometry-Guided Sequence Modeling for Efficient Semantic Segmentation

arXiv:2604.23399v1 Announce Type: new Abstract: High-performance semantic segmentation has achieved significant progress in recent years, often driven by increasingly large backbones and higher comput

local-aiarxiv-cs-cv

Bridging Reasoning and Action: Hybrid LLM-RL Framework for Efficient Cross-Domain Task-Oriented Dialogue

arXiv:2604.23345v1 Announce Type: new Abstract: Cross-domain task-oriented dialogue requires reasoning over implicit and explicit feasibility constraints while planning long-horizon, multi-turn action

safetyarxiv-cs-cl

CA-IDD: Cross-Attention Guided Identity-Conditional Diffusion for Identity-Consistent Face Swapping

arXiv:2604.24493v1 Announce Type: new Abstract: Face swapping aims to optimize realistic facial image generation by leveraging the identity of a source face onto a target face while preserving pose, e

safetyarxiv-cs-cv

CFDLLMBench: A Benchmark Suite for Evaluating Large Language Models in Computational Fluid Dynamics

arXiv:2509.20374v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated strong performance across general NLP tasks, but their utility in automating numerical experime

CLIN-LLM: A Safety-Constrained Hybrid Framework for Clinical Diagnosis and Treatment Generation

arXiv:2510.22609v2 Announce Type: replace Abstract: Accurate symptom-to-disease classification and clinically grounded treatment recommendations remain challenging, particularly in heterogeneous patie

CLIP-Guided Data Augmentation for Night-Time Image Dehazing

arXiv:2604.05500v2 Announce Type: replace Abstract: Nighttime image dehazing faces a more complex degradation pattern than its daytime counterpart, as haze scattering couples with low illumination, no

researcharxiv-cs-cv

CNN-ViT Fusion with Adaptive Attention Gate for Brain Tumor MRI Classification: A Hybrid Deep Learning Model

arXiv:2604.23137v1 Announce Type: cross Abstract: Early detection and classifying brain tumors using Magnetic Resonance Imaging (MRI) images is highly important but difficult to extract in medical ima

local-aiarxiv-cs-ai

Code Broker: A Multi-Agent System for Automated Code Quality Assessment

arXiv:2604.23088v1 Announce Type: cross Abstract: We present Code Broker, a multi agent system built with Google Agent Development Kit ADK that analyses Python code from files, local directories, or G

local-aiarxiv-cs-ai

Conditional Imputation for Within-Modality Missingness in Multi-Modal Federated Learning

arXiv:2604.23112v1 Announce Type: new Abstract: Multimodal Federated Learning (MMFL) enables privacy-preserving collaborative training, but real-world clinical applications often suffer from within-mo

safetyarxiv-cs-lg

Tutorials

Deep Learning of Solver-Aware Turbulence Closures from Nudged LES Dynamics

arXiv:2604.23874v1 Announce Type: cross Abstract: Deep learning approaches have shown remarkable promise in turbulence closure modeling for large eddy simulations (LES). The differentiable physics par

tutorialsarxiv-cs-lg

Designing escalation criteria for international AI incident response: criteria, triggers, and thresholds

arXiv:2604.23183v1 Announce Type: cross Abstract: AI incident reporting requirements are emerging in regulation and policy, yet no operational criteria exist for determining when a detected AI inciden

Detecting and Evaluating Medical Hallucinations in Large Vision Language Models

arXiv:2406.10185v2 Announce Type: replace Abstract: Large Vision Language Models (LVLMs) are increasingly integral to healthcare applications, including medical visual question answering and imaging r

Diagnostic-Driven Layer-Wise Compensation for Post-Training Quantization of Encoder-Decoder ASR Models

arXiv:2601.02455v2 Announce Type: replace-cross Abstract: Deploying Automatic Speech Recognition (ASR) models on memory-constrained edge devices requires aggressive low-bit weight quantization. Layer-

researcharxiv-cs-cl

DLM: Unified Decision Language Models for Offline Multi-Agent Sequential Decision Making

arXiv:2604.23557v1 Announce Type: cross Abstract: Building scalable and reusable multi-agent decision policies from offline datasets remains a challenge in offline multi-agent reinforcement learning (

DO-Bench: An Attributable Benchmark for Diagnosing Object Hallucination in Vision-Language Models

arXiv:2604.22822v1 Announce Type: cross Abstract: Object level hallucination remains a central reliability challenge for vision language models (VLMs), particularly in binary object existence verifica

Domain Fine-Tuning vs. Retrieval-Augmented Generation for Medical Multiple-Choice Question Answering: A Controlled Comparison at the 4B-Parameter Scale

model-releasesarxiv-cs-cl

arXiv:2604.23801v1 Announce Type: new Abstract: Practitioners deploying small open-weight large language models (LLMs) for medical question answering face a recurring design choice: invest in a domain

DRACULA: Hunting for the Actions Users Want Deep Research Agents to Execute

arXiv:2604.23815v1 Announce Type: new Abstract: Scientific Deep Research (DR) agents answer user queries by synthesizing research papers into multi-section reports. User feedback can improve their uti

agentsarxiv-cs-cl

EAD-Net: Emotion-Aware Talking Head Generation with Spatial Refinement and Temporal Coherence

arXiv:2604.23325v1 Announce Type: cross Abstract: Emotionally talking head video generation aims to generate expressive portrait videos with accurate lip synchronization and emotional facial expressio

EmoTrans: A Benchmark for Understanding, Reasoning, and Predicting Emotion Transitions in Multimodal LLMs

arXiv:2604.23348v1 Announce Type: cross Abstract: Recent multimodal large language models (MLLMs) have shown strong capabilities in perception, reasoning, and generation, and are increasingly used in

ESIA: An Energy-Based Spatiotemporal Interaction-Aware Framework for Pedestrian Intention Prediction

arXiv:2604.23728v1 Announce Type: cross Abstract: Recent advances in autonomous driving have motivated research on pedestrian intention prediction, which aims to infer future crossing decisions and ac

agentsarxiv-cs-ai

EXACT: an explainable anomaly-aware vision foundation model for analysis of 3D chest CT

arXiv:2604.24146v1 Announce Type: new Abstract: Chest computed tomography (CT) is central to the detection and management of thoracic disease, yet the growing scale and complexity of volumetric imagin

local-aiarxiv-cs-cv

Applications

Expert Evaluation of LLM's Open-Ended Legal Reasoning on the Japanese Bar Exam Writing Task

arXiv:2604.23730v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong performance on legal benchmarks, including multiple-choice components of bar exams. However, their capaci

applicationsarxiv-cs-ai

Extending Precipitation Nowcasting Horizons via Spectral Fusion of Radar Observations and Foundation Model Priors

arXiv:2603.21768v3 Announce Type: replace-cross Abstract: Precipitation nowcasting is critical for disaster mitigation and aviation safety. However, radar-only models frequently suffer from a lack of

Food4All: A Multi-Agent Framework for Real-time Free Food Discovery with Integrated Nutritional Metadata

arXiv:2510.18289v2 Announce Type: replace Abstract: Food insecurity remains a persistent public health emergency in the United States, tightly interwoven with chronic disease, mental illness, and opio

agentsarxiv-cs-cl

Forecasting Commencing Enrolments Under Data Sparsity: A Zero-Shot Time Series Foundation Models Framework for Higher Education Planning

arXiv:2602.12120v3 Announce Type: replace Abstract: Effective resource allocation in higher education depends on reliable enrolment forecasts, yet institutional planners frequently face data series di

From Pixels to Explanations: Interpretable Diabetic Retinopathy Grading with CNN-Transformer Ensembles, Visual Explainability and Vision-Language Models

arXiv:2604.23079v1 Announce Type: cross Abstract: The quality of diabetic retinopathy (DR) screening relies on the ability to correctly grade severity; however, many deep-learning (DL) classifiers can

Generalizable CT-Free PET Attenuation and Scatter Correction for Pediatric Patients

arXiv:2604.22894v1 Announce Type: cross Abstract: Computed tomography (CT)-based attenuation and scatter correction improves quantitative PET but adds radiation exposure that is particularly undesirab

researcharxiv-cs-cv

Graph-augmented Segmentation of Complex Shapes in Laser Powder bed Fusion for Enhanced In Situ Inspection

arXiv:2604.24234v1 Announce Type: new Abstract: The technological maturity of in situ inspection and monitoring methods in additive manufacturing is steadily increasing, enabling more efficient and pr

Green Shielding: A User-Centric Approach Towards Trustworthy AI

arXiv:2604.24700v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed, yet their outputs can be highly sensitive to routine, non-adversarial variation in how users p

Grounding Before Generalizing: How AI Differs from Humans in Causal Transfer

arXiv:2604.24062v1 Announce Type: new Abstract: Extracting abstract causal structures and applying them to novel situations is a hallmark of human intelligence. While Large Language Models (LLMs) and

researcharxiv-cs-ai

Tutorials

'If You're Very Clever, No One Knows You've Used It': The Social Dynamics of Developing Generative AI Literacy in the Workplace

arXiv:2602.01386v2 Announce Type: replace-cross Abstract: Generative AI (GenAI) tools are rapidly transforming knowledge work, making AI literacy a critical priority for organizations. However, resear

tutorialsarxiv-cs-ai

Information-Theoretic Measures in AI: A Practical Decision Guide

arXiv:2604.23716v1 Announce Type: new Abstract: Information-theoretic (IT) measures are ubiquitous in artificial intelligence: entropy drives decision-tree splits and uncertainty quantification, cross

agentsarxiv-cs-ai

Instance Awareness of Multi-class Semantic Segmentation Loss Functions

arXiv:2604.24276v1 Announce Type: new Abstract: Instance-sensitive losses for semantic segmentation such as blob loss and CC loss were designed to address instance imbalance, ensuring small lesions ge

researcharxiv-cs-cv

Interoceptive machine framework: Toward interoception-inspired regulatory architectures in artificial intelligence

arXiv:2604.24527v1 Announce Type: new Abstract: This review proposes an integrative framework grounded on interoception and embodied AI-termed the interoceptive machine framework-that translates biolo

researcharxiv-cs-ai

Intervention-Aware Multiscale Representation Learning from Imaging Phenomics and Perturbation Transcriptomics

arXiv:2604.22832v1 Announce Type: cross Abstract: Microscopy-based phenotypic profiling is scalable for drug discovery but lacks the mechanistic depth of transcriptomics, which remains costly and scar

Isotonic Layer: A Unified Framework for Recommendation Calibration and Debiasing

arXiv:2603.06589v2 Announce Type: replace-cross Abstract: Model calibration and debiasing are fundamental yet operationally expensive challenges in large-scale recommendation systems. Existing approac

K-MetBench: A Multi-Dimensional Benchmark for Fine-Grained Evaluation of Expert Reasoning, Locality, and Multimodality in Meteorology

arXiv:2604.24645v1 Announce Type: cross Abstract: The development of practical (multimodal) large language model assistants for Korean weather forecasters is hindered by the absence of a multidimensio

Learning Evidence of Depression Symptoms via Prompt Induction

arXiv:2604.24376v1 Announce Type: new Abstract: Depression places substantial pressure on mental health services, and many people describe their experiences outside clinical settings in high-volume us

researcharxiv-cs-cl

Applications

Learning to Rotate: Temporal and Semantic Rotary Encoding for Sequential Modeling

arXiv:2604.24717v1 Announce Type: new Abstract: Every Transformer architecture dedicates enormous capacity to learning rich representations in semantic embedding space -- yet the rotation manifold act

applicationsarxiv-cs-ai

Less Is More: Engineering Challenges of On-Device Small Language Model Integration in a Mobile Application

arXiv:2604.24636v1 Announce Type: cross Abstract: On-device Small Language Models (SLMs) promise fully offline, private AI experiences for mobile users (no cloud dependency, no data leaving the device

Live Knowledge Tracing: Real-Time Adaptation using Tabular Foundation Models

arXiv:2602.06542v3 Announce Type: replace Abstract: Deep knowledge tracing models have achieved significant breakthroughs in modeling student learning trajectories. However, these architectures requir

researcharxiv-cs-lg

LoFi: Location-Aware Fine-Grained Representation Learning for Chest X-ray

arXiv:2603.19451v2 Announce Type: replace-cross Abstract: Fine-grained representation learning is crucial for retrieval and phrase grounding in chest X-rays, where clinically relevant findings are oft

researcharxiv-cs-ai