Data analysis, statistics, and data engineering
UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...
Hi all, I’m curious about the current review dynamics for ICML 2026, especially after the rebuttal phase. For those who are reviewers (or...
MIT Professor Rafael Gómez-Bombarelli discusses the transformative potential of AI in scientific research, emphasizing its role in materi...
![[2508.09639] UbiQTree: Uncertainty Quantification in XAI with Tree Ensembles](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
The paper presents UbiQTree, a method for decomposing uncertainty in SHAP values used in explainable AI, focusing on aleatoric and episte...
This paper analyzes the emergence of massive activations during transformer training, revealing predictable patterns and offering a frame...
ICE-ID is a comprehensive historical census dataset featuring over 984,000 records from 16 census waves in Iceland, aimed at improving lo...
This paper explores the concept of Test-Time Training (TTT) with KV binding, revealing that it functions as learned linear attention rath...
PVminer is a novel NLP framework designed to detect the patient voice in patient-generated data, improving the analysis of patient-provid...
The paper presents SparkMe, a multi-agent LLM system designed for adaptive semi-structured interviewing, enhancing qualitative data colle...
The paper presents a novel kernelized self-attention mechanism designed to enhance next-item recommendations by improving the representat...
This paper presents a novel approach to brain lesion segmentation in MRI scans using report-supervised learning, enhancing accuracy by in...
This paper explores the relationship between the law of robustness and robust generalization in machine learning, providing a framework t...
This paper presents ArtiAgent, a novel approach to automate the creation of artifact-annotated datasets for training visual language mode...
This article explores efficient reasoning in Large Language Models (LLMs), focusing on optimizing computational resources through reward ...
The paper presents E-MMKGR, a unified framework for multimodal knowledge graphs tailored for e-commerce, enhancing recommendation systems...
Airavat introduces an innovative framework for automating Internet measurement workflows, ensuring both generation and verification again...
OrthoDiffusion is a novel diffusion-based model designed for multi-task interpretation of musculoskeletal MRI scans, improving diagnostic...
This article presents a deep learning-based system for detecting vocal errors in Kurdish maqams, addressing the limitations of existing a...
This paper presents an AI-driven methodology for segmenting straylight effects in space camera sensors, enhancing image analysis in resou...
The paper presents UrbanFM, a novel framework for scaling urban spatio-temporal foundation models, addressing challenges in generalizabil...
The paper presents Dataset Color Quantization (DCQ), a framework designed to compress large-scale image datasets by reducing color-space ...
This paper explores fair allocation of indivisible goods through limited cost-sensitive sharing, demonstrating how controlled sharing can...
The paper presents ACTOR-CURATOR, a novel framework for curriculum learning in reinforcement learning, enhancing post-training for large ...
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