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...
![[2511.17844] Less is More: Data-Efficient Adaptation for Controllable Text-to-Video Generation](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
This article presents a novel data-efficient approach for fine-tuning text-to-video generation models, demonstrating that low-quality syn...
The paper presents VCFlow, a novel architecture for subject-agnostic brain visual decoding, enhancing the reconstruction of visual experi...
This survey explores the concept of data agents, autonomous systems that manage complex data tasks. It introduces a hierarchical taxonomy...
This study presents a methodology for mapping and predicting chlorophyll-a levels in the Mar Menor Lagoon using C2RCC-processed Sentinel ...
The paper presents RHYTHM, a framework utilizing hierarchical temporal tokenization to enhance human mobility predictions by leveraging l...
This paper presents a novel approach to infrared small target detection and segmentation (IRSTDS) by introducing a noise-suppression feat...
This article discusses a novel approach to predicting molecular geometries using machine learning interatomic potentials, improving molec...
This article presents a novel framework, ChannelTokenFormer, for robust multivariate time series forecasting, addressing challenges of de...
This article examines how linguistic and contextual factors influence the accuracy of AI-generated health advice, revealing significant d...
The paper presents CONTINA, a method for predicting traffic demand with confidence intervals that adapt to changing conditions, ensuring ...
The paper presents ContRec, a novel framework that integrates continuous tokens into LLM-based recommender systems, enhancing user prefer...
This systematic review analyzes a decade of progress in Natural Language Processing (NLP) for the Yorùbá language, highlighting challenge...
The paper introduces Geodesic Integrated Gradients (GIG), a new method for attributing importance scores in deep networks, addressing fla...
This article presents a statistical learning perspective on semi-dual adversarial neural optimal transport solvers, addressing theoretica...
This paper presents a two-stage method for predicting subway passenger flows during incidents, addressing challenges in data scarcity and...
This paper proposes a new definition of disentanglement in representation learning that accounts for dependent factors of variation, offe...
This paper addresses the challenge of partitioning input variables in attribution methods for Explainable AI, proposing new metrics to re...
The paper introduces BioX-Bridge, a framework for unsupervised cross-modal knowledge transfer in biosignals, enhancing model efficiency w...
The paper introduces DS-STAR, a data science agent designed to automate complex workflows by integrating diverse data formats and generat...
The paper presents TASER, a system designed for schema-guided extraction and recommendation from complex financial tables, improving data...
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