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20242026
most citedMetadata-based Data Exploration with Retrieval-Augmented Generation for Large Language Models

1 citations · 1 across the 5 of their papers we have counts for

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5 papers

cs.CV2026

NOVA: Sparse Control, Dense Synthesis for Pair-Free Video Editing

Tianlin Pan, Jiayi Dai, Chenpu Yuan +7

Recent video editing models have achieved impressive results, but most still require large-scale paired datasets. Collecting such naturally aligned pairs at scale remains highly ch…

cs.LG2026

Learn from A Rationalist: Distilling Intermediate Interpretable Rationales

Jiayi Dai, Randy Goebel

Because of the pervasive use of deep neural networks (DNNs), especially in high-stakes domains, the interpretability of DNNs has received increased attention. The general idea of r…

cs.AI2025

Reason2Decide: Rationale-Driven Multi-Task Learning

H M Quamran Hasan, Housam Khalifa Bashier, Jiayi Dai +2

Despite the wide adoption of Large Language Models (LLM)s, clinical decision support systems face a critical challenge: achieving high predictive accuracy while generating explanat…

cs.CL2025

Explainability of Large Language Models: Opportunities and Challenges toward Generating Trustworthy Explanations

Shahin Atakishiyev, Housam K. B. Babiker, Jiayi Dai +8

Large language models have exhibited impressive performance across a broad range of downstream tasks in natural language processing. However, how a language model predicts the next…

cs.IR2024★ 1 cited

Metadata-based Data Exploration with Retrieval-Augmented Generation for Large Language Models

Teruaki Hayashi, Hiroki Sakaji, Jiayi Dai +1

Developing the capacity to effectively search for requisite datasets is an urgent requirement to assist data users in identifying relevant datasets considering the very limited ava…