4 papers
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…
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…
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…
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…