Justin Ho — accepted AI-conference papers

2025

DETQUS: Decomposition-Enhanced Transformers for QUery-focused Summarization

Yasir Khan, Xinlei Wu, Sangpil Youm, Justin Ho, Aryaan Mehboob Shaikh, Jairo Garciga +2

NAACL 2025long

Query-focused tabular summarization is an emerging task in table-to-text generation that synthesizes a summary response from tabular data based on user queries. Traditional transformer-based approaches face challenges due to token limitations and the complexity of reasoning over large tables. To add…

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2025

FIDELITY: Fine-grained Interpretable Distillation for Effective Language Insights and Topic Yielding

Divyansh Singh, Brodie Mather, Demi Zhang, Patrick Lehman, Justin Ho, Bonnie J Dorr

NAACL 2025findings

The rapid expansion of text data has increased the need for effective methods to distill meaningful information from large datasets. Traditional and state-of-the-art approaches have made significant strides in topic modeling, yet they fall short in generating contextually specific and semantically i…

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