Papers by Juseon-Do Juseon-Do

2 papers
InstructCMP: Length Control in Sentence Compression through Instruction-based Large Language Models (2024.findings-acl)

Copied to clipboard

Challenge: Existing sentences do not consider the length constraints in extractive summarization because of their limited model abilities.
Approach: They propose an approach that incorporates length constraints without model modifications into sentences . they use traditional sentence compression datasets to transform them into instruction format .
Outcome: The proposed method can consider the length constraint through instructions without model modifications.
Considering Length Diversity in Retrieval-Augmented Summarization (2025.findings-naacl)

Copied to clipboard

Challenge: Existing methods that require exhaustive exemplar-exemplar relevance comparisons do not consider summary lengths.
Approach: They propose a Diverse Length-aware Maximal Marginal Relevance algorithm to better control summary lengths.
Outcome: The proposed algorithm reduces the computational cost and memory consumption while maintaining the same level of informativeness.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations