Papers by Kefei Duan

2 papers
MetaFill: Text Infilling for Meta-Path Generation on Heterogeneous Information Networks (2022.emnlp-main)

Copied to clipboard

Challenge: Existing meta-path generation methods cannot fully exploit rich textual information in HINs.
Approach: They propose a text-infilling-based approach to generate meta-paths from textual information in HINs.
Outcome: The proposed approach can classify edges in the zero-shot setting, where existing methods cannot generate meta-paths.
Re-Tuning: Overcoming the Compositionality Limits of Large Language Models with Recursive Tuning (2024.acl-long)

Copied to clipboard

Challenge: Existing methods to solve compositional tasks are limited by complexity and complexity.
Approach: They propose a method that tunes large language models to break down a problem into subproblems, solve those subproblem, and combine the results.
Outcome: The proposed method significantly improves model performance on three representative compositional tasks: integer addition, dynamic programming, and parity.

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