Runyu Wu — accepted AI-conference papers

2025

Boosting Multi-Domain Fine-Tuning of Large Language Models through Evolving Interactions between Samples

Xize Liang, Lin Yang, Jie Wang, Yiyang Lu, Runyu Wu, Hanzhu Chen +1

ICML 2025poster

The multi-domain fine-tuning of large language models (LLMs) confronts a notorious trade-off among abilities across domains. Existing studies attribute this trade-off to the conflicts between samples rooted in inherent semantics. Recent approaches attempt to mitigate these conflicts through the empi…

Cited by 0 Source ↗PDF ↗Scholar ↗

2024

Zero-shot Event Detection Using a Textual Entailment Model as an Enhanced Annotator

Ziqian Zeng, Runyu Wu, Yuxiang Xiao, Xiaoda Zhong, Hanlin Wang, Zhengdong Lu +1

COLING 2024main

Zero-shot event detection is a challenging task. Recent research work proposed to use a pre-trained textual entailment (TE) model on this task. However, those methods treated the TE model as a frozen annotator. We treat the TE model as an annotator that can be enhanced. We propose to use TE models t…

Cited by 1 Source ↗PDF ↗code ↗Scholar ↗