Papers by Fangzhi Zhu

2 papers
A Semantic Mention Graph Augmented Model for Document-Level Event Argument Extraction (2024.lrec-main)

Copied to clipboard

Challenge: Document-level Event Argument Extraction (DEAE) aims to identify arguments and their specific roles from unstructured document.
Approach: They propose a document-prompt-based method for document-level event argument extraction that uses a semantic mention graph to capture relations between documents and prompts.
Outcome: The proposed method surpasses baseline methods and achieves state-of-the-art performance on RAMS and WikiEvents datasets.
MPPO: Multi Pair-wise Preference Optimization for LLMs with Arbitrary Negative Samples (2025.coling-main)

Copied to clipboard

Challenge: Existing preference optimization methods such as DPO and KTO are inherently derived from PPO, requiring a reference model that adds GPU memory resources and relies heavily on abundant preference data.
Approach: They propose an algorithm that leverages the average likelihood of model responses to fit the reward function and maximizes the utilization of preference data.
Outcome: The proposed algorithm outperforms DPO, ORPO, and SimPO on MT-Bench and Arena-Hard.

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