Wuhe Zou


A Token-pair Framework for Information Extraction from Dialog Transcripts in SereTOD Challenge
Chenyue Wang | Xiangxing Kong | Mengzuo Huang | Feng Li | Jian Xing | Weidong Zhang | Wuhe Zou
Proceedings of the Towards Semi-Supervised and Reinforced Task-Oriented Dialog Systems (SereTOD)

This paper describes our solution for Sere- TOD Challenge Track 1: Information extraction from dialog transcripts. We propose a token-pair framework to simultaneously identify entity and value mentions and link them into corresponding triples. As entity mentions are usually coreferent, we adopt a baseline model for coreference resolution. We exploit both annotated transcripts and unsupervised dialogs for training. With model ensemble and post-processing strategies, our system significantly outperforms the baseline solution and ranks first in triple f1 and third in entity f1.


LongSumm 2021: Session based automatic summarization model for scientific document
Senci Ying | Zheng Yan Zhao | Wuhe Zou
Proceedings of the Second Workshop on Scholarly Document Processing

Most summarization task focuses on generating relatively short summaries. Such a length constraint might not be appropriate when summarizing scientific work. The LongSumm task needs participants generate long summary for scientific document. This task usual can be solved by language model. But an important problem is that model like BERT is limit to memory, and can not deal with a long input like a document. Also generate a long output is hard. In this paper, we propose a session based automatic summarization model(SBAS) which using a session and ensemble mechanism to generate long summary. And our model achieves the best performance in the LongSumm task.