1 code implementation • 31 Mar 2024 • Yiqing Xie, Alex Xie, Divyanshu Sheth, PengFei Liu, Daniel Fried, Carolyn Rose
To demonstrate the complexity and solvability of examples in Exec-CSN, we present a human study demonstrating that 81. 3% of the examples can be solved by humans and 61% are rated as "requires effort to solve".
1 code implementation • 1 Mar 2024 • Zelalem Gero, Chandan Singh, Yiqing Xie, Sheng Zhang, Tristan Naumann, Jianfeng Gao, Hoifung Poon
Summarizing clinical text is crucial in health decision-support and clinical research.
1 code implementation • 16 Nov 2023 • Yiqing Xie, Sheng Zhang, Hao Cheng, PengFei Liu, Zelalem Gero, Cliff Wong, Tristan Naumann, Hoifung Poon, Carolyn Rose
Medical text generation aims to assist with administrative work and highlight salient information to support decision-making.
1 code implementation • 1 Nov 2023 • Yiqing Xie, Atharva Naik, Daniel Fried, Carolyn Rose
One major challenge of translating code between programming languages is that parallel training data is often limited.
1 code implementation • 21 May 2023 • Linyuan Gong, Chenyan Xiong, Xiaodong Liu, Payal Bajaj, Yiqing Xie, Alvin Cheung, Jianfeng Gao, Xia Song
This paper explores the effectiveness of model-generated signals in improving zero-shot generalization of text-to-text Transformers such as T5.
1 code implementation • 10 May 2023 • Yiqing Xie, Xiao Liu, Chenyan Xiong
Based on their commonalities, we train an unsupervised dense retriever, Anchor-DR, with a contrastive learning task that matches the anchor text and the linked document.
1 code implementation • 3 Nov 2022 • Yizhu Jiao, Sha Li, Yiqing Xie, Ming Zhong, Heng Ji, Jiawei Han
Specifically, we formulate the role prediction problem as an in-filling task and construct prompts for a pre-trained language model to generate candidate roles.
no code implementations • 15 Feb 2022 • Sha Li, Liyuan Liu, Yiqing Xie, Heng Ji, Jiawei Han
Our framework decomposes event detection into an identification task and a localization task.
1 code implementation • Findings (ACL) 2022 • Yiqing Xie, Jiaming Shen, Sha Li, Yuning Mao, Jiawei Han
Typical DocRE methods blindly take the full document as input, while a subset of the sentences in the document, noted as the evidence, are often sufficient for humans to predict the relation of an entity pair.
Ranked #5 on Relation Extraction on DocRED
1 code implementation • 13 Oct 2020 • Jiaxin Huang, Yiqing Xie, Yu Meng, Yunyi Zhang, Jiawei Han
Taxonomy is not only a fundamental form of knowledge representation, but also crucial to vast knowledge-rich applications, such as question answering and web search.
1 code implementation • EMNLP 2020 • Yuning Mao, Yanru Qu, Yiqing Xie, Xiang Ren, Jiawei Han
Additionally, the explicit redundancy measure in MMR helps the neural representation of the summary to better capture redundancy.
1 code implementation • 27 Jan 2020 • Jiaxin Huang, Yiqing Xie, Yu Meng, Jiaming Shen, Yunyi Zhang, Jiawei Han
Given a small set of seed entities (e. g., ``USA'', ``Russia''), corpus-based set expansion is to induce an extensive set of entities which share the same semantic class (Country in this example) from a given corpus.