Preprint

2024

MOOSE-Chem: Large Language Models for Rediscovering Unseen Chemistry Scientific Hypotheses
Zonglin Yang, Wanhao Liu, Ben Gao, Tong Xie, Yuqiang Li, Wanli Ouyang, Soujanya Poria, Erik Cambria, Dongzhan Zhou
[pdf] [code and benchmark]

Logical Reasoning over Natural Language as Knowledge Representation: A Survey
Zonglin Yang, Xinya Du, Rui Mao, Jinjie Ni, Erik Cambria
[pdf] [LRNL-bench] (to come) [ACL 2023 NLRSE workshop poster] (not archival)

Large Language Models for Automated Open-domain Scientific Hypotheses Discovery
Zonglin Yang, Xinya Du, Junxian Li, Jie Zheng, Soujanya Poria, Erik Cambria
in Proc. of ACL 2024 (Findings)
Best Poster Award in [AI4Science Workshop]
[pdf] [dataset and code]
Language Models as Inductive Reasoners
Zonglin Yang, Li Dong, Xinya Du, Hao Cheng, Erik Cambria, Xiaodong Liu, Jianfeng Gao, Furu Wei
in Proc. of EACL 2024
[pdf (preprint in 2022)] [dataset and code] [poster] [slides]

Task-Aware Self-Supervised Framework for Dialogue Discourse Parsing
Wei Li, Luyao Zhu, Wei Shao, Zonglin Yang, Erik Cambria
in Proc. of EMNLP 2023 (Findings)
[pdf] [code]
A Survey on Semantic Processing Techniques
Zonglin Yang*, Rui Mao*, Kai He*, Xulang Zhang*, Guanyi Chen*, Jinjie Ni*, Erik Cambria
in Information Fusion
[pdf]
Finding the Pillars of Strength for Multi-Head Attention
Jinjie Ni, Rui Mao, Zonglin Yang, Han Lei, Erik Cambria
in Proc. of ACL 2023
[pdf] [code]
End-to-end Case-Based Reasoning for Commonsense Knowledge Base Completion
Zonglin Yang, Xinya Du, Erik Cambria, Claire Cardie
in Proc. of EACL 2023 (oral)
[pdf] [code] [EACL 2023 slides] [ICCBR 2023 TMG/BEAR workshop slides] (not archival)

Improving Event Duration Prediction via Time-aware Pre-training
Zonglin Yang, Xinya Du, Alexander Rush, Claire Cardie
in Proc. of EMNLP 2020 (Findings)
[pdf] [collected data]