NLPTasks-through-code.md

Paper Collection for Utilizing CodeLMs for Traditional NLP Tasks

Information Extraction

1. [Preprint] Retrieval-Augmented Code Generation for Universal Information Extraction. , 2023.11

   Yucan Guo, Zixuan Li, Xiaolong Jin, Yantao Liu, Yutao Zeng, Wenxuan Liu, Xiang Li, Pan Yang, Long Bai, Jiafeng Guo, Xueqi Cheng

2. [ICLR2024] GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction. , 2023.10

   Oscar Sainz, Iker García-Ferrero, Rodrigo Agerri, Oier Lopez de Lacalle, German Rigau, Eneko Agirre

3. [ACL2023] Code4Struct: Code Generation for Few-Shot Event Structure Prediction. 2023.07

   Xingyao Wang, Sha Li, Heng Ji

4. [ACL2023] CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors. , 2023.05

   Peng Li, Tianxiang Sun, Qiong Tang, Hang Yan, Yuanbin Wu, Xuanjing Huang, Xipeng Qiu

5. [Preprint] CodeKGC: Code Language Model for Generative Knowledge Graph Construction. , 2023.04

   Zhen Bi, Jing Chen, Yinuo Jiang, Feiyu Xiong, Wei Guo, Huajun Chen, Ningyu Zhang

Commonsense Reasoning

1. [EMNLP2022] Language Models of Code are Few-Shot Commonsense Learners. , 2022.10

   Aman Madaan, Shuyan Zhou, Uri Alon, Yiming Yang, Graham Neubig

Graph Reasoning and Generation

1. [Preprint] InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignment. , 2023.04

   Jianing Wang, Junda Wu, Yupeng Hou, Yao Liu, Ming Gao, Julian J. McAuley