About

Hi! My name is Zhijiang Guo (郭志江). I am a Researcher at Huawei Noah’s Ark Lab and a Visiting Researcher at the University of Cambridge. Before that, I was a Postdoc at the Department of Computer Science and Technology at the University of Cambridge from 2020-2022, working with Prof. Andreas Vlachos. I am also a member of Trinity College.

I earned my PhD in Computer Science from SUTD in 2020, under the supervision of Prof. Wei Lu. I was a visiting student in ILCC at the University of Edinburgh from 2019-2020, working with Prof. Shay Cohen, Prof. Giorgio Satta, Prof. Frank Drewes and Prof. Johanna Björklund on Structured Prediction. I also learned a lot from Prof. Zhiyang Teng.

I am looking for research interns to work with me on large language models (see below), drop me an email if you are interested.

Email: cartusguo AT gmail.com

[Github] [Linkedin] [Google Scholoar] [Twitter]

Research

I am generally interested in natural language processing and machine learning. Current interests are in several aspects around large language models:

• Factuality: method, evaluation and multimodality
• Reasoning: math, logic and code
• Knowledge: retrieval, calibration and grounding
• LLMs as Agents: planning, memory and collaboration

News

• 2024.02: Glad to serve as Area Chair (AC) for ACL 2024
• 2023.10: Glad to serve as Area Chair (AC) for COLING 2024
• 2023.06: Glad to serve as Senior Program Committee (SPC) for AAAI 2024
• 2023.06: Glad to serve as Area Chair (AC) for EMNLP 2023
• 2022.06: Glad to serve as Senior Program Committee (SPC) for AAAI 2023
• 2022.06: Glad to serve as Area Chair (AC) for EMNLP 2022

Publications

^$ denotes equal contribution, ^# denotes corresponding author.

• Do Large Language Models Know about Facts?

  Xuming Hu, Junzhe Chen, Xiaochuan Li, Yufei Guo, Lijie Wen, Philip S Yu, Zhijiang Guo^#

  ICLR 2024 (Spotlight)

  [Paper]

• DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning

  Jing Xiong^$, Zixuan Li^$, Chuanyang Zheng, Zhijiang Guo^#, Yichun Yin, Enze Xie, Zhicheng Yang, Qingxing Cao, Haiming Wang, Xiongwei Han, Jing Tang, Chengming Li, Xiaodan Liang

  ICLR 2024

  [Paper] [Code]

• Towards Human-aligned Evaluation for Linear Programming Word Problems

  Linzi Xing, Xinglu Wang, Yuxi Feng, Zhenan Fan, Jing Xiong, Zhijiang Guo, Xiaojin Fu, Rindra Ramamonjison, Mahdi Mostajabdaveh, Xiongwei Han, Zirui Zhou and Yong Zhang

  COLING 2024

• AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web

  Michael Schlichtkrull^$, Zhijiang Guo^$ and Andreas Vlachos

  NeurIPS 2023

  [Paper] [Code] [Dataset]

• Multimodal Automated Fact-Checking: A Survey

  Mubashara Akhtar, Michael Schlichtkrull, Zhijiang Guo, Oana Cocarascu, Elena Simperl and Andreas Vlachos

  Findings of EMNLP 2023

  [Paper] [Code]

• TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language Models

  Jing Xiong, Jianhao Shen, Ye Yuan, Haiming Wang, Yichun Yin, Zhengying Liu, Lin Li, Zhijiang Guo, Qingxing Cao, Yinya Huang, Chuanyang Zheng, Xiaodan Liang, Ming Zhang, Qun Liu

  EMNLP 2023

  [Paper] [Dataset] [Code]

• Multimodal Relation Extraction with Cross-Modal Retrieval and Synthesis

  Xuming Hu, Zhijiang Guo^#, Zhiyang Teng, Irwin King and Philip S. Yu

  ACL 2023

  [Paper]

• $MR^2$: A Benchmark for Multimodal Retrieval-Augmented Rumor Detection in Social Media

  Xuming Hu, Zhijiang Guo^#, Junzhe Chen, Lijie Wen and Philip S. Yu

  SIGIR 2023

  [Paper] [Code] [Dataset]

• Read it Twice: Towards Faithfully Interpretable Fact Verification by Revisiting Evidence

  Xuming Hu, Zhaochen Hong, Zhijiang Guo, Lijie Wen and Philip S. Yu

  SIGIR 2023

  [Paper]

• A Survey on Automated Fact-Checking

  Zhijiang Guo^$, Michael Schlichtkrull^$, Andreas Vlachos

  TACL 2022

  [Paper] [Code] [Slides] [Poster] [Video]

• CHEF: A Pilot Chinese Dataset for Evidence-Based Fact-Checking

  Xuming Hu^$, Zhijiang Guo^$, Guanyu Wu, Aiwei Liu, Lijie Wen, Philip S. Yu

  NAACL 2022

  [Paper] [Code] [Dataset] [Slides]

• METS-CoV: A Dataset of Medical Entity and Targeted Sentiment on COVID-19 Related Tweets

  Peilin Zhou, Zeqiang Wang, Dading Chong, Zhijiang Guo, Yining Hua, Zichang Su, Zhiyang Teng, Jiageng Wu, Jie Yang

  NeurIPS 2022

  [Paper] [Code] [Dataset]

• Scene Graph Modification as Incremental Structure Expanding

  Xuming Hu^$, Zhijiang Guo^$, Yu Fu, Lijie Wen, Philip S. Yu

  COLING 2022

  [Paper] [Code] [Dataset]

• FEVEROUS: Fact Extraction and VERification Over Unstructured and Structured information

  Rami Aly, Zhijiang Guo, Michael Schlichtkrull, James Thorne, Andreas Vlachos, Christos Christodoulopoulos, Oana Cocarascu, Arpit Mittal

  NeurIPS 2021

  [Paper] [Code] [Website] [Dataset] [Talk]

• Uncovering Main Causalities for Long-tailed Information Extraction

  Guoshun Nan, Jiaqi Zeng, Rui Qiao, Zhijiang Guo, Wei Lu

  EMNLP 2021

  [Paper] [Code] [Talk]

• Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text Generation

  Yan Zhang^$, Zhijiang Guo^$, Zhiyang Teng, Wei Lu, Shay B. Cohen, Zuozhu Liu, Lidong Bing

  EMNLP 2020

  [Paper] [Code] [Talk] [Slides]

• Learning Latent Forests for Medical Relation Extraction

  Zhijiang Guo^$, Guoshun Nan^$, Wei Lu, Shay B. Cohen

  IJCAI 2020

  [Paper] [Code] [Talk] [Slides] [PPT] [Poster]

• Reasoning with Latent Structure Refinement for Document-Level Relation Extraction

  Guoshun Nan^$, Zhijiang Guo^$, Ivan Sekulic, Wei Lu

  ACL 2020

  [Paper] [Code] [Talk] [Slides]

• Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning

  Zhijiang Guo^$, Yan Zhang^$, Zhiyang Teng, Wei Lu

  TACL 2019

  [Paper] [Code] [Talk] [Slides]

• Attention Guided Graph Convolutional Networks for Relation Extraction

  Zhijiang Guo^$, Yan Zhang^$, Wei Lu

  ACL 2019

  [Paper] [Code] [Talk] [Slides]

• Better Transition-Based AMR Parsing with a Refined Search Space

  Zhijiang Guo, Wei Lu

  EMNLP 2018

  [Paper] [Code] [Poster]

Preprints

• ProxyQA: An Alternative Framework for Evaluating Long-Form Text Generation with Large Language Models

  Haochen Tan^$, Zhijiang Guo^$, Zhan Shi, Lu Xu, Zhili Liu, Xiaoguang Li, Yasheng Wang, Lifeng Shang, Qun Liu, Linqi Song

  Preprint

  [Paper] [Code]

• Learning From Correctness Without Prompting Makes LLM Efficient Reasoner

  Yuxuan Yao^$, Han Wu^$, Zhijiang Guo^#, Biyan Zhou, Jiahui Gao, Sichun Luo, Hanxu Hou, Xiaojin Fu, Linqi Song

  Preprint

  [Paper]

• Aligning with Human Judgement: The Role of Pairwise Preference in Large Language Model Evaluators

  Yinhong Liu^$, Han Zhou^$, Zhijiang Guo, Ehsan Shareghi, Ivan Vulić, Anna Korhonen, Nigel Collier

  [Paper] [Code]

  Preprint

• Are LLMs Rigorous Logical Reasoners? Empowering Natural Language Proof Generation with Contrastive Stepwise Decoding

  Ying Su, Xiaojin Fu, Mingwen Liu, Zhijiang Guo^#

  Preprint

  [Paper]

• Do We Need Language-Specific Fact-Checking Models? The Case of Chinese

  Caiqi Zhang, Zhijiang Guo, Andreas Vlachos

  Preprint

  [Paper] [Code]

• YODA: Teacher-Student Progressive Learning for Language Models

  Jianqiao Lu^$, Wanjun Zhong^$, Yufei Wang, Zhijiang Guo, Qi Zhu, Wenyong Huang, Yanlin Wang, Fei Mi, Baojun Wang, Yasheng Wang, Lifeng Shang, Xin Jiang, Qun Liu

  Preprint

  [Paper]

• HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning

  Chunlin Tian, Zhan Shi, Zhijiang Guo, Li Li, Cheng-zhong Xu

  Preprint

• Give Me More Details: Improving Real-World Fact-checking with Latent Retrieval

  Xuming Hu, Junzhe Chen, Zhijiang Guo^#, Philip S. Yu

  Preprint

  [Paper]

• GRATIS: Deep Learning Graph Representation with Task-specific Topology and Multi-dimensional Edge Features

  Siyang Song, Yuxin Song, Cheng Luo, Zhiyuan Song, Selim Kuzucu, Xi Jia, Zhijiang Guo, Weicheng Xie, Linlin Shen, Hatice Gunes

  Preprint

  [Paper] [Code]

Thesis

• Learning with Graphs in Natural Language Processing

  Zhijiang Guo

  PhD Thesis

  [Paper] [Slides]

Academic Services

• Area Chair: ACL 2024 (Interpretability and Analysis), COLING 2024 (Machine Learning), EMNLP 2023 (NLP Application), EMNLP 2022 (Semantics)
• Action Editor: ACL ARR
• Senior Program Committee: AAAI 2024, AAAI 2023, IJCAI 2022
• Program Committee: NeurIPS/ICLR/COLM/ACL/EMNLP/NAACL/EACL/COLING/AAAI/IJCAI
• Journal: Machine Learning/Computational Linguistics/TACL/TKDE/TALLIP/TASLP/TOIS

Workshops Organization

• EMNLP 2021 Workshop: The Fourth Fact Extraction and VERification (FEVER)
• ACL 2022 Workshop: The Fifth Fact Extraction and VERification (FEVER)
• EACL 2023 Workshop: The Sixth Fact Extraction and VERification (FEVER)
• EMNLP 2024 Workshop: The Seventh Fact Extraction and VERification (FEVER)

Research Mentoring

I am fortunate to be working with the following talented students and interns:

• Andrew Georgiou: Master at Cambridge, to Google Zurich
• Caiqi Zhang: Master at Cambridge, to PhD at Cambridge
• Henry Caushi: Undergrad at Cambridge, to Instructor at Warwick
• Haochen Tan: PhD at CityU, to Researcher at Huawei Noah’s Ark (HK)
• Jianqiao Lu: PhD at HKU
• Jing Xiong: Master at SYSU
• Ying Su: PhD at HKUST
• William Liu: PhD at Cambridge
• Yunlong Feng: PhD at HIT
• Yuxuan Yao: PhD at CityU

Education

• The University of Edinburgh, 2019-2020

  Computer Science, Advisor: Prof. Shay Cohen

• Singapore University of Technology and Design, 2016-2020

  Computer Science, Advisor: Prof. Wei Lu

• Sun Yat-sen University, 2010-2014