About Me

I'm a research scientist at Salesforce AI Research, driven by a mission to make AI more trustworthy and reduce the spread of false information. To achieve this goal, I've worked towards several key research directions: fact-checking (COLING 2022), fake news detection (NAACL 2022, ACL 2023), faithfulness enhancement and evaluation (EACL 2023 Findings, NAACL 2024, NAACL 2024), and factual error correction (ACL 2023, Arxiv 2023).

I earned my PhD at the University of Illinois Urbana-Champaign, under the guidance of my amazing advisor Prof. Heng Ji. During my PhD study, I've received the Amazon Science Ph.D. Fellowship. Before joining UIUC, I obtained my master's degree from the University of Southern California and my bachelor's degree from the Hong Kong University of Science and Technology.

Recent News

  • May, 2024 I joined Salesforce AI Research as a research scientist.
  • May, 2024 I have one paper accpeted by ACL 2024 Findings.
  • Apr, 2024 I defended my PhD thesis.
  • Mar, 2024 I have two papers accepted by NAACL 2024.
  • Feb, 2024 I was invited to serve as an Area Chair for ACL Rolling Review.
  • Sep, 2023 I was selected as an inaugural Amazon PhD Fellow at the Amazon-Illinois Center.

Selected Publications
* Equal Contribution

Please refer to my Google Scholar page for a complete list of publications.


From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Models
Kung-Hsiang Huang, Hou Pong Chan, Yi R Fung, Haoyi Qiu, Mingyang Zhou, Shafiq Joty, Shih-Fu Chang, Heng Ji.
PDF Bibtex Reading List
Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning.
Kung-Hsiang Huang, Mingyang Zhou, Hou Pong Chan, Yi R Fung, Zhenhailong Wang, Lingyu Zhang, Shih-Fu Chang, Heng Ji.
ACL 2024 Findings.
PDF Bibtex Project Code Dataset & Checkpoints
Embrace Divergence for Richer Insights: A Multi-document Summarization Benchmark and a Case Study on Summarizing Diverse Information from News Articles.
Kung-Hsiang Huang, Philippe Laban, Alexander R. Fabbri, Prafulla Kumar Choubey, Shafiq Joty, Caiming Xiong, Chien-Sheng Wu.
NAACL 2024.
PDF Bibtex Dataset
AMRFact: Enhancing Summarization Factuality Evaluation with AMR-Driven Negative Samples Generation.
Haoyi Qiu, Kung-Hsiang Huang*, Jingnong Qu*, Nanyun Peng.
NAACL 2024. 
PDF Bibtex Code


Zero-shot Faithful Factual Error Correction.
Kung-Hsiang Huang, Hou Pong Chan, Heng Ji.
ACL 2023.
PDF Bibtex Code
Faking Fake News for Real Fake News Detection: Propaganda-Loaded Training Data Generation
Kung-Hsiang Huang, Kathleen McKeown, Preslav Nakov, Yejin Choi, Heng Ji.
ACL 2023.
PDF Bibtex Code
SWING: Balancing Coverage and Faithfulness for Dialogue Summarization.
Kung-Hsiang Huang, Siffi Singh, Xiaofei Ma, Wei Xiao, Feng Nan, Nicholas Dingwall, William Yang Wang, Kathleen McKeown.
EACL 2023 Findings.
PDF Bibtex Code


Cross-document Misinformation Detection based on Event Graph Reasoning.
Xueqing Wu, Kung-Hsiang Huang, Yi Fung, Heng Ji
NAACL 2022.
PDF Bibtex Code
CONCRETE: Improving Cross-lingual Fact-checking with Cross-lingual Retrieval.
Kung-Hsiang Huang, ChengXiang Zhai, Heng Ji.
COLING 2022.
PDF Bibtex Code
The Battlefront of Combating Misinformation and Coping with Media Bias.
Yi R Fung, Kung-Hsiang Huang, Preslav Nakov, Heng Ji
KDD 2022 Tutorial.
PDF Bibtex


Document-level Entity-based Extraction as Template Generation.
Kung-Hsiang Huang, Sam Tang, Nanyun Peng.
EMNLP 2021.  
PDF Bibtex Code


Biomedical Event Extraction with Hierarchical Knowledge Graphs.
Kung-Hsiang Huang, Mu Yang, Nanyun Peng.
EMNLP 2020 Findings.
PDF Bibtex Code


     ACL Rolling Review Area Chair
2023 2022 2021