Kung-Hsiang (Steeve) Huang

Research Scientist
Salesforce AI Research

Palo Alto, California

khhuang3@illinois.edu

About Me

I'm a research scientist at Salesforce AI Research working on agentic AI (NAACL 2025), trustworthy AI (NAACL 2025 Findings) and multimodality (Arxiv 2025).

Prior to joining Salesforce AI Research, I earned my PhD at the University of Illinois Urbana-Champaign, under the guidance of my amazing advisor Prof. Heng Ji. I was 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, ACL 2024 Findings). 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.

Selected Publications
* Equal Contribution

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

2025

Why Vision Language Models Struggle with Visual Arithmetic? Towards Enhanced Chart and Geometry Understanding
Kung-Hsiang Huang, Can Qin, Haoyi Qiu, Philippe Laban, Shafiq Joty, Caiming Xiong, Chien-Sheng Wu
Arxiv
PDF Bibtex Code Dataset

@misc{huang-etal-2025-cogalign,
title = "Why Vision Language Models Struggle with Visual Arithmetic? Towards Enhanced Chart and Geometry Understanding",
author = "Huang, Kung-Hsiang  and
  Qin, Can  and
  Qiu, Haoyi  and
  Laban, Philippe  and
  Joty, Shafiq  and
  Xiong, Caiming  and
  Wu, Chien-Sheng",
year = "2025",
eprint={2502.11492},
archivePrefix = "arXiv",
primaryClass={cs.AI}
}

CRMArena: A Benchmark for Testing the Knowledge of Large Language Models in Customer Relationship Management
Kung-Hsiang Huang, Akshara Prabhakar, Sidharth Dhawan, Yixin Mao, Huan Wang, Silvio Savarese, Caiming Xiong, Philippe Laban, Chien-Sheng Wu
NAACL 2025.
PDF Bibtex Code Dataset Leaderboard

@inproceedings{huang-etal-2025-crmarena,
    title = "CRMArena: Understanding the Capacity of LLM Agents to Perform Professional CRM Tasks in Realistic Environments",
    author = "Huang, Kung-Hsiang  and
      Prabhakar, Akshara  and
      Dhawan, Sidharth  and
      Mao, Yixin  and
      Wang, Huan  and
      Savarese, Silvio  and
      Xiong, Caiming  and
      Laban, Philippe  and
      Wu, Chien-Sheng",
    booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
    year = "2025",
}

Evaluating Cultural and Social Awareness of LLM Web Agents
Haoyi Qiu, Alexander R. Fabbri*, Divyansh Agarwal*, Kung-Hsiang Huang*, Sarah Tan, Nanyun Peng, Chien-Sheng Wu
NAACL 2025 Findings.
PDF Bibtex

@inproceedings{qiu2024evaluating,
      title = "Evaluating Cultural and Social Awareness of LLM Web Agents", 
      author = "Qiu, Haoyi and Fabbri, Alexander R. and Agarwal, Divyansh and Huang, Kung-Hsiang and Tan, Sarah and Peng, Nanyun and Wu, Chien-Sheng",
      booktitle = "Findings of the Association for Computational Linguistics: NAACL 2025",
      year = "2025",
}

2024

SafeWorld: Geo-Diverse Safety Alignment
Da Yin*, Haoyi Qiu*, Kung-Hsiang Huang, Kai-Wei Chang, Nanyun Peng
NeurIPS 2024.
Bibtex

@inproceedings{da-etal-2024-safe,
    title = "SafeWorld: Geo-Diverse Safety Alignment",
    author = "Da Yin, Haoyi Qiu, Kung-Hsiang Huang, Kai-Wei Chang, Nanyun Peng",
    booktitle = "Thirty-eighth Conference on Neural Information Processing Systems",
    year="2024",
}

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.
IEEE Transactions on Knowledge and Data Engineering (TKDE).
PDF Bibtex Reading List

@article{huang-etal-2024-chart,
    title = "From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Models",
    author = "Huang, Kung-Hsiang and Chan, Hou Pong and Fung, Yi R. and Qiu, Haoyi and Zhou, Mingyang and Joty, Shafiq and Chang, Shih-Fu and Ji, Heng",
    year={2024},
    journal={IEEE Transactions on Knowledge and Data Engineering (TKDE)},
}

ManiTweet: A New Benchmark for Identifying Manipulation of News on Social Media
Kung-Hsiang Huang, Hou Pong Chan, Kathleen McKeown, Heng Ji.
COLING 2025.
PDF Bibtex

@inproceedings{huang-etal-2025-manitweet,
    title = "{M}ani{T}weet: A New Benchmark for Identifying Manipulation of News on Social Media",
    author = "Huang, Kung-Hsiang and Chan, Hou Pong and McKeown, Kathleen and Ji, Heng",
    booktitle = "Proceedings of the 31st International Conference on Computational Linguistics",
    year = "2025",
    publisher = "International Committee on Computational Linguistics",
}

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

@inproceedings{huang-etal-2023-do,
    title = "Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning",
    author = "Huang, Kung-Hsiang  and
      Zhou, Mingyang and
      Chan, Hou Pong  and
      Fung, Yi R. and
      Wang, Zhenhailong and
      Zhang, Lingyu and
      Chang, Shih-Fu and
      Ji, Heng",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2024",
    month = aug,
    year="2024",
    publisher = "Association for Computational Linguistics",
}

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

@inproceedings{huang-etal-2024-embrace,
    title = "Embrace Divergence for Richer Insights: A Multi-document Summarization Benchmark and a Case Study on Summarizing Diverse Information from News Articles.",
    author = "Kung-Hsiang Huang and Philippe Laban and Alexander R. Fabbri and Prafulla Kumar Choubey and Shafiq Joty and Caiming Xiong and Chien-Sheng Wu",
    booktitle = "Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
    year = "2024",
    publisher = "Association for Computational Linguistics",
}

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

@inproceedings{qiu-etal-2024-amrfact,
    title = "AMRFact: Enhancing Summarization Factuality Evaluation with AMR-Driven Negative Samples Generation",
    author = "Haoyi Qiu and Kung-Hsiang Huang and Jingnong Qu and Nanyun Peng",
    booktitle = "Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
    year = "2024",
    publisher = "Association for Computational Linguistics",
}

2023

Zero-shot Faithful Factual Error Correction.
Kung-Hsiang Huang, Hou Pong Chan, Heng Ji.
ACL 2023.
PDF Bibtex Code

@inproceedings{huang-etal-2023-zero,
    title = "Zero-shot Faithful Factual Error Correction",
    author = "Huang, Kung-Hsiang  and
      Chan, Hou Pong  and
      Ji, Heng",
    editor = "Rogers, Anna  and
      Boyd-Graber, Jordan  and
      Okazaki, Naoaki",
    booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.acl-long.311",
    doi = "10.18653/v1/2023.acl-long.311",
    pages = "5660--5676",
}
}

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

@inproceedings{huang-etal-2023-faking,
    title = "Faking Fake News for Real Fake News Detection: Propaganda-Loaded Training Data Generation",
    author = "Huang, Kung-Hsiang  and
      McKeown, Kathleen  and
      Nakov, Preslav  and
      Choi, Yejin  and
      Ji, Heng",
    editor = "Rogers, Anna  and
      Boyd-Graber, Jordan  and
      Okazaki, Naoaki",
    booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.acl-long.815",
    doi = "10.18653/v1/2023.acl-long.815",
    pages = "14571--14589",
    
}

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

                      @inproceedings{huang-etal-2023-swing,
                        title = "{SWING}: Balancing Coverage and Faithfulness for Dialogue Summarization",
                        author = "Huang, Kung-Hsiang  and
                          Singh, Siffi  and
                          Ma, Xiaofei  and
                          Xiao, Wei  and
                          Nan, Feng  and
                          Dingwall, Nicholas  and
                          Wang, William Yang  and
                          McKeown, Kathleen",
                        editor = "Vlachos, Andreas  and
                          Augenstein, Isabelle",
                        booktitle = "Findings of the Association for Computational Linguistics: EACL 2023",
                        month = may,
                        year = "2023",
                        address = "Dubrovnik, Croatia",
                        publisher = "Association for Computational Linguistics",
                        url = "https://aclanthology.org/2023.findings-eacl.37",
                        doi = "10.18653/v1/2023.findings-eacl.37",
                        pages = "512--525",
                    }

2022

Cross-document Misinformation Detection based on Event Graph Reasoning.
Xueqing Wu, Kung-Hsiang Huang, Yi Fung, Heng Ji
NAACL 2022.
PDF Bibtex Code

                      @inproceedings{wu-etal-2022-cross,
                          title = "Cross-document Misinformation Detection based on Event Graph Reasoning",
                          author = "Wu, Xueqing  and
                            Huang, Kung-Hsiang  and
                            Fung, Yi  and
                            Ji, Heng",
                          editor = "Carpuat, Marine  and
                            de Marneffe, Marie-Catherine  and
                            Meza Ruiz, Ivan Vladimir",
                          booktitle = "Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
                          month = jul,
                          year = "2022",
                          address = "Seattle, United States",
                          publisher = "Association for Computational Linguistics",
                          url = "https://aclanthology.org/2022.naacl-main.40",
                          doi = "10.18653/v1/2022.naacl-main.40",
                          pages = "543--558",
                      }

CONCRETE: Improving Cross-lingual Fact-checking with Cross-lingual Retrieval.
Kung-Hsiang Huang, ChengXiang Zhai, Heng Ji.
COLING 2022.
PDF Bibtex Code

                        @inproceedings{huang-etal-2022-concrete,
                          title = "{CONCRETE}: Improving Cross-lingual Fact-checking with Cross-lingual Retrieval",
                          author = "Huang, Kung-Hsiang  and
                            Zhai, ChengXiang  and
                            Ji, Heng",
                          booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
                          month = oct,
                          year = "2022",
                          address = "Gyeongju, Republic of Korea",
                          publisher = "International Committee on Computational Linguistics",
                          url = "https://aclanthology.org/2022.coling-1.86",
                          pages = "1024--1035",
                      }

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

                        @inproceedings{10.1145/3534678.3542615,
                          author = {Fung, Yi R. and Huang, Kung-Hsiang and Nakov, Preslav and Ji, Heng},
                          title = {The Battlefront of Combating Misinformation and Coping with Media Bias},
                          year = {2022},
                          isbn = {9781450393850},
                          publisher = {Association for Computing Machinery},
                          address = {New York, NY, USA},
                          url = {https://doi.org/10.1145/3534678.3542615},
                          doi = {10.1145/3534678.3542615},
                          booktitle = {Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
                          pages = {4790–4791},
                          numpages = {2},
                          keywords = {computation for the social good, correcting bias and misinformation, fake news detection, misinformation characterization},
                          location = {Washington DC, USA},
                          series = {KDD '22}
                          }

2021

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

                        @inproceedings{huang-etal-2021-document,
                        title = "Document-level Entity-based Extraction as Template Generation",
                        author = "Huang, Kung-Hsiang  and
                          Tang, Sam  and
                          Peng, Nanyun",
                        editor = "Moens, Marie-Francine  and
                          Huang, Xuanjing  and
                          Specia, Lucia  and
                          Yih, Scott Wen-tau",
                        booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
                        month = nov,
                        year = "2021",
                        address = "Online and Punta Cana, Dominican Republic",
                        publisher = "Association for Computational Linguistics",
                        url = "https://aclanthology.org/2021.emnlp-main.426",
                        doi = "10.18653/v1/2021.emnlp-main.426",
                        pages = "5257--5269",
                    }

2020

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

                      @inproceedings{huang-etal-2020-biomedical,
                        title = "Biomedical Event Extraction with Hierarchical Knowledge Graphs",
                        author = "Huang, Kung-Hsiang  and
                          Yang, Mu  and
                          Peng, Nanyun",
                        editor = "Cohn, Trevor  and
                          He, Yulan  and
                          Liu, Yang",
                        booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
                        month = nov,
                        year = "2020",
                        address = "Online",
                        publisher = "Association for Computational Linguistics",
                        url = "https://aclanthology.org/2020.findings-emnlp.114",
                        doi = "10.18653/v1/2020.findings-emnlp.114",
                        pages = "1277--1285",
                        abstract = "Biomedical event extraction is critical in understanding biomolecular interactions described in scientific corpus. One of the main challenges is to identify nested structured events that are associated with non-indicative trigger words. We propose to incorporate domain knowledge from Unified Medical Language System (UMLS) to a pre-trained language model via Graph Edge-conditioned Attention Networks (GEANet) and hierarchical graph representation. To better recognize the trigger words, each sentence is first grounded to a sentence graph based on a jointly modeled hierarchical knowledge graph from UMLS. The grounded graphs are then propagated by GEANet, a novel graph neural networks for enhanced capabilities in inferring complex events. On BioNLP 2011 GENIA Event Extraction task, our approach achieved 1.41{\%} F1 and 3.19{\%} F1 improvements on all events and complex events, respectively. Ablation studies confirm the importance of GEANet and hierarchical KG.",
                    }

Service

ACL Rolling Review Area Chair

Reviewer

	2023	2022	2021
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