Xuan Wang

Xuan Wang

Assistant Professor

Publications and Patents

2025

  1. Xuan Wang, “AI for Science in the Era of Large Language Models”, in Proc. of the 39th Annual AAAI Conference on Artificial Intelligence (AAAI’25) (Conference Tutorial), pages TBD, February 25-26, 2025, Philadelphia, Pennsylvania

2024

  1. Tran N. Chau, Xuan Wang, John M. McDowell, and Song Li, “Advancing Plant Single-Cell Genomics with Foundation Models”, Current Opinion in Plant Biology, pages TBD (impact factor: 8.3).
  2. Hanwen Liu, Daniel Hajialigol, Benny Antony, Aiguo Han, and Xuan Wang, “EEG2Text: Open Vocabulary EEG-to-Text Translation with Multi-View Transformer”, in Proc. 2024 IEEE International Conference on Big Data (IEEE-BigData’24), pages TBD, December 15-18, 2024, Washington DC (acceptance rate: TBD%) (Previous version in ICML’24 AI4Science)
  3. Meng Lu, Ho Brandon, Ren Dennis, and Xuan Wang, “TriageAgent: Towards Better Multi-Agents Collaborations for Large Language Model-Based Clinical Triage”, in Proc. 2024 Conf. on Findings of Empirical Methods in Natural Language Processing (EMNLP’24), pages TBD, November 12-16, 2024, Miami, Florida (acceptance rate: TBD%) (Previous version in ICML’24 AI4Science, Spotlight, acceptance rate: 13%)
  4. Zhenyu Bi, Minghao Xu, Jian Tang, and Xuan Wang, “AI for Science in the Era of Large Language Models”, in Proc. 2024 Conf. on Empirical Methods in Natural Language Processing (EMNLP’24) (Conference Tutorial), pages TBD, November 12-16, 2024, Miami
  5. Sindhura Kommu, Yizhi Wang, Yue Wang, and Xuan Wang, “Gene Regulatory Network Inference from Pre-trained Single-Cell Transcriptomics Transformer with Joint Graph Learning”, The Forty-first International Conference on Machine Learning AI for Science Workshop (ICML’24 AI4Science), July 26 or 27, 2024, Vienna, Austria
  6. Sajib Acharjee Dip, Uddip Acharjee Shuvo, Tran Chau, Haoqiu Song, Petra Choi, Xuan Wang, and Liqing Zhang, “PathoLM: Identifying pathogenicity from the DNA sequence through the Genome Foundation Model”, The Forty-first International Conference on Machine Learning AI for Science Workshop (ICML’24 AI4Science), July 26 or 27, 2024, Vienna, Austria
  7. Brandon Ho, Meng Lu, Xuan Wang, and Dennis Ren, “Evaluation of AI Models in Predicting Pediatric Emergency Severity Index Levels”, Pediatric Emergency Care, pages TBD (impact factor: 1.6) (Previous version in 2024 AAP National Conference & Exhibition (Abstract Poster))
  8. Tanay Komarlu, Minhao Jiang, Xuan Wang, and Jiawei Han, “OntoType: Ontology-Guided and Pre-Trained Language Model Assisted Fine-Grained Entity Typing”, in Proc. 2024 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’24), pages TBD, August 25–29, 2024, Barcelona, Spain (acceptance rate: TBD%)
  9. Chufan Gao, Xuan Wang, and Jimeng Sun, “TTM-RE: Memory-Augmented Document-Level Relation Extraction”, in Proc. The 62nd Annual Meeting of the Association for Computational Linguistics (ACL’24), pages TBD, August 11–16, 2024, Bangkok, Thailand (acceptance rate: TBD%)
  10. Chufan Gao, Xulin Fan, Jimeng Sun, and Xuan Wang, “PromptRE: Weakly-Supervised Document-Level Relation Extraction via Prompting-Based Data Programming”, in Proc. The 62nd Annual Meeting of the Association for Computational Linguistics (ACL’24 KnowledgeLM), August 11–16, 2024, Bangkok, Thailand
  11. Yueyan Gu, Xuan Wang, and Farrokh Jazizadeh, “Are Transformers Effective for Time Series Anomaly Detection? – A Case Study in Building Energy Management”, in Proc. 2024 ASCE International Conference on Computing in Civil Engineering (i3CE’24), pages TBD, July 28-31, 2024, Pittsburgh, Pennsylvania

2023

  1. Daniel Hajialigol, Derek Kaknes, Tanner Barbour, Daphne Yao, Chris North, Jimeng Sun, David Liem, and Xuan Wang, “DRGCoder: Explainable Clinical Coding for the Early Prediction of Diagnostic-Related Groups”, in Proc. 2023 Conf. on Empirical Methods in Natural Language Processing (EMNLP’23) (System Demonstration), pages 373–380, December 6-10, 2023, Singapore
  2. Ming Zhong, Siru Ouyang, Yizhu Jiao, Priyanka Kargupta, Leo Luo, Yanzhen Shen, Bobby Zhou, Xianrui Zhong, Xuan Liu, Hongxiang Li, Jinfeng Xiao, Minhao Jiang, Vivian Hu, Xuan Wang, Heng Ji, Martin Burke, Huimin Zhao, and Jiawei Han, “Reaction Miner: An Integrated System for Chemical Reaction Extraction from Textual Data”, in Proc. 2023 Conf. on Empirical Methods in Natural Language Processing (EMNLP’23) (System Demonstration), pages 389–402, December 6-10, 2023, Singapore
  3. Priyanka Kargupta, Tanay Komarlu, Susik Yoon, Xuan Wang, and Jiawei Han, “MEGClass: Text Classification with Extremely Weak Supervision via Mutually-Enhancing Text Granularities”, in Proc. 2023 Conf. on Findings of Empirical Methods in Natural Language Processing (EMNLP’23), pages 10543–10558, December 6-10, 2023, Singapore (acceptance rate: 22.1%)
  4. Pengcheng Jiang, Shivam Agarwal, Bowen Jin, Xuan Wang, Jimeng Sun and Jiawei Han, “Text Augmented Open Knowledge Graph Completion via Pre-Trained Language Models”, in Proc. 2023 Findings of Annual Meeting of the Association for Computational Linguistics (ACL’23), pages 11161–11180, July 9-14, 2023, Toronto, Canada (acceptance rate: 18.4%)
  5. Ming Zhong, Siru Ouyang, Minhao Jiang, Vivian Hu, Yizhu Jiao, Xuan Wang and Jiawei Han “ReactIE: Enhancing Chemical Reaction Extraction with Weak Supervision”, in Proc. 2023 Findings of Annual Meeting of the Association for Computational Linguistics (ACL’23), pages 12120–12130, July 9-14, 2023, Toronto, Canada (acceptance rate: 19.1%)

Patents

  1. Gaetano Rosielo, Alfio Massimiliano Gliozo, Xuan Wang, “Transformer-Based Model Knowledge Graph Link Prediction”, No.US20220327356A1 (submitted, under IBM Research).

Before 2023

Xuan Wang. Scientific Knowledge Extraction from Massive Text Data . Thesis, 2022

Journal Papers

  1. Xuan Wang, Yu Zhang, Xiang Ren, Yuhao Zhang, Marinka Zitnik, Jingbo Shang, Curtis Langlotz and Jiawei Han, “Cross-type Biomedical Named Entity Recognition with Deep Multi-Task Learning”, Bioinformatics 35.10 (2018): 1745-1752. [code] (impact factor: 6.9)
  2. David Liem, Alexandre, Sanjana Murali, Dibakar Sigdel, Yu Shi, Xuan Wang, Jiaming Shen, Howard Choi et al. “Phrase Mining of Textual Data to Analyze Extracellular Matrix Protein Patterns Across Cardiovascular Disease”, American Journal of Physiology-Heart and Circulatory Physiology, 1;315(4):H910-H924, 2018 (impact factor: 4.8)

Conference Papers

  1. Xuan Wang, Vivian Hu, Minhao Jiang, Yu Zhang, Jinfeng Xiao, Danielle Loving, Heng Ji, Martin Burke, and Jiawei Han, ”ReactClass: Cross-Modal Supervision for Subword-Guided Reactant Entity Classification”, in Proc. of 2022 IEEE Int. Conf. on Bioinformatics and Biomedicine (IEEE-BIBM’22), pages 844-847, Las Vegas, NV, Dec. 2022 (acceptance rate: 20.0%)
  2. Yu Zhang, Yu Meng, Xuan Wang, Sheng Wang, Jiawei Han, “Seed-Guided Topic Discovery with Out-of-Vocabulary Seeds”, in Proc. of 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL’22), Seattle, WA, July 2022 (acceptance rate: 28.0%)
  3. Haoyu Wang, Xuan Wang, Yaqing Wang, Guangxu Xun, Kishlay Jha, and Jing Gao, “InterHG: an Interpretable and Accurate Model for Hypothesis Generation”, in Proc. of 2021 IEEE Int. Conf. on Bioinformatics and Biomedicine (BIBM’21), pages 1552-1557, Dec. 2021, online. (acceptance rate: 19.6%)
  4. Xuan Wang, Vivian Hu, Xiangchen Song, Shweta Garg, Jinfeng Xiao and Jiawei Han, “ChemNER: Fine-Grained Chemistry Named Entity Recognition with Ontology-guided Distant Supervision”, in Proc. 2021 Conf. on Empirical Methods in Natural Language Processing (EMNLP’21), pages 5227-5240, Nov. 2021 [code] (acceptance rate: 25.6%)
  5. Yu Meng, Yunyi Zhang, Jiaxin Huang, Xuan Wang, Yu Zhang, Heng Ji and Jiawei Han, “Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training”, in Proc. 2021 Conf. on Empirical Methods in Natural Language Processing (EMNLP’21), pages 10367-10378, Nov. 2021 (acceptance rate: 25.6%)
  6. Xuan Wang, Xiangchen Song, Bangzheng Li, Kang Zhou, Qi Li, and Jiawei Han, “Fine-Grained Named Entity Recognition with Distant Supervision in COVID-19 Literature”, in Proc. 2020 IEEE Int. Conf. on Bioinformatics and Biomedicine (BIBM’20), pages 491-494, Dec. 2020, online. (acceptance rate: 19.3%)
  7. Xuan Wang, Yingjun Guan, Yu Zhang, Qi Li, and Jiawei Han, “Pattern-enhanced Named Entity Recognition with Distant Supervision”, 2020 IEEE Int. Conf. on Big Data (BigData’20), pages 818-827, December 2020, online. (acceptance rate: 15.7%)
  8. Xuan Wang*, Yu Zhang*, Aabhas Chauhan, Qi Li, and Jiawei Han, “Textual Evidence Mining via Spherical Heterogeneous Information Network Embedding”, 2020 IEEE Int. Conf. on Big Data (BigData’20), pages 828-837, December 2020, online. (acceptance rate: 15.7%)
  9. Yu Zhang, Yu Meng, Jiaxin Huang, Frank F. Xu, Xuan Wang and Jiawei Han, “Minimally Supervised Categorization of Text with Metadata”, in Proc. 2020 ACM SIGIR Int. Conf. on Research and development in Information Retrieval (SIGIR’20), pages 1231-1240, Xi’an, China, July 2020 (acceptance rate: 26.5%)
  10. Xuan Wang*, Yu Zhang*, Qi Li, Xiang Ren, Jingbo Shang, and Jiawei Han, “Distantly Supervised Biomedical Named Entity Recognition with Dictionary Expansion”, in Proc. 2019 IEEE Int. Conf. on Bioinformatics and Biomedicine (BIBM’19), pages 496-503, San Diego, CA, Nov. 2019 [code] (acceptance rate: 18.8%)
  11. Yu Zhang, Frank F. Xu, Sha Li, Yu Meng, Xuan Wang, Qi Li, and Jiawei Han, “HiGitClass: Keyword-Driven Hierarchical Classification of GitHub Repositories”, in Proc. 2019 Int. Conf. on Data Mining (ICDM’19), pages 876-885, Beijing, November 2019 (acceptance rate: 18.1%)
  12. Xuan Wang*, Yu Zhang*, Qi Li, Cathy H. Wu and Jiawei Han, “PENNER: Pattern-enhanced Nested Named Entity Recognition in Biomedical Literature”, in Proc. 2018 Int. Conf. on Bioinformatics and Biomedicine (BIBM’18), pages 540-547, Madrid, Spain, Dec. 2018 (acceptance rate: 19.3%)
  13. Qi Li, Xuan Wang, Yu Zhang, Fei Ling, Cathy H. Wu and Jiawei Han, “Pattern Discovery for Wide-Window Open Information Extraction in Biomedical Literature”, in Proc. 2018 Int. Conf. on Bioinformatics and Biomedicine (BIBM’18), pages 420-427, Madrid, Spain, Dec. 2018 (acceptance rate: 19.3%)
  14. Xuan Wang, Yu Zhang, Qi Li, Yinyin Chen, and Jiawei Han. “Open Information Extraction with Meta-pattern Discovery in Biomedical Literature”, in Proc. of 2018 ACM Conf. on Bioinformatics, Computational Biology, and Health Informatics (BCB’18), pages 291-300, Washington, DC, August 2018 (acceptance rate: 31.0%)

System Demonstrations

  1. Qingyun Wang, Manling Li, Xuan Wang, Nikolaus Parulian, Guangxing Han, Jiawei Ma, Jingxuan Tu, Ying Lin, et al., “COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation”, in Proc. of 2021 Annual Conf. of the North American Chapter of the Association for Computational Linguistics (NAACL’21) (System Demonstration), pages 66-77, Mexico City, Mexico, June 2021 (Best Demo Paper Award)
  2. Xuan Wang, Yingjun Guan, Weili Liu, Aabhas Chauhan, Enyi Jiang, Qi Li, David Liem, Dibakar Sigdel, John Caufield, Peipei Ping and Jiawei Han, “EVIDENCEMINER: Textual Evidence Discovery for Life Sciences”, in Proc. 2020 Annual Conf. of the Association for Computational Linguistics (ACL’20) (System Demonstration), pages 56-62, Seattle, WA, July 2020 [system]
  3. Jingbo Shang, Qi Zhu, Jiaming Shen, Xuan Wang, Xiaotao Gu, Lance Kaplan, Timothy Harratty, and Jiawei Han, “AutoNet: Automated Network Construction and Exploration System from Domain-Specific Corpora”, in Proc. of 2018 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD’18), (demo paper), London, UK, August 2018
  4. Xiang Ren, Jiaming Shen, Meng Qu, Xuan Wang, Zeqiu Wu, Qi Zhu, Meng Jiang et al. “Life-iNet: A Structured Network-Based Knowledge Exploration and Analytics System for Life Sciences”, in Proc. of 2017 Annual Meeting of the Association for Computational Linguistics (ACL’17), (System Demonstration), pages 55-60, Vancouver, Canada, July 2017

Workshop & Abstract Papers

  1. Xuan Wang, Vivian Hu, Xiangchen Song, Qi Li and Jiawei Han, “Textual Evidence Mining in Scientific Literature”, TrueFact Workshop: Making a Credible Web for Tomorrow at 2021 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (TrueFact@KDD’21), Aug. 2020, online.
  2. Xuan Wang, Xiangchen Song, Bangzheng Li, Yingjun Guan and Jiawei Han, “Comprehensive Named Entity Recognition on CORD-19 with Distant or Weak Supervision”, 2020 Intelligent Systems for Molecular Biology (ISMB’20), Abstracts (oral and poster), July 2020, online.
  3. Xuan Wang, Weili Liu, Aabhas Chauhan, Yingjun Guan and Jiawei Han, “Automatic Textual Evidence Mining in COVID-19 Literature”, 2020 Intelligent Systems for Molecular Biology (ISMB’20), Abstracts (poster), July 2020, online.
  4. Xuan Wang, Qi Li, Jiaxin Huang, Yu Zhang, Charles Blatti, Mikel Hernaez and Jiawei Han, “ClaimMiner: Query-guided Claim Mining in Biomedical Literature”, 2019 Intelligent Systems for Molecular Biology (ISMB’19), Abstracts (oral and poster).
  5. Yu Zhang, Xiang Ren, Xuan Wang, Qi Li and Jiawei Han. “Organizing Bioinformatics GitHub Repositories with Multidimensional Text Cube”, 2019 Intelligent Systems for Molec- ular Biology (ISMB’19), Abstracts (poster).
  6. Jiawei Han, Qi Li, Jiaming Shen, Xuan Wang, Jinfeng Xiao and Yu Zhang. “Text Mining for Biomedical Literature-Based Discovery”, 2019 Intelligent Systems for Molecular Biology (ISMB’19), Abstracts (poster).