[Google scholar profile].
(Google scholar is usually more up-to-date and I manually check all the paper entries on Google scholar.)

Recent Preprints

• Haokun Liu, Sicong Huang, Jingyu Hu, Yangqiaoyu Zhou, and Chenhao Tan. HypoBench: Towards Systematic and Principled Benchmarking for Hypothesis Generation.
• Michael Cooper, Rohan Wadhawan, John Michael Giorgi, Chenhao Tan, Davis Liang. The Curious Language Model: Strategic Test-Time Information Acquisition.
• Mingxuan Li, Hanchen Li, and Chenhao Tan. HypoEval: Hypothesis-Guided Evaluation for Natural Language Generation.
• Cristina Garbacea and Chenhao Tan. HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation.
• Mourad Heddaya, Chenhao Tan, Rob Voigt, Qingcheng Zeng, and Alexander Zentefis. A Century of Inflation Narratives.
• Zhizhang Yuan, Fanqi Shen, Meng Li, Yuguo Yu, Chenhao Tan, and Yang Yang. BrainWave: A Brain Signal Foundation Model for Clinical Applications.

2025

• Ari Holtzman and Chenhao Tan. Prompting as Scientific Inquiry. NeurIPS 2025 (position papers track). [Blog]
• Xiaoyan Bai, Ike Peng, Aditya Singh, and Chenhao Tan. Concept Incongruence: An Exploration of Time and Death in Role Playing. NeurIPS 2025. [Blog]
• Harvey Yiyun Fu, Aryan Shrivastava, Jared Moore, Peter West, Chenhao Tan, Ari Holtzman. AbsenceBench: Language Models Can’t Tell What’s Missing. NeurIPS 2025 (spotlight in Datasets and Benchmarks).
• Ziyu Chen, Junfei Sun, Chenxi Li, Tuan Dung Nguyen, Jing Yao, Xiaoyuan Yi, Xing Xie, Chenhao Tan, and Lexing Xie. MoVa: Resources for Generalizable Classification of Human Morals and Values. EMNLP 2025.
• Karen Zhou, John Giorgi, Pranav Mani, Peng Xu, Davis Liang, and Chenhao Tan. From Feedback to Checklists: Grounded Evaluation of AI-Generated Clinical Notes. EMNLP 2025 (industry track).
• Yuyang Jiang, Chacha Chen, Shengyuan Wang, Feng Li, Zecong Tang, Benjamin M. Mervak, Lydia Chelala, Christopher M Straus, Reve Chahine, Samuel G. Armato III, and Chenhao Tan. CLEAR: A Clinically-Grounded Tabular Framework for Radiology Report Evaluation. Findings of EMNLP 2025.
• Chao-Chun Hsu, Ziad Obermeyer, and Chenhao Tan. A machine learning model using clinical notes to identify physician fatigue. Nature Communications 2025. arXiv version
• Dang Nguyen and Chenhao Tan. On the Effectiveness and Generalization of Race Representations for Debiasing High-Stakes Decisions. COLM 2025.
• Haokun Liu*, Yangqiaoyu Zhou*, Mingxuan Li*, Chenfei Yuan, and Chenhao Tan. Literature Meets Data: A Synergistic Approach to Hypothesis Generation. ACL 2025. \[Website\]
• Jacy Anthis, Kristian Lum, Michael Ekstrand, Avi Feller, and Chenhao Tan. The Impossibility of Fair LLMs. ACL 2025.
• Lan Gao, Oscar Chen, Rachel Lee, Nick Feamster, Chenhao Tan, Marshini Chetty. “I Cannot Write This Because It Violates Our Content Policy”: Understanding Content Moderation Policies and User Experiences in Generative AI Products. USENIX Security 2025.
• Chacha Chen, Han Liu, Jiamin Yang, Benjamin M. Mervak, Bora Kalaycioglu, Grace Lee, Emre Cakmakli, Matteo Bonatti, Sridhar Pudu, Osman Kahraman, Gul Gizem Pamuk, Aytekin Oto, Aritrick Chatterjee, and Chenhao Tan. Can Domain Experts Rely on AI Appropriately? A Case Study on AI-Assisted Prostate Cancer MRI Diagnosis. FAccT 2025.
• Mourad Heddaya, Kyle MacMillan, Anup Malani, Hongyuan Mei, and Chenhao Tan. CaseSumm: A Large-Scale Dataset for Long-Context Summarization from U.S. Supreme Court Opinions. Findings of NAACL 2025.
• Yuyang Jiang, Chacha Chen, Dang Nguyen, Benjamin M. Mervak, and Chenhao Tan. GPT-4V Cannot Generate Radiology Reports Yet. Findings of NAACL 2025.

2024

• Yangqiaoyu Zhou, Haokun Liu, Tejes Srivastava, Hongyuan Mei, and Chenhao Tan. Hypothesis Generation with Large Language Models. NLP4Science workshop at EMNLP 2024.
• Mourad Heddaya, Qingcheng Zeng, Chenhao Tan, Rob Voigt, and Alexander Zentefis. Causal Micro-Narratives. EMNLP 2024 Workshop on Narrative Understanding.
• Emre Kıcıman, Robert Ness, Amit Sharma, and Chenhao Tan. Causal Reasoning and Large Language Models: Opening a New Frontier for Causality. Transactions on Machine Learning Research (TMLR) 2024.
• Karen Zhou, Alexander A. Meitus, Milo Chase, Grace Wang, Anne Mykland, William Howell, and Chenhao Tan. Quantifying the uniqueness and divisiveness of presidential discourse. PNAS Nexus 2024.
• Tianyu Cao, Natraj Raman, Danial Dervovic, and Chenhao Tan. Characterizing Multimodal Long-form Summarization: A Case Study on Financial Reports. COLM 2024.
• Chao-Chun Hsu, Erin Bransom, Jenna Sparks, Bailey Kuehl, Chenhao Tan, David Wadden, Lucy Lu Wang, Aakanksha Naik. CHIME: LLM-Assisted Hierarchical Organization of Scientific Studies for Literature Review Support. Findings of ACL 2024.
• Zining Zhu, Hanjie Chen, Xi Ye, Chenhao Tan, Ana Marasović, Sarah Wiergreffe, Veronica Qing Lyu. Explanation in the Era of Large Language Models. NAACL tutorial 2024.
• Brennan Schaffner, Arjun Nitin Bhagoji, Siyuan Cheng, Jacqueline Mei, Jay L Shen, Grace Wang, Marshini Chetty, Nick Feamster, Genevieve Lakier, Chenhao Tan. “Community Guidelines Make this the Best Party on the Internet”: An In-Depth Study of Online Platforms’ Content Moderation Policies. CHI 2024.
• C. Estelle Smith, Shamika Klassen, Gale H. Prinster, Chenhao Tan, and Brian C. Keegan. Governance of the Black Experience on Reddit: r/BlackPeopleTwitter as a Case Study in Supporting Sense of Virtual Community for Black Users. CSCW 2024. DEI Recognition Award (Top 4% of papers).
• Gale H. Prinster, C. Estelle Smith, Chenhao Tan, and Brian C. Keegan. Community Archetypes: An Empirical Framework for Guiding Research Methodologies to Reflect User Experiences of Sense of Virtual Community. CSCW 2024.
• Jiashuo Wang, Yang Xiao, Yanran Li, Changhe Song, Chunpu Xu, Chenhao Tan, and Wenjie Li. Towards a Client-Centered Assessment of LLM Therapists by Client Simulation.

2023

• Dang Nguyen, Chacha Chen, He He, and Chenhao Tan. Pragmatic Radiology Report Generation. Machine Learning for Health (ML4H) 2023.
• Xiaoming Shi, Siqiao Xue, Kangrui Wang, Fan Zhou, James Y. Zhang, Jun Zhou, Chenhao Tan, and Hongyuan Mei. Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning. NeurIPS 2023.
• Karen Zhou and Chenhao Tan. Entity-Based Evaluation of Political Bias in Automatic Summarization. Findings of EMNLP 2023 (short paper). Presented at TrustNLP at ACL 2023.
• Nan-Jiang Jiang, Chenhao Tan, and Marie-Catherine de Marneffe. Ecologically Valid Explanations for Label Variation in NLI. Findings of EMNLP 2023 (short paper).
• Vivian Lai, Yiming Zhang, Chacha Chen, Q. Vera Liao, and Chenhao Tan. Selective Explanations: Leveraging Human Input to Align Explainable AI. CSCW 2023.
• Raul Castro Fernandez, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan, and Chenhao Tan. How large language models will disrupt data management. VLDB 2023.
• Chacha Chen, Shi Feng, Amit Sharma, and Chenhao Tan. Machine Explanations and Human Understanding. Accepted at Transactions on Machine Learning Research (TMLR); presented at FAccT 2023; Best paper award at the ICML 2022 Workshop on Human-Machine Collaboration and Teaming (workshop version).
• Vivian Lai, Chacha Chen, Alison Smith-Renner, Q. Vera Liao, and Chenhao Tan. Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies. In Proceedings of FAccT 2023.
• Mourad Heddaya, Solomon Dworkin, Chenhao Tan, Rob Voigt, and Alexander Zentefis. Language of Bargaining. In Proceedings of ACL 2023.
• Yangqiaoyu Zhou, Yiming Zhang, and Chenhao Tan. FLamE: Few-shot Learning from Natural Language Explanations. In Proceedings of ACL 2023.
• Han Liu, Yizhou Tian, Chacha Chen, Shi Feng, Yuxin Chen, and Chenhao Tan. Learning Human-Compatible Representations for Case-Based Decision Support. In Proceedings of ICLR 2023.
• Yiming Zhang, Yangqiaoyu Zhou, Samuel Carton and Chenhao Tan. Learning to Ignore Adversarial Attacks. In Proceedings of EACL 2023.
• Yuan Yuan, Tracy Xiao Liu, Chenhao Tan, Qian Chen, Alex ‘Sandy’ Pentland, and Jie Tang. Gift Contagion in Online Groups: Evidence From Virtual Red Packets. Management Science. 2023.
• Xuan Yang, Yang Yang, Chenhao Tan, Yinghe Lin, Zhengzhe Fu, Fei Wu, and Yueting Zhuang. Unfolding and Modeling the Recovery Process after COVID Lockdowns. Scientific Reports. 2023.

2022

• Jordan Boyd-Graber, Samuel Carton, Shi Feng, Q. Vera Liao, Tania Lombrozo, Alison Smith-Renner, Chenhao Tan. Human-Centered Evaluations of Explanations. NAACL tutorial 2022.
• Han Liu, Yizhou Tian, Chacha Chen, Shi Feng, Yuxin Chen, Chenhao Tan. Towards Effective Case-Based Decision Support with Human-Compatible Representations. In Proceedings of the 1st ICML 2022 Workshop on Human-Machine Collaboration and Teaming.
• Yiming Zhang, Shi Feng, Chenhao Tan. Active Example Selection for In-Context Learning. EMNLP 2022.
• Abhinav Kumar, Chenhao Tan, Amit Sharma. Probing Classifiers are Unreliable for Concept Removal and Detection. NeurIPS 2022; also presented at the Spurious correlations, Invariance, and Stability (SCIS) workshop at ICML 2022.
• Vivian Lai, Samuel Carton, Rajat Bhatnagar, Q. Vera Liao, Yunfeng Zhang, and Chenhao Tan. Human-AI Collaboration via Conditional Delegation: A Case Study of Content Moderation. CHI 2022.
• Samuel Carton, Surya Kanoria, and Chenhao Tan. What to Learn, and How: Toward Effective Learning from Rationales. Findings of ACL 2022.
• Chenhao Tan. On the Diversity and Limits of Human Explanations. NAACL 2022.
• Jamar L. Sullivan, Will Brackenbury, Andrew McNutt, Kevin Bryson, Kwam Byll, Yuxin Chen, Michael Littman, Chenhao Tan, Blase Ur. Explaining Why: How Instructions and User Interfaces Impact Annotator Rationales When Labeling Text Data. NAACL 2022.
• C. Estelle Smith, Irfanul Alam, Chenhao Tan, Brian C. Keegan, Anita Blanchard. The Impact of Governance Bots on Sense of Virtual Community: Development and Validation of the GOV-BOTs Scale. CSCW 2022.
• Himabindu Lakkaraju, Dylan Slack, Yuxin Chen, Chenhao Tan, and Sameer Singh. Rethinking Explainability as a Dialogue: A Practitioner’s Perspective. Preprint.

2021

• Chao-Chun Hsu and Chenhao Tan. Decision-focused Summarization. EMNLP 2021.
• Han Liu, Vivian Lai, and Chenhao Tan. Understanding the Effect of Out-of-distribution Examples and Interactive Explanations on Human-AI Decision Making. CSCW 2021.
• Ramaravind Kommiya Mothilal, Divyat Mahajan, Chenhao Tan and Amit Sharma. Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End. In Proceedings of the Fourth AAAI/ACM conference on Artificial Intelligence, Ethics, and Society (AIES'2021); also presented at the Reponsible AI workshop at ICLR.
• Madhusudhan Aithal Mahabhaleshwara and Chenhao Tan. On Positivity Bias in Negative Reviews. In Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) (short paper).
• Yangqiaoyu Zhou and Chenhao Tan. Investigating the Effect of Natural Language Explanations on Out-of-Distribution Generalization in Few-shot NLI. Workshop on Insights from Negative Results in NLP at EMNLP 2021.
• Jason Shuo Zhang, Qin Lv, Brian Keegan, and Chenhao Tan. Understanding the Diverging User Trajectories in Highly-related Online Communities during the COVID-19 Pandemic. In Proceedings of the 15th International Conference On Web and Social Media (ICWSM'2021).
• Isil Erel, Lea Stern, Chenhao Tan, Michael S. Weisbach. Selecting Directors Using Machine Learning. Review of Financial Studies. 2021.
• Abhijit Suresh, Jennifer Jacobs, Vivian Lai, Chenhao Tan, Wayne Ward, James H. Martin, Tamara Sumner. Using Transformers to Provide Teachers with Personalized Feedback on their Classroom Discourse: The TalkMoves Application. AAAI Spring Symposium Series 2021.
• Abhijit Suresh, Jennifer Jacobs, Charis Clevenger, Vivian Lai, Chenhao Tan, James H. Martin and Tamara Sumner. Using AI to promote equitable classroom instruction: The TalkMoves Application. In Proceedings of the 22nd International Conference on Artificial Intelligence in Education (AIED'2021) (short paper).

2020

• Chao-Chun Hsu, Shantanu Karnwal, Sendhil Mullainathan, Ziad Obermeyer, and Chenhao Tan. Characterizing the Value of Information in Medical Notes. In Findings of EMNLP 2020.
• Samuel Carton, Anirudh Rathore, and Chenhao Tan. Evaluating and Characterizing Human Rationales. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP'2020).
• Vivian Lai, Samuel Carton, and Chenhao Tan. Harnessing Explanations to Bridge AI and Humans. In Fair & Responsible AI Workshop, CHI 2020.
• Vivian Lai, Han Liu, and Chenhao Tan. “Why is ‘Chicago’ deceptive?”: Towards Building Model-Driven Tutorials for Humans. In Proceedings of the ACM CHI Conference on Human Factors in Computing Systems 2020 (CHI'2020).
• Ramaravind Kommiya Mothilal, Amit Sharma, and Chenhao Tan. Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations. In Proceedings of ACM FAT* Conference 2020.

2019

• Brian Lubars and Chenhao Tan. Ask Not What AI Can Do, But What AI Should Do: Towards a Framework of Task Delegability. In Proceedings of Thirty-third Conference on Neural Information Processing Systems (NeurIPS'2019) (spotlight presentation).
• David Atkinson, Kumar Bhargav Srinivasan, and Chenhao Tan. What Gets Echoed? Understanding the ‘Pointers’ in Explanations of Persuasive Arguments. In Proceedings of 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing (EMNLP'2019).
• Vivian Lai, Jon Z. Cai, and Chenhao Tan. Many Faces of Feature Importance: Comparing Built-in and Post-hoc Feature Importance in Text Classification. In Proceedings of 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing (EMNLP'2019).
• Kelvin Luu, Chenhao Tan, and Noah A. Smith. Measuring Online Debaters’ Persuasive Skill from Text over Time. Transactions of the Association for Computational Linguistics (TACL'2019).
• Jason Shuo Zhang, Chenhao Tan, and Qin Lv. Intergroup Contact in the Wild: Characterizing Language Differences between Intergroup and Single-group Members in NBA-related Discussion Forums. In Proceedings of the Conference on Computer-Supported Cooperative Work and Social Computing (CSCW'2019).
• Kumar Bhargav Srinivasan, Cristian Danescu-Niculescu-Mizil, Lillian Lee, and Chenhao Tan. Content Removal as a Moderation Strategy: Compliance and Other Outcomes in the ChangeMyView Community. In Proceedings of the Conference on Computer-Supported Cooperative Work and Social Computing (CSCW'2019).
• Vivian Lai and Chenhao Tan. On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detection. In Proceedings of ACM FAT* Conference 2019.
• Xiaochuang Han, Eunsol Choi, and Chenhao Tan. No Permanent Friends or Enemies: Tracking Relationships Between Nations from News. In Proceedings of 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL'2019).
• Tiago Cunha, David Jurgens, Chenhao Tan and Daniel Romero. Are All Successful Communities Alike? Characterizing and Predicting the Success of Online Communities. In Proceedings of The Web Conference 2019 (WWW'2019).
• Ziqiang Cheng, Yang Yang, Chenhao Tan, Denny Cheng, Alex Cheng and Yueting Zhuang. What Makes a Good Team? A Large-scale Study on the Effect of Team Composition in Online Gaming. In Proceedings of The Web Conference 2019 (WWW'2019) (short paper).

2018

• Jason Shuo Zhang, Chenhao Tan, and Qin Lv.
  “This is why we play”: Characterizing Online Fan Communities of the NBA Teams. In Proceedings of the Conference on Computer-Supported Cooperative Work and Social Computing (CSCW'2018).

• Tal August, Nigini Oliveira, Chenhao Tan, Noah A. Smith, and Katharina Reinecke.
  Framing Effect: The Choice of Slogans Used to Advertise Online Experiments Can Boost Recruitment and Lead to Sample Biases. In Proceedings of the Conference on Computer-Supported Cooperative Work and Social Computing (CSCW'2018).

• Dallas Card, Chenhao Tan, and Noah A. Smith.
  Neural Models for Documents with Metadata. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL'2018).

• Nelson F. Liu, Omer Levy, Roy Schwartz, Chenhao Tan, and Noah A. Smith.
  LSTMs Exploit Linguistic Attributes of Data.
  In Proceedings of ACL 2018 RepL4NLP Workshop (Best paper award).

• Chenhao Tan.
  Tracing Community Genealogy: How New Communities Emerge from the Old. In Proceedings of the 12th International AAAI Conference on Web and Social Media (ICWSM'18).

• Chenhao Tan, Hao Peng, and Noah A. Smith.
  “You are no Jack Kennedy”: On Media Selection of Highlights from Presidential Debates. In Proceedings of The Web Conference (WWW’2018).

• Yang Yang, Zongtao Liu, Chenhao Tan, Fei Wu, Yueting Zhuang and Yafeng Li.
  To Stay or to Leave: Churn Prediction for Urban Migrants in the Initial Period. In Proceedings of The Web Conference (WWW’2018).

• Isil Erel, Léa H. Stern, Chenhao Tan, and Michael S. Weisbach.
  Could Machine Learning Help Companies Select Better Board Directors?. Harvard Business Review. April, 2018.

• Elizabeth Clark, Anne Ross, Chenhao Tan, Yangfeng Ji, and Noah A. Smith.
  Creative Writing with a Machine in the Loop: Case Studies on Slogans and Stories. In Proceedings of the 23rd ACM Conference on Intelligent User Interfaces (IUI’2018).

• Yang Yang, Chenhao Tan, Zongtao Liu, Fei Wu, and Yueting Zhuang.
  Urban Dreams of Migrants: A Case Study of Migrant Integration in Shanghai. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI'2018).

2017

• Yangfeng Ji, Chenhao Tan, Sebastian Martschat, Yejin Choi, Noah A. Smith
  Dynamic Entity Representations in Neural Language Models. In Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP'2017).
• Chenhao Tan, Dallas Card, Noah A. Smith.
  Friendships, Rivalries, and Trysts: Characterizing Relations between Ideas in Texts. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL'2017).

2016

• Chenhao Tan.
  Computational approaches to understanding human behavior from online social interactions: Language and Communities. PhD thesis.
• Chenhao Tan, Lillian Lee.
  Talk it up or play it down? (Un)expected correlations between (de-)emphasis and recurrence of discussion points in consequential U.S. economic policy meetings. Presented in Text As Data 2016.
• Chenhao Tan, Vlad Niculae, Cristian Danescu-Niculescu-Mizil, Lillian Lee.
  Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions. In Proceedings of the 25th International World Wide Web Conference (WWW'2016).
• Isabel Kloumann, Chenhao Tan, Jon Kleinberg, Lillian Lee.
  Internet Collaboration on Extremely Difficult Problems: Research versus Olympiad Questions on the Polymath Site. In Proceedings of the 25th International World Wide Web Conference (WWW'2016).
• Chenhao Tan, Adrien Friggeri, Lada Adamic.
  Lost in propagation? Unfolding news cycles from the source. In Proceedings of the 10th International AAAI Conference on Web and Social Media (ICWSM'2016).
• Jack Hessel, Chenhao Tan, Lillian Lee.
  Science, AskScience, and BadScience: On the Coexistence of Highly Related Communities. In Proceedings of the 10th International AAAI Conference on Web and Social Media (ICWSM'2016).

2015

• Chenhao Tan, Lillian Lee.
  All Who Wander: On the Prevalence and Characteristics of Multi-community Engagement. In Proceedings of the 24th International World Wide Web Conference (WWW'2015).

2014

• Chenhao Tan, Lillian Lee, Bo Pang.
  The effect of wording on message propagation: Topic- and author-controlled natural experiments on Twitter. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL'14) \[[Quiz][nyt_quiz_link] on NYT\]\[[Prediction tool][acl14_demo]\] (featured on The New York Times and other media outlets).
• Chenhao Tan, Lillian Lee.
  A Corpus of Sentence-level Revisions in Academic Writing: A Step towards Understanding Statement Strength in Communication. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL'2014) (short paper).
• Jon Kleinberg, Sendhil Mullainathan, Chenhao Tan, Thomas Zimmermann.
  Inductive Testing: Theory and an Application to the Disposition Effect.
  NBER Behavioral Finance Working Group, 2014.

2013

• Chenhao Tan, Ed H. Chi, David Huffaker, Gueorgi Kossinets, Alexander J. Smola.
  Instant Foodie: Predicting Expert Ratings From Grassroots. In Proceedings of 22nd ACM International Conference on Information and Knowledge Management (CIKM'2013).
• Daniel M. Romero, Chenhao Tan, Johan Ugander.
  On the Interplay between Social and Topical Structure. In Proceedings of 7th International AAAI Conference on Weblogs and Social Media (ICWSM'2013).

2012

• Chenhao Tan, Evgeniy Gabrilovich, Bo Pang.
  To Each His Own: Personalized Content Selection based on Text Comprehensibility. In Proceedings of the Fifth ACM International Conference on Web Search and Data Mining (WSDM'2012).
• Eunsol Choi, Chenhao Tan, Lillian Lee, Cristian Danescu-Niculescu-Mizil, Jennifer Spindel.
  Hedge detection as a lens on framing in the GMO debates: A position paper. In Proceedings of the Workshop on Extra-Propositional Aspects of Meaning in Computational Linguistics.
• Wenbin Tang, Jie Tang, Tao Lei, Chenhao Tan, Bo Gao, Tian Li.
  On optimization of expertise matching with various constraints. Neurocomputing (January, 2012).

2011

• Chenhao Tan, Lillian Lee, Jie Tang, Long Jiang, Ming Zhou, Ping Li.
  User-level sentiment analysis incorporating social networks. In Proceedings of the Sixteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD'2011) (poster, aggregate oral+poster acceptance rate: 17.5%).
• Shaomei Wu, Chenhao Tan, Jon Kleinberg, Michael Macy.
  Does Bad News Go Away Faster? In Proceedings of Fifth International AAAI Conference on Weblogs and Social Media (ICWSM'2011) (short paper).
• Bin Lu, Chenhao Tan, Claire Cardie, Benjamin K. Tsou. Joint Bilingual Sentiment Classification with Unlabeled Parallel Corpora. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics (ACL'2011).
• Fei Wang, Chenhao Tan, Arnd Christian Konig, Ping Li.
  Efficient Document Clustering via Online Nonnegative Matrix Factorizations. In Proceedings of the SIAM International Conference on Data Mining (SDM'2011).

2010

• Chenhao Tan, Jie Tang, Jimeng Sun, Quan Lin, Fengjiao Wang.
  Social Action Tracking via Noise Tolerant Time-varying Factor Graphs. In Proceedings of the Sixteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD'2010).
  [A companion page with details that I made as an undergrad]
• Wenbin Tang, Jie Tang, Chenhao Tan.
  Expertise Matching via Constrained-based Optimization. In Proceedings of 2010 IEEE/WIC/ACM International Conferences (WIC'2010).
  [A link to the details of the journal version)]