Yu Su (苏煜)

About Me

Yu Su

I'm a Distinguished Assistant Professor of Engineering Inclusive Excellence at the Department of Computer Science and Engineering, The Ohio State University, where I co-direct the OSU NLP group, co-lead the Foundational AI team in the ICICLE AI Institute and lead the Machine Learning Foundations team in the Imageomics Institute. I also spend some fun time at Microsoft Semantic Machines. I got my PhD from University of California, Santa Barbara and my bachelor's degree from Tsinghua University, both in Computer Science.

I have broad interests in developing artificial intelligence, with a primary interest in the role of language, as a vehicle of thought and communication, in both artificial and human intelligence. These days, I'm particularly fond of foundation models, including both large language models (LLMs) and multimodal ones, and I believe they are an important step towards more general AI and should be studied thoroughly. I enjoy developing language agents that, in a robust and trustworthy way, automate a lot of our tedious tasks and make the computing world more accessible to all. I like to make things that work, which often means operating at scale and in real-world settings. For that I also deeply care about generalizability, interpretability, efficiency, and robustness. Finally, I believe in translational research and seek to leverage AI capabilities to empower a variety of domains such as biology and biomedicine, and meanwhile seek inspirations from these disciplines to develop better AI.

I'm always looking for highly motivated students. Drop me an email with CV and transcripts if you are interested in natural language processing, machine learning, or AI in general (unfortunately due to the high volumn I may not be able to reply to every email)

What's New

  • These days language agents are what excit me most, so much so that I wrote my first blog about it.
  • 05/2024: Thrilled to release HippoRAG and bring my passion about biological intelligence into AI!
  • 05/2024: 2 papers accepted to ACL'24: tool learning through simulated trial and error and planning with LLMs (or why it's hard).
  • 05/2024: New talk on a holistic and critical look at language agents at the CMU Agent Workshop.
  • 05/2024: 3 papers accepted to ICML'24: SeeAct, TravelPlanner, MagicLens.
  • 04/2024: Honored that both BioCLIP and MMMU are selected for oral presentation at CVPR'24 (90/11,532, 0.8%)!
  • 02/2024: 3 papers accepted to CVPR'24: BioCLIP, MMMU, multimodal web agents.
  • 02/2024: Excited to release TravelPlanner, a real-world planning benchmark for language agents.
  • 01/2024: 5 papers accepted to ICLR'24 on knowledge conflicts in LLMs, MAmmoTH, AgentBench, Interpretable Transformer, MUFFIN.
  • 01/2024: Thrilled to release SeeAct, enabling everyone to use GPT-4V-based web agents with one click.
  • 12/2023: Thrilled to release BioCLIP, a vision foundation model for the tree of life.
  • 11/2023: Excited to release MMMU, a new multimodal benchmark for Expert AGI.
  • 10/2023: Invited talks at IJCAI, UCSD, Tsinghua, Fudan, University of Hong Kong, Pinterest, and Salesforce AI Research on language agents (slides).
  • 10/2023: 3 papers accepted to EMNLP'23 on attribution evaluation of LLMs, text-to-SQL error detection, and biomedical NLP.
  • 09/2023: 3 papers accepted to NeurIPS'23: Mind2Web (spotlight), MagicBrush, and Holistic Transfer.
  • 07/2023: Glad that LLM-Planner that uses LLMs for embodied agent planning got accepted to ICCV'23!
  • 07/2023: Honored that our paper Pangu received the Outstanding Paper Award from ACL 2023!
  • 06/2023: Invited talks at Army Research Lab and OSU RISK Institute.
  • 05/2023: 6 papers accepted to ACL'23. Congrats to all the students and collaborators!
  • 05/2023: Grateful to receive support from NIH R01 for our research on AI and biomedicine!
  • 04/2023: Honored to receive support from President Johnson for our research on large language models!
  • 03/2023: Invited talks at University of Tokyo and Amazon on grounding language models to real-world environments.
  • 03/2023: Honored to receive the College of Engineering Lumley Research Award!
  • 01/2023: Check out a summary of the major achievements by the OSU NLP group in 2022!
  • 12/2022: Serve as Area Chair for ACL'23.
  • 11/2022: Serve as Workflow Co-Chair for SIGKDD'23.
  • 10/2022: Excited that our ArcaneQA paper won the Outstanding Paper Award at COLING'22 (top 15 out of 2253 submissions)!
  • 10/2022: Papers on broad-coverage conversational AI and GPT-3 for biomedical information extraction accepted to EMNLP'22!
  • 09/2022: New grant from ARL for knowledge-based embodied AI.
  • 08/2022: Honored to receive the Distinguished Assistant Professorship of Engineering Inclusive Excellence from OSU for research and contributions towards democratizing AI!
  • 08/2022: Paper on question answering over large knowledge graphs accepted to COLING'22.
  • 07/2022: Serve as Senior PC member for AAAI'23.
  • 07/2022: Invited talk at the DLG4NLP workshop at NAACL'22: Will Graphs Lead to the Next Breakthrough of Conversational AI?
  • 06/2022: Our OSU team won the 3rd place in the inaugural Amazon Alexa Prize TaskBot Challenge! Check out our website.
  • 05/2022: Thank you, Walmart and Cisco, for supporting our research!
  • 04/2022: Talk at Nanjing University and JD.com on emerging frontiers of conversational AI.
  • 02/2022: Paper on long-horizon vison-and-language navigation accepted to CVPR 2022.
  • 02/2022: Paper on text-to-SQL generalization accepted to ACL 2022.
  • 12/2021: Check out a summary of the major achievements by the OSU NLP group in 2021!
  • 11/2021: Our team is selected to participate in the Alexa Prize SimBot challenge!
  • 09/2021: Excited to be a part of the Imageomics Institute -- a new NSF HDR Institute dedicated for knowledge-guided machine learning for biology. I will lead the Machine Learning Foundations team.
  • 08/2021: Paper on pre-trained language models with better reasoning capabilities accepted to EMNLP 2021.
  • 07/2021: Excited to be a part of ICICLE -- a new NSF AI Institute dedicated to democratizing AI through AI and cyberinfrastructure innovations. I will lead the AI team with Eric Fosler-Lussier. Read more.
  • 07/2021: Talk at USC/ISI and Beijing Academy of Artificial Intelligence on Emerging Frontiers of Conversational AI.
  • 05/2021: Long paper on large-scale joint KB and text embedding accepted to ACL 2021.
  • 03/2021: Received an Accelerator Grant from OSU TDAI on NLP for Social Media Pharmacovigilance.
  • 03/2021: Short Paper on compositional generalization for neural semantic parsing accepted to NAACL-HLT 2021.
  • 01/2021: Paper on non-i.i.d. generalization of question answering on knowledge bases accepted to TheWebConf 2021 (previously WWW).
  • 11/2020: Will co-organize the First Workshop on Natural Language Processing for Programming at ACL-IJCNLP 2021.
  • 09/2020: Will serve on the organizing committee of NAACL 2021.
  • 09/2020: Super excited to share some of the work I've been working on at Microsoft Semantic MachinesTask-Oriented Dialogue as Dataflow Synthesis (TACL'20)
  • 09/2020: Two long papers (learning language interfaces from use and data-to-text generation) accepted to EMNLP'20. One short paper on document classification for COVID-19 literature accepted to Findings of EMNLP.
  • 05/2020: Serve as Area Chair (Conversational Bot/QA) at NLPCC'20. Serve in the Program Committee of ACL'20, KDD'20 (chair of Trustworthy Data Mining session), EMNLP'20, AAAI'21, AKBC'20, IntEx-SemPar'20.
  • 04/2020: Long paper on logical natural language generation accepted to ACL 2020
  • 03/2020: Thank you, Fujitsu Laboratories of America, for supporting our research!
  • 01/2020: Started as Assistant Professor of Computer Science and Engineering at the Ohio State University
  • 08/2019: Long paper on model-based interactive semantic parsing got accepted to EMNLP 2019
  • 08/2019: Long paper on taxonomic categorization of documents got accepted to ICDM 2019
  • 05/2019: Short paper on general-purpose textual relation embedding got accepted to ACL 2019
  • 05/2019: Received Outstanding Dissertation Award of Computer Science from UCSB. Thank you UCSB!
  • 05/2019: Check out what we are doing at Microsoft Semantic Machines (highlighted in Microsoft Build 2019)!
  • 02/2019: Full paper on vocabulary selection got accepted to NAACL 2019
  • 02/2019: Talk at Stanford NLP Seminar on democratizing data science with knowledge engines
  • 11/2018: Full paper on zero-shot video captioning got accepted to AAAI 2019
  • 10/2018: Started as researcher at Microsoft Semantic Machines in Berkeley working on conversational AI.
  • 08/2018: Full paper on concept mining from text got accepted to ICDM 2018.
  • 08/2018: Two long papers on dialog/semantic parsing got accepted to EMNLP 2018.
  • 07/2018: Our work on natural language interfaces to APIs highlighted in Microsoft Research Blog!
  • 06/2018: Serve as PC member for ACL'18, EMNLP'18, CoNLL'18, NLPCC'18, and AAAI'19.
  • 04/2018: Paper "DialSQL: Dialogue Based Structured Query Generation" accepted to ACL'18 as long paper: Improve semantic parsing with dialog.
  • 04/2018: Paper "Natural Language Interfaces with Fine-Grained User Interaction: A Case Study on Web APIs" accepted to SIGIR'18 as long paper.
  • 03/2018: Awarded the Best Distinguished Graduate Student Lecture of UCSB CS Summit.
  • 02/2018: Paper "Global Relation Embedding for Relation Extraction" accepted to NAACL-HLT'18: Robust relation extraction from text with global statistics.
  • 02/2018: Talk about "Bridging the Gap between Human and Data with AI" at the University of Massachusetts, Amherst.
  • 02/2018: Successfully organized the first Workshop on Knowledge Base Construction, Reasoning and Mining at Los Angeles. Check out the great invited talks and accepted papers!
  • 01/2018: Talk about "Bridging the Gap between Human and Data with AI" at the Ohio State University.
  • 12/2017: I will serve in the Program Committee (Research Track) of KDD'18
  • 12/2017: Paper "Unsupervised Neural Categorization for Scientific Publications" accepted to SDM'18.
  • 11/2017: Attended CIKM'17 in Singapore and gave a talk on natural lanugage interface and a tutorial on construction and querying of large-scale knowledge bases.
  • 10/2017: Upcoming visits in China: 10.09-10.15 (Alibaba, Hangzhou), 10.10 (Fudan University, Shanghai), 10.11 (The Computing Conferencce, Hangzhou), 10.16 (Tsinghua University, Beijing), 10.17 (Toutiao AI Lab, Beijing)
  • 09/2017: I'm co-organizing the First Workshop on Knowledge Base Construction, Reasoning and Mining (KBCOM'18) co-located with WSDM'18 on Feb 9, 2018 at Los Angeles. CFP is out!
  • 09/2017: Finished summer internship at MSR. Flying to Copenhagen for EMNLP.
  • 08/2017: I will serve in the Program Committee of WWW'18
  • 08/2017: Paper on natural language interface to web API from zero user and data accepted to CIKM'17.
  • 07/2017: Tutorial on Construction and Querying of Large-Scale Knowledge Bases accepted to CIKM'17. See you in Singapore!
  • 06/2017: Three papers on semantic parsing/QA accepted to EMNLP'17. Thanks to my collaborators!
  • 06/2017: Started summer internship in Microsoft Research
  • 04/2017: I will serve in the Program Committee of CIKM'17
  • 03/2017: Attended a project meeting at UIUC and gave a talk on unsupervised document categorization
  • 03/2017: I will serve in the Program Committee of NLPCC'17
  • 02/2017: I will serve in the Program Committee of EMNLP'17
  • 01/2017: I will serve in the Program Committee of ACL'17
  • 11/2016: Attended EMNLP'16 in Austin, US
  • 09/2016: Our QA dataset GraphQuestions v1 is released. Check it out!
  • 09/2016: Two papers on knowledge base question answering got accepted to EMNLP'16!
  • 09/2016: Attended the Bay Area Deep Learning School, Stanford
  • 06/2016: Started summer internship in Microsoft Research, Redmond

Recent Talks

Students

     Ph.D. Students

Publications

     Preprints

  • HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models
    Bernal Jiménez Gutiérrez, Yiheng Shu, Yu Gu, Michihiro Yasunaga, Yu Su. [paper] [code]
  • Grokked Transformers are Implicit Reasoners: A Mechanistic Journey to the Edge of Generalization
    Boshi Wang, Xiang Yue, Yu Su, Huan Sun. [paper] [code]
  • Middleware for LLMs: Tools are Instrumental for Language Agents in Complex Environments
    Yu Gu, Yiheng Shu, Hao Yu, Xiao Liu, Yuxiao Dong, Jie Tang, Jayanth Srinivasa, Hugo Latapie, Yu Su. [paper]
  • A Trembling House of Cards? Mapping Adversarial Attacks against Language Agents
    Lingbo Mo, Zeyi Liao, Boyuan Zheng, Yu Su, Chaowei Xiao, Huan Sun. [paper]
  • Deductive Beam Search: Decoding Deducible Rationale for Chain-of-Thought Reasoning
    Tinghui Zhu*, Kai Zhang*, Jian Xie, Yu Su. [paper] [code] (*: Equal Contribution)
  • Multimodal Question Answering for Unified Information Extraction
    Yuxuan Sun*, Kai Zhang*, Yu Su. [paper] [code] (*: Equal Contribution)
  • Memorization for Good: Encryption with Autoregressive Language Models
    Samuel Stevens, Yu Su. [paper] [blog] [code]

     Refereed Publications

  • LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error
    Boshi Wang, Hao Fang, Jason Eisner, Benjamin Van Durme, Yu Su. In the Annual Conference of the Association for Computational Linguistics, 2024 (ACL'24) [paper][code]
  • When is Tree Search Useful for LLM Planning? It Depends on the Discriminator
    Ziru Chen, Michael White, Raymond Mooney, Ali Payani, Yu Su, Huan Sun. In the Annual Conference of the Association for Computational Linguistics, 2024 (ACL'24) [paper]
  • MagicLens: Self-Supervised Image Retrieval with Open-Ended Instructions
    Kai Zhang, Yi Luan, Hexiang Hu, Kenton Lee, Siyuan Qiao, Wenhu Chen, Yu Su, Ming-Wei Chang. In the International Conference on Machine Learning, 2024 (ICML'24) [project][paper]
    Oral (1.5%)
  • GPT-4V(ision) is a Generalist Web Agent, if Grounded
    Boyuan Zheng, Boyu Gou, Jihyung Kil, Huan Sun, Yu Su. In the International Conference on Machine Learning, 2024 (ICML'24) [project website] [paper] [code]
  • TravelPlanner: A Benchmark for Real-World Planning with Language Agents
    Jian Xie*, Kai Zhang*, Jiangjie Chen, Tinghui Zhu, Renze Lou, Yuandong Tian, Yanghua Xiao, Yu Su. In the International Conference on Machine Learning, 2024 (ICML'24) [project website] [paper] [code] (*: Equal Contribution)
    Spotlight (3.5%)
  • BioCLIP: A Vision Foundation Model for the Tree of Life
    Samuel Stevens*, Jiaman Wu*, Matthew J Thompson, Elizabeth G Campolongo, Chan Hee Song, David Edward Carlyn, Li Dong, Wasila M Dahdul, Charles Stewart, Tanya Berger-Wolf, Wei-Lun Chao, Yu Su. In the Conference on Computer Vision and Pattern Recognition, 2024 (CVPR'24) [project website] [paper] [code] (*: Equal Contribution)
    Oral (0.8%)
  • MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
    Xiang Yue*, Yuansheng Ni, Kai Zhang, Tianyu Zheng, Ruoqi Liu, Ge Zhang, Samuel Stevens, Dongfu Jiang, Weiming Ren, Yuxuan Sun, Cong Wei, Botao Yu, Ruibin Yuan, Renliang Sun, Ming Yin, Boyuan Zheng, Zhenzhu Yang, Yibo Liu, Wenhao Huang, Huan Sun, Yu Su*, Wenhu Chen*. In the Conference on Computer Vision and Pattern Recognition, 2024 (CVPR'24) [project website] [paper] [code] [data] (*: corresponding authors)
    Oral (0.8%)
  • Dual-View Visual Contextualization for Web Navigation
    Jihyung Kil, Chan Hee Song, Boyuan Zheng, Xiang Deng, Yu Su, Wei-Lun Chao. In the Conference on Computer Vision and Pattern Recognition, 2024 (CVPR'24) [paper]
  • Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflicts
    Jian Xie*, Kai Zhang*, Jiangjie Chen, Renze Lou, Yu Su. In the International Conference on Learning Representations, 2024 (ICLR'24) [paper] [code] (*: Equal Contribution)
    Spotlight (5%)
  • MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning
    Xiang Yue, Xingwei Qu, Ge Zhang, Yao Fu, Wenhao Huang, Huan Sun, Yu Su, Wenhu Chen. In the International Conference on Learning Representations, 2024 (ICLR'24) [paper] [project] [code] [data]
    Spotlight (5%)
  • AgentBench: Evaluating LLMs as Agents
    Xiao Liu*, Hao Yu*, Hanchen Zhang, Yifan Xu, Xuanyu Lei, Hanyu Lai, Yu Gu, Hangliang Ding, Kaiwen Men, Kejuan Yang, Shudan Zhang, Xiang Deng, Aohan Zeng, Zhengxiao Du, Chenhui Zhang, Sheng Shen, Tianjun Zhang, Yu Su, Huan Sun, Minlie Huang, Yuxiao Dong, Jie Tang. In the International Conference on Learning Representations, 2024 (ICLR'24) [paper] [code] (*: Equal Contribution)
  • MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction-Following
    Renze Lou, Kai Zhang, Jian Xie, Yuxuan Sun, Janice Ahn, Hanzi Xu, Yu Su, Wenpeng Yin. In the International Conference on Learning Representations, 2024 (ICLR'24) [project website] [paper] [code]
  • A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis
    Dipanjyoti Paul, Arpita Chowdhury, Xinqi Xiong, Feng-Ju Chang, David Carlyn, Samuel Stevens, Kaiya Provost, Anuj Karpatne, Bryan Carstens, Daniel Rubenstein, Charles Stewart, Tanya Berger-Wolf, Yu Su, Wei-Lun Chao. In the International Conference on Learning Representations, 2024 (ICLR'24) [paper] [code]
  • Automatic Evaluation of Attribution by Large Language Models
    Xiang Yue, Boshi Wang, Kai Zhang, Ziru Chen, Yu Su, Huan Sun. In the Findings of the Conference on Empirical Methods in Natural Language Processing, 2023 (EMNLP'23: Findings) [paper] [code] [data]
  • Error Detection for Text-to-SQL Semantic Parsing
    Shijie Chen, Ziru Chen, Huan Sun, Yu Su. In the Findings of the Conference on Empirical Methods in Natural Language Processing, 2023 (EMNLP'23: Findings) [paper] [InterNLP workshop at NeurIPS'22]
  • Solving the Right Problem is Key for Translational NLP: A Case Study in UMLS Vocabulary Insertion
    Bernal Jimenez Gutierrez, Yuqing Mao, Vinh Nguyen, Kin Wah Fung, Yu Su, Olivier Bodenreider. In the Findings of the Conference on Empirical Methods in Natural Language Processing, 2023 (EMNLP'23: Findings) [paper]
  • Mind2Web: Towards a Generalist Agent for the Web
    Xiang Deng, Yu Gu, Boyuan Zheng, Shijie Chen, Samuel Stevens, Boshi Wang, Huan Sun, Yu Su. In the Conference on Neural Information Processing Systems, 2023 (NeurIPS'23) [paper] [project website] [code]
    Spotlight (5%)
  • MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing
    Kai Zhang*, Lingbo Mo*, Wenhu Chen, Huan Sun, Yu Su. In the Conference on Neural Information Processing Systems, 2023 (NeurIPS'23) [paper] [project website] [code] (*: Equal Contribution)
  • Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data
    Cheng-Hao Tu, Hong-You Chen, Jike Zhong, Zheda Mai, Vardaan Pahuja, Tanya Berger-Wolf, Song Gao, Charles Stewart, Yu Su, Wei-Lun Chao. In the Conference on Neural Information Processing Systems, 2023 (NeurIPS'23) [paper]
  • LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models
    Chan Hee Song, Jiaman Wu, Clayton Washington, Brian M. Sadler, Wei-Lun Chao, Yu Su. In the International Conference on Computer Vision, 2023 (ICCV'23) [paper] [project website] [code] [Embodied AI workshop at CVPR'23]
  • A Retrieve-and-Read Framework for Knowledge Graph Link Prediction
    Vardaan Pahuja, Boshi Wang, Hugo Latapie, Jayanth Srinivasa, Yu Su. In the ACM International Conference on Information and Knowledge Management, 2023 (CIKM'23) [paper]
  • Biomedical Language Models are Robust to Sub-optimal Tokenization
    Bernal Jimenez Gutierrez, Huan Sun, Yu Su. In the 22nd BioNLP Workshop at ACL, 2023 (BioNLP'23) [paper] [code]
  • Don't Generate, Discriminate: A Proposal for Grounding Language Models to Real-World Environments
    Yu Gu, Xiang Deng, Yu Su. In the Annual Conference of the Association for Computational Linguistics, 2023 (ACL'23) [paper] [code] Outstanding Paper Award
  • Few-shot In-context Learning on Knowledge Base Question Answering
    Tianle Li, Xueguang Ma, Alex Zhuang, Yu Gu, Yu Su, Wenhu Chen. In the Annual Conference of the Association for Computational Linguistics, 2023 (ACL'23) [paper] [code]
  • Federated Learning for Semantic Parsing: Task Formulation, Evaluation Setup, New Algorithms
    Tianshu Zhang, Changchang Liu, Wei-Han Lee, Yu Su, Huan Sun. In the Annual Conference of the Association for Computational Linguistics, 2023 (ACL'23) [paper] [code]
  • Privacy-Preserving Domain Adaptation of Semantic Parsers
    Fatemehsadat Mireshghallah, Yu Su, Tatsunori Hashimoto, Jason Eisner, Richard Shin. In the Annual Conference of the Association for Computational Linguistics, 2023 (ACL'23) [paper]
  • Text-to-SQL Error Correction with Language Models of Code
    Ziru Chen, Shijie Chen, Michael White, Raymond Mooney, Ali Payani, Jayanth Srinivasa, Yu Su, Huan Sun. In the Annual Conference of the Association for Computational Linguistics, 2023, short paper (ACL'23) [paper] [code]
  • Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation Extractors
    Kai Zhang, Bernal Jimenez Gutierrez, Yu Su. Findings of the Annual Conference of the Association for Computational Linguistics, 2023 (Findings of ACL'23) [paper] [code]
  • When More Data Hurts: A Troubling Quirk in Developing Broad-Coverage Natural Language Understanding Systems
    Elias Stengel-Eskin, Emmanouil Antonios Platanios, Adam Pauls, Sam Thomson, Hao Fang, Benjamin Van Durme, Jason Eisner, Yu Su. In the Proc. of the Conference on Empirical Methods in Natural Language Processing, 2022 (EMNLP'22) [paper] [code]
  • Thinking about GPT-3 In-Context Learning for Biomedical IE? Think Again
    Bernal Jiménez Gutiérrez, Nikolas McNeal, Clay Washington, You Chen, Lang Li, Huan Sun, Yu Su. Findings of the Conference on Empirical Methods in Natural Language Processing, 2022 (EMNLP'22: Findings) [paper] [code]
  • Knowledge Base Question Answering: A Semantic Parsing Perspective
    Yu Gu, Vardaan Pahuja, Gong Cheng, Yu Su. In the Conference on Automated Knowledge Base Construction, 2022 (AKBC'22) [paper]
  • ArcaneQA: Dynamic Program Induction and Contextualized Encoding for Knowledge Base Question Answering
    Yu Gu and Yu Su. In the International Conference on Computational Linguistics, 2022 (COLING'22) [paper] [code]
    Outstanding Paper Award
  • Bootstrapping a User-Centered Task-Oriented Dialogue System
    Shijie Chen, Ziru Chen, Xiang Deng, Ashley Lewis, Lingbo Mo, Samuel Stevens, Zhen Wang, Xiang Yue, Tianshu Zhang, Yu Su, Huan Sun. Alexa Prize TaskBot Challenge Proceedings, 2022 [paper]
  • Detecting Drug-Drug Interactions Between COVID-19 Therapies and Concomitant Medications Using the FDA Adverse Event Reporting System
    Eugene Jeong, Scott D Nelson, Yu Su, Bradley Malin, Lang Li, You Chen. Frontiers in Pharmacology, 2022 [paper]
  • Bridging the Generalization Gap in Text-to-SQL Parsing with Schema Expansion
    Chen Zhao, Yu Su, Adam Pauls, Emmanouil Antonios Platanios. In the Annual Conference of the Association for Computational Linguistics, 2022 (ACL'22) [paper] [code]
  • One Step at a Time: Long-Horizon Vision-and-Language Navigation with Milestones
    Chan Hee Song, Jihyung Kil, Tai-Yu Pan, Brian M. Sadler, Wei-Lun Chao, Yu Su. In the Conference on Computer Vision and Pattern Recognition, 2022 (CVPR'22) [paper] [code]
  • Random Control Selection for Conducting High-throughput Adverse Drug Events Screening Using Large-scale Longitudinal Health Data
    Chien-Wei Chiang, Pengyue Zhang, Macarius Donneyong, You Chen, Yu Su, Lang Li. CPT: Pharmacometrics & Systems Pharmacology, 2021 (PSP'21) [paper]
  • An Investigation of Language Model Interpretability via Sentence Editing
    Samuel Stevens and Yu Su. In the Proc. of the BlackboxNLP Workshop at EMNLP, 2021 (BlackboxNLP'21) [paper] [code and data]
  • ReasonBERT: Pre-trained to Reason with Distant Supervision
    Xiang Deng, Yu Su, Alyssa Lees, You Wu, Cong Yu and Huan Sun. In the Proc. of the Conference on Empirical Methods in Natural Language Processing, 2021 (EMNLP'21) [paper] [code and pre-trained models]
  • A Systematic Investigation of KB-Text Embedding Alignment at Scale
    Vardaan Pahuja, Yu Gu, Wenhu Chen, Mehdi Bahrami, Lei Liu, Wei-Peng Chen, and Yu Su. In the Proc. of the Annual Conference of the Association for Computational Linguistics, 2021 (ACL'21) [paper] [code]
  • Compositional Generalization for Neural Semantic Parsing via Span-level Supervised Attention
    Pengcheng Yin, Hao Fang, Graham Neubig, Adam Pauls, Emmanouil Antonios Platanios, Yu Su, Sam Thomson, and Jacob Andreas. In the Proc. of the Annual Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies, 2021, short paper (NAACL-HLT'21) [paper]
  • Beyond I.I.D.: Three Levels of Generalization for Question Answering on Knowledge Bases
    Yu Gu, Sue Kase, Michelle Vanni, Brian Sadler, Percy Liang, Xifeng Yan, and Yu Su. In the Proc. of the Web Conference (previously WWW), 2021 (TheWebConf'21) [paper] [data and leaderboard] [code]
  • Task-Oriented Dialogue as Dataflow Synthesis
    Semantic Machines, Jacob Andreas, John Bufe, David Burkett, Charles Chen, Josh Clausman, Jean Crawford, Kate Crim, Jordan DeLoach, Leah Dorner, Jason Eisner, Hao Fang, Alan Guo, David Hall, Kristin Hayes, Kellie Hill, Diana Ho, Wendy Iwaszuk, Smriti Jha, Dan Klein, Jayant Krishnamurthy, Theo Lanman, Percy Liang, Christopher H. Lin, Ilya Lintsbakh, Andy McGovern, Aleksandr Nisnevich, Adam Pauls, Dmitrij Petters, Brent Read, Dan Roth, Subhro Roy, Jesse Rusak, Beth Short, Div Slomin, Ben Snyder, Stephon Striplin, Yu Su, Zachary Tellman, Sam Thomson, Andrei Vorobev, Izabela Witoszko, Jason Wolfe, Abby Wray, Yuchen Zhang and Alexander Zotov. Transactions of the Association for Computational Linguistics, 2020 (TACL’20) [blog][paper] [code] [data and leaderboard] [Satya Nadella's Presentation at Microsoft Build 2019] [talk at EMNLP'20]
    Deployed as Conversational Interface of Microsoft Outlook
  • An Imitation Game for Learning Semantic Parsers from User Interaction
    Ziyu Yao, Yiqi Tang, Wen-tau Yih, Huan Sun, Yu Su. In Proc. of the Conference on Empirical Methods in Natural Language Processing, 2020 (EMNLP’20) [paper] [code]
  • KGPT: Knowledge-Grounded Pre-Training for Data-to-Text Generation
    Wenhu Chen, Yu Su, Xifeng Yan, William Yang Wang. In Proc. of the Conference on Empirical Methods in Natural Language Processing, 2020 (EMNLP’20) [paper] [code]
  • Document Classification for COVID-19 Literature
    Bernal Jiménez Gutiérrez, Juncheng Zeng, Dongdong Zhang, Ping Zhang, Yu Su. Findings of EMNLP'20, short paper. Presented at NLP-COVID workshop at ACL'20 [paper]
  • Logical Natural Language Generation from Open-Domain Tables
    Wenhu Chen, Jianshu Chen, Yu Su, Zhiyu Chen, William Yang Wang. In Proc. of the Annual Conference of the Association for Computational Linguistics, 2020 (ACL’20) [paper][code and data]
  • Model-based Interactive Semantic Parsing: A Unified Formulation and A Text-to-SQL Case Study
    Ziyu Yao, Yu Su, Huan Sun, Scott Wen-tau Yih. In Proc. of the Conference on Empirical Methods in Natural Language Processing, 2019 (EMNLP’19) [paper][code]
  • HierCon: Hierarchical Organization of Technical Documents based on Concepts
    Keqian Li, Shiyang Li, Semih Yavuz, Hanwen Zha, Yu Su, and Xifeng Yan. In Proc. of the IEEE International Conference on Data Mining, 2019 (ICDM’19) [paper]
    Best of ICDM 2019 Selection
  • Global Textual Relation Embedding for Relational Understanding
    Zhiyu Chen, Hanwen Zha, Honglei Liu, Wenhu Chen, Xifeng Yan and Yu Su. In Proc. of the Annual Conference of the Association for Computational Linguistics, 2019, short paper (ACL’19) [paper] [code and data]
  • How Large A Vocabulary Does Text Classification Need? A Variational Approach on Vocabulary Selection
    Wenhu Chen, Yu Su, Yilin Shen, Zhiyu Chen, Xifeng Yan and William Yang Wang. In Proc. of the Annual Conference of the North American Chapter of the Association for Computational Linguistics, 2019 (NAACL-HLT’19) [paper]
  • Learning to Compose Topic-Aware Mixture of Experts for Zero-Shot Video Captioning
    Xin Wang, Jiawei Wu, Da Zhang, Yu Su, William Yang Wang. In Proc. of the AAAI Conference on Artificial Intelligence, 2019 (AAAI’19) [paper]
  • Concept Mining via Embedding
    Keqian Li, Hanwen Zha, Yu Su, Xifeng Yan. In Proc. of the IEEE International Conference on Data Mining, 2018 (ICDM’18) [paper]
  • XL-NBT: A Cross-lingual Neural Belief Tracking Framework
    Wenhu Chen, Jianshu Chen, Yu Su, Xin Wang, Dong Yu, Xifeng Yan and William Yang Wang. In Proc. of the Conference on Empirical Methods in Natural Language Processing, 2018 (EMNLP’18) [paper]
  • What It Takes to Achieve 100% Condition Accuracy on WikiSQL
    Semih Yavuz, Izzeddin Gur, Yu Su and Xifeng Yan. In Proc. of the Conference on Empirical Methods in Natural Language Processing, 2018 (EMNLP’18) [paper]
  • DialSQL: Dialogue Based Structured Query Generation
    Izzeddin Gur, Semih Yavuz, Yu Su, Xifeng Yan. In Proc. of the Annual Meeting of the Association for Computational Linguistics, 2018, oral (ACL’18) [paper]
  • Natural Language Interfaces with Fine-Grained User Interaction: A Case Study on Web APIs
    Yu Su, Ahmed Hassan Awadallah, Miaosen Wang, Ryen White. In Proc. of the International ACM SIGIR Conference on Research and Development in Information Retrieval, 2018, oral (SIGIR’18) [paper] [Microsoft Research Blog]
  • Global Relation Embedding for Relation Extraction
    Yu Su*, Honglei Liu*, Semih Yavuz, Izzeddin Gur, Huan Sun, Xifeng Yan. In Proc. of the Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018 (NAACL-HLT’18) [paper] [code] (*: Equal Contribution)
  • Unsupervised Neural Categorization for Scientific Publications
    Keqian Li, Hanwen Zha, Yu Su, Xifeng Yan. In Proc. of the SIAM International Conference on Data Mining, 2018, oral (SDM’18) [paper]
  • Building Natural Language Interfaces to Web APIs
    Yu Su, Ahmed Hassan Awadallah, Madian Khabsa, Patrick Pantel, Michael Gamon, Mark Encarnacion. In Proc. of the ACM International Conference on Information and Knowledge Management, 2017, oral (CIKM’17) [paper] [data]
  • Cross-domain Semantic Parsing via Paraphrasing
    Yu Su, Xifeng Yan. In Proc. of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP’17) [paper] [code]
  • An End-to-End Deep Framework for Answer Triggering with a Novel Group-Level Objective
    Jie Zhao, Yu Su, Ziyu Guan, Huan Sun. In Proc. of the 2017 Conference on Empirical Methods in Natural Language Processing, short paper (EMNLP’17) [paper]
  • Recovering Question Answering Errors via Query Revision
    Semih Yavuz, Izzeddin Gur, Yu Su, Xifeng Yan. In Proc. of the 2017 Conference on Empirical Methods in Natural Language Processing, short paper (EMNLP’17) [paper]
  • On Generating Characteristic-rich Question Sets for QA Evaluation
    Yu Su, Huan Sun, Brian Sadler, Mudhakar Srivatsa, Izzeddin Gur, Zenghui Yan, Xifeng Yan. In Proc. of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP’16) [paper] [appendix] [data]
  • Improving Semantic Parsing via Answer Type Inference
    Semih Yavuz, Izzeddin Gur, Yu Su, Mudhakar Srivatsa, Xifeng Yan. In Proc. of the 2016 Conference on Empirical Methods in Natural Language Processing, oral (EMNLP’16) [paper]
  • A Fast Kernel for Attributed Graphs
    Yu Su, Fangqiu Han, Richard E. Harang, Xifeng Yan. In Proc. of the SIAM International Conference on Data Mining, 2016, oral (SDM’16) [paper] [appendix] [slides] [poster]
  • Table Cell Search for Question Answering
    Huan Sun, Hao Ma, Xiaodong He, Wen-Tau Yih, Yu Su, Xifeng Yan. In Proc. of the International World Wide Web Conference, 2016, oral (WWW’16) [paper]
  • Visual Graph Query Formulation and Exploration: A New Perspective on Information Retrieval at the Edge
    Sue Kase, Michelle Vanni, Joanne Knight, Yu Su, Xifeng Yan. In Proc. of SPIE 9851, Next-Generation Analyst IV, 2016 (SPIE Defense+Security’16)
  • Exploiting Relevance Feedback in Knowledge Graph Search
    Yu Su, Shengqi Yang, Huan Sun, Mudhakar Srivatsa, Sue Kase, Michelle Vanni, Xifeng Yan. In Proc. of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015, oral (KDD’15) [paper] [slides] [poster] [data]
  • On the Validity of Geosocial Mobility Traces
    Zengbin Zhang, Lin Zhou, Xiaohan Zhao, Gang Wang, Yu Su, Miriam Metzger, Haitao Zheng, and Ben Y. Zhao. In Proc. of the ACM Workshop on Hot Topics in Networks, 2013 (HotNets’13) [paper]

Awards & Honors

  • Outstanding Paper Award, ACL, 2023
  • Lumley Research Award, OSU, 2023
  • Outstanding Paper Award, COLING, 2022
  • Distinguished Assistant Professorship of Engineering Inclusive Excellence, OSU, 2022
  • Third-Place Honor, Inaugural Amazon Alexa Prize TaskBot Challenge, 2022
  • Work at Microsoft Deployed as the Official Conversational Interface for Outlook, 2020
  • Best of IEEE ICDM Selection, 2019
  • Outstanding Dissertation Award of Computer Science, UCSB, 2019
  • Best Distinguished Graduate Student Lecture of CS Summit, UCSB, 2018
  • Outstanding Freshman/Graduate Awards, Tsinghua University, 2008/2012

Teaching

Sponsers

  • We are grateful for NSF (awards 2118240, 2112606, 2137806), ARL, NIH, Amazon, Walmart, Cisco, Fujitsu, and OSU TDAI for supporting our research.

Contact

  • Email: %s@osu.edu % 'su.809'