I am a Research Engineer at Google Research. I am interested in machine learning problems that involve correcting and evaluating model errors. Formerly, I have enjoyed internships at Philips Research, Amazon A9, and AI2. I obtained my PhD Degree from the School of Computing, University of Utah where I was very fortunate to be advised by Prof. Vivek Srikumar.
Selected Papers
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Learning Semantic Role Labeling from Compatible Label Sequences
Tao Li, Ghazaleh Kazeminejad, Susan W. Brown, Martha Palmer, Vivek Srikumar. arXiv 2023
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MUG: Interactive Multimodal Grounding on User Interfaces
Tao Li, Gang Li, Jingjie Zheng, Purple Wang, Yang Li. arXiv 2022
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PYLON: A PyTorch Framework for Learning with Constraints
Kareem Ahmed, Tao Li, Thy Ton, Quan Guo, Kai-Wei Chang, Parisa Kordjamshidi, Vivek Srikumar, Guy Van den Broeck, Sameer Singh. NeurIPS Demo 2021 & AAAI 2022
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OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings
Sunipa Dev, Tao Li, Jeff M Phillips, Vivek Srikumar. EMNLP 2021
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Automatic Entity State Annotation using the VerbNet Semantic Parser
Ghazaleh Kazeminejad, Martha Palmer, Tao Li, Vivek Srikumar. LAW-DMR at EMNLP 2021
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UnQovering Stereotyping Biases via Underspecified Questions
Tao Li, Tushar Khot, Daniel Khashabi, Ashish Sabharwal and Vivek Srikumar. EMNLP Findings 2020
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On Data Augmentation for Extreme Multi-label Classification
Danqing Zhang, Tao Li, Haiyang Zhang, Bing Yin. Arxiv 2020
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Structured Tuning for Semantic Role Labeling
Tao Li, Parth Anand Jawale, Martha Palmer and Vivek Srikumar. ACL 2020
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On Measuring and Mitigating Biased Inferences of Word Embeddings
Sunipa Dev, Tao Li, Jeff Philips and Vivek Srikumar. AAAI 2020 (oral presentation)
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A Logic-Driven Framework for Consistency of Neural Models
Tao Li, Vivek Gupta, Maitrey Mehta and Vivek Srikumar. EMNLP 2019
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Augmenting Neural Networks with First-order Logic
Tao Li and Vivek Srikumar. ACL 2019 (oral presentation)
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Visual Interrogation of Attention-Based Models for Natural Language Inference and Machine Comprehension
Shusen Liu, Tao Li, Zhimin Li, Vivek Srikumar, Valerio Pascucci and Peer-Timo Bremer. EMNLP 2018 Demo
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NLIZE: A Perturbation-Driven Visual Interrogation Tool for Analyzing and Interpreting Natural Language Inference Models
Shusen Liu, Zhimin Li, Tao Li, Vivek Srikumar, Valerio Pascucci and Peer-Timo Bremer. IEEE InfoVis 2018
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Exploiting Sentence Similarities for Better Alignments
Tao Li and Vivek Srikumar. EMNLP 2016 (oral presentation)
Thesis
- Neural Learning with Rules for Data Efficiency
Tao Li. University of Utah. 2022
Experience
- Jan 2022 - Present
- Research Engineer, Google Research
- Jan 2020 - May 2020
- Research Intern, AllenAI Aristo
- May 2019 - Aug 2019
- Applied Scientist Intern, Amazon A9
- May 2018 - Aug.2018
- Research Intern, Philips Research
Talks
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End-to-end Neural Learning with Rules
Talk at ML Seminar, UCLA
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Structured Tuning for Semantic Role Lableing
Talk at the Computational Semantics group, CU Boulder
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Augmenting Neural Networks with First-order Logic
Talk at Session: Machine Learning, ACL 2019, Florence, Italy
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Exploiting Sentence Similarities for Better Alignments
Talk at Session: Semantic Similarity, EMNLP 2016, Austin, Texas
Repositories
Check out my repos at:
Teaching
Services
- Routine reviewer for AAAI, AACL, ACL, ARR, CoNLL, EMNLP, ICLR, JMLR, NeurIPS, TKDE, and etc.