I am a PhD student in the School of Computing, University of Utah. I am fortunate to be advised by Prof. Vivek Srikumar. My interests are on Natural Language Processing and Machine Learning. My current and prior projects cover logic+neural networks, structured prediction, bias probing and debiasing, machine comprehension, natural language inference, extreme multi-label classification, and visualizing/interpreting neural models.
Formerly, I enjoyed my internship at AllenAI Aristo team (Spring 2020), Amazon A9 (Summer 2019), and Philips Research (Summer 2018).
* Freshly baked bias probe paper accepted at Findings of EMNLP 2020.
* Freshly baked bias mitigation paper just got released.
Tao Li, Tushar Khot, Daniel Khashabi, Ashish Sabharwal and Vivek Srikumar. Findings of EMNLP 2020 (to appear)
Danqing Zhang, Tao Li, Haiyang Zhang, Bing Yin. (Arxiv 2020)
Sunipa Dev, Tao Li, Jeff M Phillips, Vivek Srikumar. (Arxiv 2020)
Tao Li, Parth Anand Jawale, Martha Palmer and Vivek Srikumar. ACL 2020
Sunipa Dev, Tao Li, Jeff Philips and Vivek Srikumar. AAAI 2020 (oral presentation)
Tao Li, Vivek Gupta, Maitrey Mehta and Vivek Srikumar. EMNLP 2019
Tao Li and Vivek Srikumar. ACL 2019 (oral presentation)
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
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
Tao Li and Vivek Srikumar. EMNLP 2016 (oral presentation)
Talk at Session: Semantic Similarity, EMNLP 2016, Austin, Texas
Talk at Session: Machine Learning, ACL 2019, Florence, Italy
Talk at the Computational Semantics group, CU Boulder
Check out my repos at:
- Reviewer for TKDE, AAAI, ACL, EMNLP, CoNLL, and AACL.