What's New

• [July 2023] Our paper on Synthetic Text Generation with Differential Privacy was listed as one of the Honorable Mentions in ACL'23!
• [May 2023] Check out our new preprints on Automatic Evaluation of Attribution by Large Language Models and Can ChatGPT Defend the Truth? Automatic Dialectical Evaluation Elicits LLMs’ Deficiencies in Reasoning
• [May 2023] I'm honored to receive two research awards: 2023 CSE Graduate Research Award and 2023 College of Engineering Exemplary Graduate Student Researcher
• [May 2023] Our paper on Synthetic Text Generation with Differential Privacy got accepted by ACL 2023 main conference
• [June 2022] Our OSU TacoBot team earned the third-place honor ($50K) in the first Alexa Prize TaskBot Challenge! 10 teams were selected worldwide out of 125 initiated applications to participate in the challenge in May 2021 and 5 teams were selected into finals in April 2022. We are the only US team in the top-3 performers! Check out our report here.
• [Mar 2022] - Two recent papers about question answering got accepted by ACL 2022 main conference: "Synthetic Question Value Estimation for Domain Adaptation of Question Answering" and "C-MORE: Pretraining to Answer Open-Domain Questions by Consulting Millions of References"
• [Mar 2022] - I will join Microsoft Research to explore NLP+Privacy for my 2022 summer internship!
• [Dec 2021] - Our paper "CliniQG4QA: Generating Diverse Questions for Domain Adaptation of Clinical Question Answering" has received the IEEE BIBM 2021 Best Paper Award!
• [Aug 2021] - Our short paper "COUGH: A Challenge Dataset and Models for COVID-19 FAQ Retrieval" has been accepted to EMNLP 2021 main conference!
• [May 2021] - Our team has been selected in the Alexa Prize TaskBot Challenge as one of 10 teams over 125 applications initiated from 15 countries! We will build a smart dialogue system to help users finish Cooking and DIY tasks.
• [May 2021] - Our long paper "Differential Privacy for Text Analytics via Natural Text Sanitization " has been accepted to ACL-IJCNLP 2021, Findings! We propose a privacy-preserving NLP pipeline (which consists of DP-based text sanitization mechanisms, sanitization-aware language model pretraining and finetuning)
• [Sept 2020] - Our paper "PHICON: Improving Generalization of Clinical Text De-identification Models via Data Augmentation" has been accepted to EMNLP'20 Clinical NLP Workshop!
• [July 2020] - Attended ACL 2020 and presented our Clinical Reading Comprehension work. Check out our slides and video
• [April 2020] - Our paper "Clinical Reading Comprehension: A Thorough Analysis of the emrQA Dataset" has been accepted to ACL 2020! We conduct a comprehensive study on the Clinical Reading Comprehension task based on the recently-released emrQA dataset!