Rupak Sarkar
I am a fourth year PhD. student at the University of Maryland,
College Park in the department of Computer Science in the amazing
CLIP lab
with Prof. Philip Resnik.
My primary area of research is computational pragmatics, with a special interest in the role of
implicit content. Current NLP methods focus (too) heavily on the surface form of text, but a large part
of the communicative intent of humans is implicit.
I am interested in understanding how to model and interpret these implicit aspects of human communication, with
specific applications in modeling common ground in conversations, and understanding the role of implicit content
in political polarization.
Prior to my PhD, I served as a Course Research Engineer in the course 11-865/11-665
Tracking Political Sentiments Using Machine Learning
(Fall 2020) at CMU with instructors Dr. Ashiqur Khudabukhsh,
Prof. Tom Mitchell and
Prof. Mark Kamlet.
My previous research mentor is Prof. Ashiqur R KhudaBukhsh.
Mailto : rupak@umd.edu, rupaksarkar.cs@gmail.com
More Info : [CV], [Google Scholar]
Recent updates
- 2025: Our paper on scoring user attitudes on a scale using pairwise comparisons was accepted at NAACL 2025 Findings! We propose an alternative to stance detection where instead of categorical pro/anti/neutral labels, we can score user attitudes on a scale. More details coming soon!
- 2024: I spent a wonderful summer at Microsoft Research as a Research Intern working on making conversational AI respond better to a broad range of user prompts. (Paper in Progress)
Selected Publications
- PairScale: Analyzing Attitude Change in Online Communities Rupak Sarkar, Patrick Y Wu, Kristina Miler, Alexander Hoyle, Philip Resnik NAACL 2025 Findings [pdf]
- Understanding Common Ground Misalignment in Goal-Oriented Dialog: A Case-Study with Ubuntu Chat Logs Rupak Sarkar, Neha Srikanth, Taylor Hudson, Claire Bonial, Rachel Rudinger, Philip Resnik (Under Review at ARR)
- Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering Neha Srikanth*, Rupak Sarkar*, Rachel Rudinger, Jordan Boyd-Graber NAACL 2024 Main [pdf]
- Natural Language Decompositions of Implicit Content Enable Better Text Representations. Alexander Hoyle*, Rupak Sarkar*, Pranav Goel, Philip Resnik EMNLP 2023 Main [pdf]
- We Don't Speak the Same Language: Interpreting Polarization Through Machine Translation. A. R. KhudaBukhsh*, Rupak Sarkar*, Mark S. Kamlet, Tom M. Mitchell
(AAAI) 2021 [slides]
- Are chess discussions racist? An Adversarial Hate Speech Data Set (Student Abstract). Rupak Sarkar, A. R. KhudaBukhsh
35th AAAI Conference on Artificial Intelligence AAAI 2021 Best Student Abstract [poster]
- Social Media Attributions in the Context of Water Crisis. Rupak Sarkar*, Sayantan Mahinder*, Hirak Sarkar, A. R. KhudaBukhsh
Empirical Methods in Natural Language Processing (EMNLP), 2020
- The Non-native Speaker Aspect: Indian English in Social Media. Rupak Sarkar, Sayantan Mahinder, A. R. KhudaBukhsh
6th Workshop on Noisy User-generated Text (W-NUT), EMNLP 2020 [slides]
Selected Media Coverage