4 citations · 11 across the 12 of their papers we have counts for
13 papers
Language Models Encode the Contextual Truth of Propositions
Rupak Sarkar, Pritika Ramu, Rachel Rudinger
Prior work has shown that LLMs encode the truth of factual propositions along linear directions in activation space. It's unclear how these representations extend to contextual tru…
Sycophancy Undermines Epistemic Vigilance in Cooperative Vision-Language Tasks
Rupak Sarkar, Neha Srikanth, Saloni Gupta +3
To maintain common ground in cooperative conversation, humans iteratively update their beliefs as conversation participants share new information; participants who are epistemicall…
Measuring Scalar Constructs in Social Science with LLMs
Hauke Licht, Rupak Sarkar, Patrick Y. Wu +4
Many constructs that characterize language, like its complexity or emotionality, have a naturally continuous semantic structure; a public speech is not just "simple" or "complex,"…
Conversational User-AI Intervention: A Study on Prompt Rewriting for Improved LLM Response Generation
Rupak Sarkar, Bahareh Sarrafzadeh, Nirupama Chandrasekaran +4
Human-LLM conversations are increasingly becoming more pervasive in peoples' professional and personal lives, yet many users still struggle to elicit helpful responses from LLM Cha…
Understanding Common Ground Misalignment in Goal-Oriented Dialog: A Case-Study with Ubuntu Chat Logs
Rupak Sarkar, Neha Srikanth, Taylor Hudson +3
While it is commonly accepted that maintaining common ground plays a role in conversational success, little prior research exists connecting conversational grounding to success in…
Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering
Neha Srikanth, Rupak Sarkar, Heran Mane +4
Questions posed by information-seeking users often contain implicit false or potentially harmful assumptions. In a high-risk domain such as maternal and infant health, a question-a…
Natural Language Decompositions of Implicit Content Enable Better Text Representations
Alexander Hoyle, Rupak Sarkar, Pranav Goel +1
When people interpret text, they rely on inferences that go beyond the observed language itself. Inspired by this observation, we introduce a method for the analysis of text that t…
Are Neural Topic Models Broken?
Alexander Hoyle, Pranav Goel, Rupak Sarkar +1
Recently, the relationship between automated and human evaluation of topic models has been called into question. Method developers have staked the efficacy of new topic model varia…
Empathy and Hope: Resource Transfer to Model Inter-country Social Media Dynamics
Clay H. Yoo, Shriphani Palakodety, Rupak Sarkar +1
The ongoing COVID-19 pandemic resulted in significant ramifications for international relations ranging from travel restrictions, global ceasefires, and international vaccine produ…
Fringe News Networks: Dynamics of US News Viewership following the 2020 Presidential Election
Ashiqur R. KhudaBukhsh, Rupak Sarkar, Mark S. Kamlet +1
The growing political polarization of the American electorate over the last several decades has been widely studied and documented. During the administration of President Donald Tr…
Are Chess Discussions Racist? An Adversarial Hate Speech Data Set
Rupak Sarkar, Ashiqur R. KhudaBukhsh
On June 28, 2020, while presenting a chess podcast on Grandmaster Hikaru Nakamura, Antonio Radić's YouTube handle got blocked because it contained "harmful and dangerous" content.…
We Don't Speak the Same Language: Interpreting Polarization through Machine Translation
Ashiqur R. KhudaBukhsh, Rupak Sarkar, Mark S. Kamlet +1
Polarization among US political parties, media and elites is a widely studied topic. Prominent lines of prior research across multiple disciplines have observed and analyzed growin…
Social Media Attributions in the Context of Water Crisis
Rupak Sarkar, Hirak Sarkar, Sayantan Mahinder +1
Attribution of natural disasters/collective misfortune is a widely-studied political science problem. However, such studies are typically survey-centric or rely on a handful of exp…