Papers by Akshay Paruchuri

2 papers
What Are the Odds? Language Models Are Capable of Probabilistic Reasoning (2024.emnlp-main)

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Challenge: Language models (LMs) are capable of remarkably complex linguistic tasks, but numerical reasoning is an area in which they struggle.
Approach: They evaluate the probabilistic reasoning capabilities of language models using idealized and real-world statistical distributions.
Outcome: The proposed model can make inferences about distributions, even if assumptions are incorrect or misspecified.
“What’s Up, Doc?”: Analyzing How Users Seek Health Information in Large-Scale Conversational AI Datasets (2025.findings-emnlp)

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Challenge: a growing number of people are seeking healthcare information from large language models via chatbots, yet the nature and inherent risks of these interactions remain unexplored.
Approach: They use a curated dataset of 11K real-world conversations composed of 25K user messages to analyze user interactions across 21 health specialties.
Outcome: The proposed dataset consists of 11K real-world conversations composed of 25K user messages.

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