4 citations · 6 across the 13 of their papers we have counts for
13 papers
Hard Rules, Soft Preferences: Bridging Reasoning, Learning, and Optimization for Personalized Packing Checklist Generation
Himel Dev, Madhusudan Basak, Tanmoy Sen +2
Packing for air travel is recurring and error-prone: the checklist must be personal and context-aware, yet feasible under safety rules, item dependencies, and luggage limits. Exist…
From Feasibility to Desirability: Plan, Learn, Adapt (PLA) Framework for Personalized On-Device Itinerary Generation
Himel Dev, Tanmoy Sen, Madhusudan Basak +1
Generating personalized trip itineraries is a complex planning task and involves a tension between hard combinatorial feasibility and soft latent desirability. Classical optimizati…
Socially Constructed Treatment Plans: Analyzing Online Peer Interactions to Understand How Patients Navigate Complex Medical Conditions
Madhusudan Basak, Omar Sharif, Jessica Hulsey +4
When faced with complex and uncertain medical conditions (e.g., cancer, mental health conditions, recovery from substance dependency), millions of patients seek online peer support…
REGen: A Reliable Evaluation Framework for Generative Event Argument Extraction
Omar Sharif, Joseph Gatto, Madhusudan Basak +1
Event argument extraction identifies arguments for predefined event roles in text. Existing work evaluates this task with exact match (EM), where predicted arguments must align exa…
Explicit, Implicit, and Scattered: Revisiting Event Extraction to Capture Complex Arguments
Omar Sharif, Joseph Gatto, Madhusudan Basak +1
Prior works formulate the extraction of event-specific arguments as a span extraction problem, where event arguments are explicit -- i.e. assumed to be contiguous spans of text in…
A Thematic Framework for Analyzing Large-scale Self-reported Social Media Data on Opioid Use Disorder Treatment Using Buprenorphine Product
Madhusudan Basak, Omar Sharif, Sarah E. Lord +7
Background: One of the key FDA-approved medications for Opioid Use Disorder (OUD) is buprenorphine. Despite its popularity, individuals often report various information needs regar…
Do LLMs Find Human Answers To Fact-Driven Questions Perplexing? A Case Study on Reddit
Parker Seegmiller, Joseph Gatto, Omar Sharif +2
Large language models (LLMs) have been shown to be proficient in correctly answering questions in the context of online discourse. However, the study of using LLMs to model human-l…
Scope of Large Language Models for Mining Emerging Opinions in Online Health Discourse
Joseph Gatto, Madhusudan Basak, Yash Srivastava +2
In this paper, we develop an LLM-powered framework for the curation and evaluation of emerging opinion mining in online health communities. We formulate emerging opinion mining as…
Characterizing Information Seeking Events in Health-Related Social Discourse
Omar Sharif, Madhusudan Basak, Tanzia Parvin +5
Social media sites have become a popular platform for individuals to seek and share health information. Despite the progress in natural language processing for social media mining,…
The Scope of In-Context Learning for the Extraction of Medical Temporal Constraints
Parker Seegmiller, Joseph Gatto, Madhusudan Basak +4
Medications often impose temporal constraints on everyday patient activity. Violations of such medical temporal constraints (MTCs) lead to a lack of treatment adherence, in additio…
Theme-driven Keyphrase Extraction to Analyze Social Media Discourse
William Romano, Omar Sharif, Madhusudan Basak +2
Social media platforms are vital resources for sharing self-reported health experiences, offering rich data on various health topics. Despite advancements in Natural Language Proce…
Scope of Pre-trained Language Models for Detecting Conflicting Health Information
Joseph Gatto, Madhusudan Basak, Sarah M. Preum
An increasing number of people now rely on online platforms to meet their health information needs. Thus identifying inconsistent or conflicting textual health information has beco…
Not Low-Resource Anymore: Aligner Ensembling, Batch Filtering, and New Datasets for Bengali-English Machine Translation
Tahmid Hasan, Abhik Bhattacharjee, Kazi Samin +4
Despite being the seventh most widely spoken language in the world, Bengali has received much less attention in machine translation literature due to being low in resources. Most p…