activity
20182026
most citedImproving Broad-Coverage Medical Entity Linking with Semantic Type Prediction and Large-Scale Datasets

32 citations · 80 across the 16 of their papers we have counts for

collaborators

24 papers

cs.AI2026

Lost in the Request: How Communication Variation Disrupts Retrieval and Action in Email Agents

Feng Chen, Ritam Dutt, Atnaz Taheri +1

An email assistant should not complete less work simply because a user phrases the same request differently. Yet most benchmarks test each task with only one canonical request, lea…

cs.CL2026

Evaluating Multi-Dimensional Generalization of Large Language Models in Temporal Extraction Tasks

Fahmid Shahriar Iqbal, Ritam Dutt, Soumitra Das +2

Time and event expression extraction are fundamental temporal reasoning tasks, but the problem remains difficult due to annotation ambiguity, domain sensitivity, and unstable model…

cs.AI2026

EmailBench: A Benchmark for Evaluating LLM Agents on Enterprise Email and Productivity Tasks

Mukul Singh, Mansi Uniyal, Devin Devlin +5

Enterprise email agents must combine information retrieval, structured state changes, temporal reasoning, and multi-step coordination. Recent agent benchmarks include productivity…

cs.AI2026

Position: Evaluations of AI Moral Reasoning Still Miss Half of the Picture

Aidan Kierans, Ritam Dutt, Kaley Rittichier +2

Recent work on evaluating the moral competence of large language models (LLMs) has focused primarily on what we call the moral value problem, i.e., whether model outputs align with…

cs.AI2025

-CoD: Understanding Text-Graph Complementarity in Relational Reasoning via Knowledge Co-Distillation

Zhen Wu, Ritam Dutt, Luke M. Breitfeller +3

Relational reasoning lies at the core of many NLP tasks, drawing on complementary signals from text and graphs. While prior research has investigated how to leverage this dual comp…

cs.IR2024

Chemical Reaction Extraction from Long Patent Documents

Aishwarya Jadhav, Ritam Dutt

The task of searching through patent documents is crucial for chemical patent recommendation and retrieval. This can be enhanced by creating a patent knowledge base (ChemPatKB) to…