32 citations · 80 across the 16 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…
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…