activity
20172022
most citedImproving Gender Translation Accuracy with Filtered Self-Training

11 citations · 36 across the 7 of their papers we have counts for

collaborators
Showing cs.CLShow all

9 papers · 1 filter

cs.CL2025

Turning Conversations into Workflows: A Framework to Extract and Evaluate Dialog Workflows for Service AI Agents

Prafulla Kumar Choubey, Xiangyu Peng, Shilpa Bhagavath +3

Automated service agents require well-structured workflows to provide consistent and accurate responses to customer queries. However, these workflows are often undocumented, and th…

cs.CL20221 cited

Improving Factual Consistency in Summarization with Compression-Based Post-Editing

Alexander R. Fabbri, Prafulla Kumar Choubey, Jesse Vig +2

State-of-the-art summarization models still struggle to be factually consistent with the input text. A model-agnostic way to address this problem is post-editing the generated summ…

cs.CL2022

Conformal Predictor for Improving Zero-shot Text Classification Efficiency

Prafulla Kumar Choubey, Yu Bai, Chien-Sheng Wu +2

Pre-trained language models (PLMs) have been shown effective for zero-shot (0shot) text classification. 0shot models based on natural language inference (NLI) and next sentence pre…

cs.CL20222 cited

Modeling Document-level Temporal Structures for Building Temporal Dependency Graphs

Prafulla Kumar Choubey, Ruihong Huang

We propose to leverage news discourse profiling to model document-level temporal structures for building temporal dependency graphs. Our key observation is that the functional role…

cs.CL202111 cited

Improving Gender Translation Accuracy with Filtered Self-Training

Prafulla Kumar Choubey, Anna Currey, Prashant Mathur +1

Targeted evaluations have found that machine translation systems often output incorrect gender, even when the gender is clear from context. Furthermore, these incorrectly gendered…

cs.CL2019

In Plain Sight: Media Bias Through the Lens of Factual Reporting

Lisa Fan, Marshall White, Eva Sharma +4

The increasing prevalence of political bias in news media calls for greater public awareness of it, as well as robust methods for its detection. While prior work in NLP has primari…