activity
20152021
most citedQMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization

27 citations · 28 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL202127 cited

QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization

Ming Zhong, Da Yin, Tao Yu +8

Meetings are a key component of human collaboration. As increasing numbers of meetings are recorded and transcribed, meeting summaries have become essential to remind those who may…

cs.CL2020

Artemis: A Novel Annotation Methodology for Indicative Single Document Summarization

Rahul Jha, Keping Bi, Yang Li +4

We describe Artemis (Annotation methodology for Rich, Tractable, Extractive, Multi-domain, Indicative Summarization), a novel hierarchical annotation process that produces indicati…

cs.CL2020

AREDSUM: Adaptive Redundancy-Aware Iterative Sentence Ranking for Extractive Document Summarization

Keping Bi, Rahul Jha, W. Bruce Croft +1

Redundancy-aware extractive summarization systems score the redundancy of the sentences to be included in a summary either jointly with their salience information or separately as…

cs.CL2018

Zero-Shot Adaptive Transfer for Conversational Language Understanding

Sungjin Lee, Rahul Jha

Conversational agents such as Alexa and Google Assistant constantly need to increase their language understanding capabilities by adding new domains. A massive amount of labeled da…

cs.CL20151 cited

Humor in Collective Discourse: Unsupervised Funniness Detection in the New Yorker Cartoon Caption Contest

Dragomir Radev, Amanda Stent, Joel Tetreault +8

The New Yorker publishes a weekly captionless cartoon. More than 5,000 readers submit captions for it. The editors select three of them and ask the readers to pick the funniest one…