101 citations · 261 across the 12 of their papers we have counts for
4 papers · 1 filter
Exploring Neural Models for Query-Focused Summarization
Jesse Vig, Alexander R. Fabbri, Wojciech Kryściński +2
Query-focused summarization (QFS) aims to produce summaries that answer particular questions of interest, enabling greater user control and personalization. While recently released…
CaPE: Contrastive Parameter Ensembling for Reducing Hallucination in Abstractive Summarization
Prafulla Kumar Choubey, Alexander R. Fabbri, Jesse Vig +3
Hallucination is a known issue for neural abstractive summarization models. Recent work suggests that the degree of hallucination may depend on errors in the training data. In this…
SummVis: Interactive Visual Analysis of Models, Data, and Evaluation for Text Summarization
Jesse Vig, Wojciech Kryściński, Karan Goel +1
Novel neural architectures, training strategies, and the availability of large-scale corpora haven been the driving force behind recent progress in abstractive text summarization.…
Robustness Gym: Unifying the NLP Evaluation Landscape
Karan Goel, Nazneen Rajani, Jesse Vig +6
Despite impressive performance on standard benchmarks, deep neural networks are often brittle when deployed in real-world systems. Consequently, recent research has focused on test…