3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.CL2022★ 3 cited
Correcting Diverse Factual Errors in Abstractive Summarization via Post-Editing and Language Model Infilling
Vidhisha Balachandran, Hannaneh Hajishirzi, William W. Cohen +1
Abstractive summarization models often generate inconsistent summaries containing factual errors or hallucinated content. Recent works focus on correcting factual errors in generat…
cs.CL2021
Multilingual Fact Linking
Keshav Kolluru, Martin Rezk, Pat Verga +2
Knowledge-intensive NLP tasks can benefit from linking natural language text with facts from a Knowledge Graph (KG). Although facts themselves are language-agnostic, the fact label…