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cs.CL2022
HaRiM: Evaluating Summary Quality with Hallucination Risk
Seonil Son, Junsoo Park, Jeong-in Hwang +3
One of the challenges of developing a summarization model arises from the difficulty in measuring the factual inconsistency of the generated text. In this study, we reinterpret the…
cs.CL2021★ 1 cited
May the Force Be with Your Copy Mechanism: Enhanced Supervised-Copy Method for Natural Language Generation
Sanghyuk Choi, Jeong-in Hwang, Hyungjong Noh +1
Recent neural sequence-to-sequence models with a copy mechanism have achieved remarkable progress in various text generation tasks. These models addressed out-of-vocabulary problem…