136 citations · 563 across the 31 of their papers we have counts for
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cs.CL2020★ 5 cited
Text Generation by Learning from Demonstrations
Richard Yuanzhe Pang, He He
Current approaches to text generation largely rely on autoregressive models and maximum likelihood estimation. This paradigm leads to (i) diverse but low-quality samples due to mis…
cs.CL2020★ 9 cited
An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language Models
Lifu Tu, Garima Lalwani, Spandana Gella +1
Recent work has shown that pre-trained language models such as BERT improve robustness to spurious correlations in the dataset. Intrigued by these results, we find that the key to…
cs.CL2020★ 103 cited
FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization
Esin Durmus, He He, Mona Diab
Neural abstractive summarization models are prone to generate content inconsistent with the source document, i.e. unfaithful. Existing automatic metrics do not capture such mistake…