65 citations · 96 across the 12 of their papers we have counts for
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cs.CL2022
Improving the Robustness of Summarization Models by Detecting and Removing Input Noise
Kundan Krishna, Yao Zhao, Jie Ren +4
The evaluation of abstractive summarization models typically uses test data that is identically distributed as training data. In real-world practice, documents to be summarized may…
cs.CL2022★ 15 cited
Prompting PaLM for Translation: Assessing Strategies and Performance
David Vilar, Markus Freitag, Colin Cherry +3
Large language models (LLMs) that have been trained on multilingual but not parallel text exhibit a remarkable ability to translate between languages. We probe this ability in an i…
cs.CL2022★ 12 cited
Out-of-Distribution Detection and Selective Generation for Conditional Language Models
Jie Ren, Jiaming Luo, Yao Zhao +4
Machine learning algorithms typically assume independent and identically distributed samples in training and at test time. Much work has shown that high-performing ML classifiers c…