17 citations · 29 across the 3 of their papers we have counts for
9 papers
On the Influence of Masking Policies in Intermediate Pre-training
Qinyuan Ye, Belinda Z. Li, Sinong Wang +5
Current NLP models are predominantly trained through a two-stage "pre-train then fine-tune" pipeline. Prior work has shown that inserting an intermediate pre-training stage, using…
CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP
Qinyuan Ye, Bill Yuchen Lin, Xiang Ren
Humans can learn a new language task efficiently with only few examples, by leveraging their knowledge obtained when learning prior tasks. In this paper, we explore whether and how…
Learning to Generate Task-Specific Adapters from Task Description
Qinyuan Ye, Xiang Ren
Pre-trained text-to-text transformers such as BART have achieved impressive performance across a range of NLP tasks. Recent study further shows that they can learn to generalize to…
Studying Strategically: Learning to Mask for Closed-book QA
Qinyuan Ye, Belinda Z. Li, Sinong Wang +5
Closed-book question-answering (QA) is a challenging task that requires a model to directly answer questions without access to external knowledge. It has been shown that directly f…
Semi-Automated Protocol Disambiguation and Code Generation
Jane Yen, Tamás Lévai, Qinyuan Ye +3
For decades, Internet protocols have been specified using natural language. Given the ambiguity inherent in such text, it is not surprising that protocol implementations have long…
Teaching Machine Comprehension with Compositional Explanations
Qinyuan Ye, Xiao Huang, Elizabeth Boschee +1
Advances in machine reading comprehension (MRC) rely heavily on the collection of large scale human-annotated examples in the form of (question, paragraph, answer) triples. In cont…