7 citations · 16 across the 9 of their papers we have counts for
21 papers
Evaluating Factuality in Text Simplification
Ashwin Devaraj, William Sheffield, Byron C. Wallace +1
Automated simplification models aim to make input texts more readable. Such methods have the potential to make complex information accessible to a wider audience, e.g., providing a…
How Do We Answer Complex Questions: Discourse Structure of Long-form Answers
Fangyuan Xu, Junyi Jessy Li, Eunsol Choi
Long-form answers, consisting of multiple sentences, can provide nuanced and comprehensive answers to a broader set of questions. To better understand this complex and understudied…
Roosterize: Suggesting Lemma Names for Coq Verification Projects Using Deep Learning
Pengyu Nie, Karl Palmskog, Junyi Jessy Li +1
Naming conventions are an important concern in large verification projects using proof assistants, such as Coq. In particular, lemma names are used by proof engineers to effectivel…
My Teacher Thinks The World Is Flat! Interpreting Automatic Essay Scoring Mechanism
Swapnil Parekh, Yaman Kumar Singla, Changyou Chen +2
Significant progress has been made in deep-learning based Automatic Essay Scoring (AES) systems in the past two decades. However, little research has been put to understand and int…
Inquisitive Question Generation for High Level Text Comprehension
Wei-Jen Ko, Te-Yuan Chen, Yiyan Huang +2
Inquisitive probing questions come naturally to humans in a variety of settings, but is a challenging task for automatic systems. One natural type of question to ask tries to fill…
Deep Just-In-Time Inconsistency Detection Between Comments and Source Code
Sheena Panthaplackel, Junyi Jessy Li, Milos Gligoric +1
Natural language comments convey key aspects of source code such as implementation, usage, and pre- and post-conditions. Failure to update comments accordingly when the correspondi…