182 citations · 233 across the 36 of their papers we have counts for
9 papers · 1 filter
Using Developer Discussions to Guide Fixing Bugs in Software
Sheena Panthaplackel, Milos Gligoric, Junyi Jessy Li +1
Automatically fixing software bugs is a challenging task. While recent work showed that natural language context is useful in guiding bug-fixing models, the approach required promp…
Discourse Analysis via Questions and Answers: Parsing Dependency Structures of Questions Under Discussion
Wei-Jen Ko, Yating Wu, Cutter Dalton +3
Automatic discourse processing is bottlenecked by data: current discourse formalisms pose highly demanding annotation tasks involving large taxonomies of discourse relations, makin…
CoditT5: Pretraining for Source Code and Natural Language Editing
Jiyang Zhang, Sheena Panthaplackel, Pengyu Nie +2
Pretrained language models have been shown to be effective in many software-related generation tasks; however, they are not well-suited for editing tasks as they are not designed t…
Text Simplification of College Admissions Instructions: A Professionally Simplified and Verified Corpus
Zachary W. Taylor, Maximus H. Chu, Junyi Jessy Li
Access to higher education is critical for minority populations and emergent bilingual students. However, the language used by higher education institutions to communicate with pro…
News Summarization and Evaluation in the Era of GPT-3
Tanya Goyal, Junyi Jessy Li, Greg Durrett
The recent success of prompting large language models like GPT-3 has led to a paradigm shift in NLP research. In this paper, we study its impact on text summarization, focusing on…
longhorns at DADC 2022: How many linguists does it take to fool a Question Answering model? A systematic approach to adversarial attacks
Venelin Kovatchev, Trina Chatterjee, Venkata S Govindarajan +9
Developing methods to adversarially challenge NLP systems is a promising avenue for improving both model performance and interpretability. Here, we describe the approach of the tea…
SNaC: Coherence Error Detection for Narrative Summarization
Tanya Goyal, Junyi Jessy Li, Greg Durrett
Progress in summarizing long texts is inhibited by the lack of appropriate evaluation frameworks. When a long summary must be produced to appropriately cover the facets of that tex…
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…