182 citations · 233 across the 36 of their papers we have counts for
43 papers
CROCODIL: Cross-Model Code Editing with LLMs
Linghan Zhong, Aditya Thimmaiah, Jayanth Srinivasa +2
Large language models (LLMs) have become ubiquitous tools for code generation and editing. However, development teams often use multiple LLM assistants. Different developers may pr…
VakyArth: Evaluating Pragmatic Competence in LLMs across Indic Languages
Usneek Singh, Poorvaja Veera Balaji Kumar, Parth Nanda +4
Real-world communication often requires pragmatic reasoning: interpreting meanings implied through context and cultural convention rather than stated literally. Existing pragmatic…
Predicting Program Exit Code with LLMs and Programming Language Semantics
Lara Marinov, Aditya Thimmaiah, Jayanth Srinivasa +2
Large language models (LLMs) have shown proficiency in various software engineering tasks, such as code generation and translation. However, a key limitation in their performance m…
Sarcasm Detection in a Disaster Context
Tiberiu Sosea, Junyi Jessy Li, Cornelia Caragea
During natural disasters, people often use social media platforms such as Twitter to ask for help, to provide information about the disaster situation, or to express contempt about…
Multilingual Code Co-Evolution Using Large Language Models
Jiyang Zhang, Pengyu Nie, Junyi Jessy Li +1
Many software projects implement APIs and algorithms in multiple programming languages. Maintaining such projects is tiresome, as developers have to ensure that any change (e.g., a…
Unsupervised Extractive Summarization of Emotion Triggers
Tiberiu Sosea, Hongli Zhan, Junyi Jessy Li +1
Understanding what leads to emotions during large-scale crises is important as it can provide groundings for expressed emotions and subsequently improve the understanding of ongoin…
Summarizing, Simplifying, and Synthesizing Medical Evidence Using GPT-3 (with Varying Success)
Chantal Shaib, Millicent L. Li, Sebastian Joseph +3
Large language models, particularly GPT-3, are able to produce high quality summaries of general domain news articles in few- and zero-shot settings. However, it is unclear if such…
Using Natural Language Explanations to Rescale Human Judgments
Manya Wadhwa, Jifan Chen, Junyi Jessy Li +1
The rise of large language models (LLMs) has brought a critical need for high-quality human-labeled data, particularly for processes like human feedback and evaluation. A common pr…
Multilingual Simplification of Medical Texts
Sebastian Joseph, Kathryn Kazanas, Keziah Reina +4
Automated text simplification aims to produce simple versions of complex texts. This task is especially useful in the medical domain, where the latest medical findings are typicall…
Elaborative Simplification as Implicit Questions Under Discussion
Yating Wu, William Sheffield, Kyle Mahowald +1
Automated text simplification, a technique useful for making text more accessible to people such as children and emergent bilinguals, is often thought of as a monolingual translati…
Learning Deep Semantics for Test Completion
Pengyu Nie, Rahul Banerjee, Junyi Jessy Li +2
Writing tests is a time-consuming yet essential task during software development. We propose to leverage recent advances in deep learning for text and code generation to assist dev…
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…
Discourse Comprehension: A Question Answering Framework to Represent Sentence Connections
Wei-Jen Ko, Cutter Dalton, Mark Simmons +3
While there has been substantial progress in text comprehension through simple factoid question answering, more holistic comprehension of a discourse still presents a major challen…
Impact of Evaluation Methodologies on Code Summarization
Pengyu Nie, Jiyang Zhang, Junyi Jessy Li +2
There has been a growing interest in developing machine learning (ML) models for code summarization tasks, e.g., comment generation and method naming. Despite substantial increase…
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…