25 citations · 39 across the 12 of their papers we have counts for
11 papers
Intention-Adaptive LLM Fine-Tuning for Text Revision Generation
Zhexiong Liu, Diane Litman
Large Language Models (LLMs) have achieved impressive capabilities in various context-based text generation tasks, such as summarization and reasoning; however, their applications…
Efficient Layer-wise LLM Fine-tuning for Revision Intention Prediction
Zhexiong Liu, Diane Litman
Large Language Models (LLMs) have shown extraordinary success across various text generation tasks; however, their potential for simple yet essential text classification remains un…
eRevise+RF: A Writing Evaluation System for Assessing Student Essay Revisions and Providing Formative Feedback
Zhexiong Liu, Diane Litman, Elaine Wang +4
The ability to revise essays in response to feedback is important for students' writing success. An automated writing evaluation (AWE) system that supports students in revising the…
LogicPrpBank: A Corpus for Logical Implication and Equivalence
Zhexiong Liu, Jing Zhang, Jiaying Lu +2
Logic reasoning has been critically needed in problem-solving and decision-making. Although Language Models (LMs) have demonstrated capabilities of handling multiple reasoning task…
Overview of ImageArg-2023: The First Shared Task in Multimodal Argument Mining
Zhexiong Liu, Mohamed Elaraby, Yang Zhong +1
This paper presents an overview of the ImageArg shared task, the first multimodal Argument Mining shared task co-located with the 10th Workshop on Argument Mining at EMNLP 2023. Th…
Ticket-BERT: Labeling Incident Management Tickets with Language Models
Zhexiong Liu, Cris Benge, Siduo Jiang
An essential aspect of prioritizing incident tickets for resolution is efficiently labeling tickets with fine-grained categories. However, ticket data is often complex and poses se…
Predicting the Quality of Revisions in Argumentative Writing
Zhexiong Liu, Diane Litman, Elaine Wang +2
The ability to revise in response to feedback is critical to students' writing success. In the case of argument writing in specific, identifying whether an argument revision (AR) i…
Task-Adaptive Meta-Learning Framework for Advancing Spatial Generalizability
Zhexiong Liu, Licheng Liu, Yiqun Xie +2
Spatio-temporal machine learning is critically needed for a variety of societal applications, such as agricultural monitoring, hydrological forecast, and traffic management. These…
ImageArg: A Multi-modal Tweet Dataset for Image Persuasiveness Mining
Zhexiong Liu, Meiqi Guo, Yue Dai +1
The growing interest in developing corpora of persuasive texts has promoted applications in automated systems, e.g., debating and essay scoring systems; however, there is little pr…
Anatomy-Guided Weakly-Supervised Abnormality Localization in Chest X-rays
Ke Yu, Shantanu Ghosh, Zhexiong Liu +2
Creating a large-scale dataset of abnormality annotation on medical images is a labor-intensive and costly task. Leveraging weak supervision from readily available data such as rad…
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…