21 citations · 25 across the 5 of their papers we have counts for
5 papers
Zero-shot Large Language Models for Automatic Readability Assessment
Riley Grossman, Yi Chen
Unsupervised automatic readability assessment (ARA) methods have important practical and research applications (e.g., ensuring medical or educational materials are suitable for the…
Role Prompting Guided Domain Adaptation with General Capability Preserve for Large Language Models
Rui Wang, Fei Mi, Yi Chen +5
The growing interest in Large Language Models (LLMs) for specialized applications has revealed a significant challenge: when tailored to specific domains, LLMs tend to experience c…
A Benchmark for Text Expansion: Datasets, Metrics, and Baselines
Yi Chen, Haiyun Jiang, Wei Bi +4
This work presents a new task of Text Expansion (TE), which aims to insert fine-grained modifiers into proper locations of the plain text to concretize or vivify human writings. Di…
Enhancing Large Language Models Against Inductive Instructions with Dual-critique Prompting
Rui Wang, Hongru Wang, Fei Mi +4
Numerous works are proposed to align large language models (LLMs) with human intents to better fulfill instructions, ensuring they are trustful and helpful. Nevertheless, some huma…
Exploring the Use of Large Language Models for Reference-Free Text Quality Evaluation: An Empirical Study
Yi Chen, Rui Wang, Haiyun Jiang +2
Evaluating the quality of generated text is a challenging task in NLP, due to the inherent complexity and diversity of text. Recently, large language models (LLMs) have garnered si…