most citedExploring the Use of Large Language Models for Reference-Free Text Quality Evaluation: An Empirical Study

21 citations · 28 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2024★ 1 cited

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…

cs.CV2023

EgoPlan-Bench: Benchmarking Multimodal Large Language Models for Human-Level Planning

Yi Chen, Yuying Ge, Yixiao Ge +6

The pursuit of artificial general intelligence (AGI) has been accelerated by Multimodal Large Language Models (MLLMs), which exhibit superior reasoning, generalization capabilities…

cs.AI2023★ 3 cited

TPE: Towards Better Compositional Reasoning over Conceptual Tools with Multi-persona Collaboration

Hongru Wang, Huimin Wang, Lingzhi Wang +6

Large language models (LLMs) have demonstrated exceptional performance in planning the use of various functional tools, such as calculators and retrievers, particularly in question…

cs.CL2023

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…

cs.CL2023★ 3 cited

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…

cs.CL2023★ 21 cited

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…