most citedMoZIP: A Multilingual Benchmark to Evaluate Large Language Models in Intellectual Property

3 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2025

STORYTELLER: An Enhanced Plot-Planning Framework for Coherent and Cohesive Story Generation

Jiaming Li, Yukun Chen, Ziqiang Liu +10

Stories are central to human culture, serving to share ideas, preserve traditions, and foster connections. Automatic story generation, a key advancement in artificial intelligence…

cs.CL2024

APTNESS: Incorporating Appraisal Theory and Emotion Support Strategies for Empathetic Response Generation

Yuxuan Hu, Minghuan Tan, Chenwei Zhang +5

Empathetic response generation is designed to comprehend the emotions of others and select the most appropriate strategies to assist them in resolving emotional challenges. Empathy…

cs.CL2024

CollectiveSFT: Scaling Large Language Models for Chinese Medical Benchmark with Collective Instructions in Healthcare

Jingwei Zhu, Minghuan Tan, Min Yang +2

The rapid progress in Large Language Models (LLMs) has prompted the creation of numerous benchmarks to evaluate their capabilities.This study focuses on the Comprehensive Medical B…

cs.CL20241 cited

CPsyCoun: A Report-based Multi-turn Dialogue Reconstruction and Evaluation Framework for Chinese Psychological Counseling

Chenhao Zhang, Renhao Li, Minghuan Tan +7

Using large language models (LLMs) to assist psychological counseling is a significant but challenging task at present. Attempts have been made on improving empathetic conversation…

cs.CL2024

NUMCoT: Numerals and Units of Measurement in Chain-of-Thought Reasoning using Large Language Models

Ancheng Xu, Minghuan Tan, Lei Wang +2

Numeral systems and units of measurement are two conjoined topics in activities of human beings and have mutual effects with the languages expressing them. Currently, the evaluatio…

cs.CL20243 cited

MoZIP: A Multilingual Benchmark to Evaluate Large Language Models in Intellectual Property

Shiwen Ni, Minghuan Tan, Yuelin Bai +9

Large language models (LLMs) have demonstrated impressive performance in various natural language processing (NLP) tasks. However, there is limited understanding of how well LLMs p…