Lin, Chenghua

Compressing Context to Enhance Inference Efficiency of Large Language Models

Li, Y., Dong, B., Guerin, F., & Lin, C. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 253

Compressing Context to Enhance Inference Efficiency of Large Language Models

Li, Y., Dong, B., Lin, C., & Guerin, F. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 88

An Open-Source Data Contamination Report for Large Language Models

Li, Y., Guo, Y., Guerin, F., & Lin, C. (2024) · Findings of the Association for Computational Linguistics: EMNLP 2024

Topic ModelingNatural Language Processing Techniques

Cited by 19

LLMs as Narcissistic Evaluators: When Ego Inflates Evaluation Scores

Liu, Y., Moosavi, N. S., & Lin, C. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 13

LLMs as Narcissistic Evaluators: When Ego Inflates Evaluation Scores

Liu, Y., Moosavi, N., & Lin, C. (2024) · Findings of the Association for Computational Linguistics ACL 2024

Topic ModelingNatural Language Processing Techniques

Cited by 12

On the Rigour of Scientific Writing: Criteria, Analysis, and Insights

James, J., Xiao, C., Li, Y., & Lin, C. (2024) · Findings of the Association for Computational Linguistics: EMNLP 2024

Academic Writing and Publishingscientometrics and bibliometrics research

Cited by 2

Scaling Latent Reasoning via Looped Language Models

Zhu, R.-J., Wang, Z., Hua, K., Zhang, T., Li, Z., Que, H., Wei, B., Wen, Z., Yin, F., Xing, H., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

JudgeMoE: Distributional Aggregation for LLM-as-a-Judge

Liu, Y., James, J., Wang, Y., Zhao, K., Xiao, C., & Lin, C. (2026) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0