Lin, Chin-Yew
Microsoft (United States)
10 papers on CoChatORCID 0000-0002-0798-6365
Most cited papers
- Verified
Automatic evaluation of machine translation quality using longest common subsequence and skip-bigram statistics
Lin, C.-Y., & Och, F. J. (2004) · Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics - ACL '04
Natural Language Processing TechniquesTranslation Studies and Practices
Cited by 737
- Verified
LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression
Jiang, H., Wu, Q., Luo, X., Li, D., Lin, C.-Y., Yang, Y., & Qiu, L. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Topic ModelingNatural Language Processing Techniques
Cited by 400
- Verified
LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models
Jiang, H., Wu, Q., Lin, C.-Y., Yang, Y., & Qiu, L. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Topic ModelingNatural Language Processing Techniques
Cited by 168
- Verified
LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models
Jiang, H., Wu, Q., Lin, C.-Y., Yang, Y., & Qiu, L. (2023) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 168
- Verified
A Simple Recipe towards Reducing Hallucination in Neural Surface Realisation
Nie, F., Yao, J.-G., Wang, J., Pan, R., & Lin, C.-Y. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Natural Language Processing TechniquesTopic Modeling
Cited by 68
- Verified
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
Pan, Z., Wu, Q., Jiang, H., Xia, M., Luo, X., Zhang, J., Lin, Q., Rühle, V., Yang, Y., Lin, C.-Y., et al. (2024) · Findings of the Association for Computational Linguistics: ACL 2024
Topic ModelingNatural Language Processing Techniques
Cited by 58
- Verified
MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention
Jiang, H., Li, Y., Zhang, C., Wu, Q., Luo, X., Ahn, S., Han, Z., Abdi, A. H., Li, D., Lin, C.-Y., et al. (2024) · arXiv
Topic ModelingAdvanced Neural Network Applications
Cited by 36
- Verified
LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression
Jiang, H., Wu, Q., Luo, X., Li, D., Lin, C.-Y., Yang, Y., & Qiu, L. (2023) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 12
- Verified
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
Pan, Z., Wu, Q., Jiang, H., Xia, M., Luo, X., Zhang, J., Lin, Q., Rühle, V., Yang, Y., Lin, C.-Y., et al. (2024) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 2
- Verified
On Memory Construction and Retrieval for Personalized Conversational Agents
Pan, Z., Wu, Q., Jiang, H., Luo, X., Cheng, H., Li, D., Yang, Y., Lin, C.-Y., Zhao, H. V., Qiu, L., et al. (2025) · arXiv
Speech and dialogue systemsAI in Service Interactions
Cited by 2
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