| Annollm: Making large language models to be better crowdsourced annotators X He, Z Lin, Y Gong, A Jin, H Zhang, C Lin, J Jiao, SM Yiu, N Duan, ... arXiv preprint arXiv:2303.16854, 2023 | 124 | 2023 |
| Text generation with diffusion language models: A pre-training approach with continuous paragraph denoise Z Lin, Y Gong, Y Shen, T Wu, Z Fan, C Lin, N Duan, W Chen International Conference on Machine Learning, 21051-21064, 2023 | 57* | 2023 |
| Sentiment-Aware Word and Sentence Level Pre-training for Sentiment Analysis S Fan, C Lin, H Li, Z Lin, J Su, H Zhang, Y Gong, J Guo, N Duan EMNLP2022, 2022 | 22 | 2022 |
| Prod: Progressive distillation for dense retrieval Z Lin, Y Gong, X Liu, H Zhang, C Lin, A Dong, J Jiao, J Lu, D Jiang, ... WWW2023, 2022 | 19 | 2022 |
| Rho-1: Not all tokens are what you need Z Lin, Z Gou, Y Gong, X Liu, Y Shen, R Xu, C Lin, Y Yang, J Jiao, N Duan, ... arXiv preprint arXiv:2404.07965, 2024 | 17 | 2024 |
| Competition-level problems are effective llm evaluators Y Huang, Z Lin, X Liu, Y Gong, S Lu, F Lei, Y Liang, Y Shen, C Lin, ... Findings of the Association for Computational Linguistics ACL 2024, 13526-13544, 2024 | 8 | 2024 |
| AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators.” arXiv X He, Z Lin, Y Gong, AL Jin, H Zhang, C Lin, J Jiao, SM Yiu, N Duan, ... | 5 | 2023 |
| Ensuring Safe and High-Quality Outputs: A Guideline Library Approach for Language Models Y Luo, Z Lin, Y Zhang, J Sun, C Lin, C Xu, X Su, Y Shen, J Guo, Y Gong arXiv preprint arXiv:2403.11838, 2024 | 1 | 2024 |
| Revolutionizing Database Q&A with Large Language Models: Comprehensive Benchmark and Evaluation Y Zheng, B Li, Z Lin, Y Luo, X Zhou, C Lin, J Su, G Li, S Li arXiv preprint arXiv:2409.04475, 2024 | | 2024 |
