| A survey on in-context learning Q Dong, L Li, D Dai, C Zheng, Z Wu, B Chang, X Sun, J Xu, Z Sui EMNLP 2024, 2023 | 1272 | 2023 |
| Large language models are not fair evaluators P Wang, L Li, L Chen, D Zhu, B Lin, Y Cao, Q Liu, T Liu, Z Sui ACL 2024, 2023 | 334 | 2023 |
| Be careful about poisoned word embeddings: Exploring the vulnerability of the embedding layers in nlp models W Yang, L Li, Z Zhang, X Ren, X Sun, B He NAACL 2021, 2021 | 144 | 2021 |
| MIT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning L Li, Y Yin, S Li, L Chen, P Wang, S Ren, M Li, Y Yang, J Xu, X Sun, ... arXiv preprint arXiv:2306.04387, 2023 | 133* | 2023 |
| Can We Edit Factual Knowledge by In-Context Learning? C Zheng, L Li, Q Dong, Y Fan, Z Wu, J Xu, B Chang EMNLP 2023, 2023 | 124 | 2023 |
| Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning L Wang, L Li, D Dai, D Chen, H Zhou, F Meng, J Zhou, X Sun EMNLP 2023 (Best Long Paper Award), 2023 | 103 | 2023 |
| Enhancing topic-to-essay generation with external commonsense knowledge P Yang, L Li, F Luo, T Liu, X Sun ACL 2019, 2002-2012, 2019 | 97 | 2019 |
| Math-shepherd: A label-free step-by-step verifier for llms in mathematical reasoning P Wang, L Li, Z Shao, RX Xu, D Dai, Y Li, D Chen, Y Wu, Z Sui ACL 2024, 2023 | 94* | 2023 |
| Video-mme: The first-ever comprehensive evaluation benchmark of multi-modal llms in video analysis C Fu, Y Dai, Y Luo, L Li, S Ren, R Zhang, Z Wang, C Zhou, Y Shen, ... arXiv preprint arXiv:2405.21075, 2024 | 75 | 2024 |
| Knowledgeable Storyteller: A Commonsense-Driven Generative Model for Visual Storytelling. P Yang, F Luo, P Chen, L Li, Z Yin, X He, X Sun IJCAI 2019, 2019 | 74 | 2019 |
| VLFeedback: A Large-Scale AI Feedback Dataset for Large Vision-Language Models Alignment L Li*, Z Xie*, M Li, S Chen, P Wang, L Chen, Y Yang, B Wang, L Kong, ... EMNLP 2024 (arXiv:2410.09421, previous arXiv:2312.10665), 2024 | 52* | 2024 |
| Making large language models better reasoners with alignment P Wang, L Li, L Chen, F Song, B Lin, Y Cao, T Liu, Z Sui arXiv preprint arXiv:2309.02144, 2023 | 48 | 2023 |
| CascadeBERT: Accelerating inference of pre-trained language models via calibrated complete models cascade L Li, Y Lin, D Chen, S Ren, P Li, J Zhou, X Sun Findings of EMNLP 2021, 2020 | 45* | 2020 |
| Dynamic Knowledge Distillation for Pre-trained Language Models L Li, Y Lin, S Ren, P Li, J Zhou, X Sun EMNLP 2021 (Oral), 2021 | 42 | 2021 |
| FETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation Y Liu, L Li, S Ren, R Gao, S Li, S Chen, X Sun, L Hou NeurIPS 2023 Dataset and Benchmark Track, 2023 | 39 | 2023 |
| Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models L Li, Y Wang, R Xu, P Wang, X Feng, L Kong, Q Liu ACL 2024, 2024 | 38 | 2024 |
| Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification S Ren, J Zhang, L Li, X Sun, J Zhou EMNLP 2021, 2021 | 37 | 2021 |
| TempCompass: Do Video LLMs Really Understand Videos? Y Liu, S Li, Y Liu, Y Wang, S Ren, L Li, S Chen, X Sun, L Hou Findings of ACL 2024, 2024 | 36 | 2024 |
| Red teaming visual language models M Li, L Li, Y Yin, M Ahmed, Z Liu, Q Liu Findings of ACL 2024, 2024 | 32 | 2024 |
| Automatic generation of personalized comment based on user profile W Zeng, A Abuduweili, L Li, P Yang ACL Student Research Workshop 2019, 2019 | 27 | 2019 |
Xu SunAssociate Professor, Peking UniversityVerified email at pku.edu.cn
