| Aod-net: All-in-one dehazing network B Li, X Peng, Z Wang, J Xu, D Feng Proceedings of the IEEE International Conference on Computer Vision, 4770-4778, 2017 | 2797 | 2017 |
| Benchmarking single-image dehazing and beyond B Li, W Ren, D Fu, D Tao, D Feng, W Zeng, Z Wang IEEE Transactions on Image Processing 28 (1), 492-505, 2019 | 2623 | 2019 |
| Language-driven Semantic Segmentation B Li, KQ Weinberger, S Belongie, V Koltun, R Ranftl International Conference on Learning Representations, 2022 | 1013 | 2022 |
| LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models L Lian, B Li, A Yala, T Darrell Transactions on Machine Learning Research, 2024 | 293 | 2024 |
| Geometry-Informed Neural Operator for Large-Scale 3D PDEs Z Li, NB Kovachki, C Choy, B Li, J Kossaifi, SP Otta, MA Nabian, M Stadler, ... Advances in Neural Information Processing Systems, 2023 | 286* | 2023 |
| An all-in-one network for dehazing and beyond B Li, X Peng, Z Wang, J Xu, D Feng Women in Machine Learning, 2019 | 260 | 2019 |
| On Feature Normalization and Data Augmentation B Li, F Wu, SN Lim, S Belongie, KQ Weinberger Conference on Computer Vision and Pattern Recognition, 2021 | 234 | 2021 |
| End-to-End United Video Dehazing and Detection B Li, X Peng, Z Wang, J Xu, D Feng Proceedings of 32nd AAAI Conference on Artificial Intelligence, 2018 | 136 | 2018 |
| Positional Normalization B Li, F Wu, KQ Weinberger, S Belongie Advances in Neural Information Processing Systems, 1622-1634, 2019 | 130 | 2019 |
| LLM-grounded Video Diffusion Models L Lian, B Shi, A Yala, T Darrell, B Li International Conference on Learning Representations, 2024 | 107 | 2024 |
| Self-correcting LLM-controlled Diffusion Models TH Wu, L Lian, JE Gonzalez, B Li, T Darrell Conference on Computer Vision and Pattern Recognition, 2024 | 104 | 2024 |
| EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision J Yang, B Ivanovic, O Litany, X Weng, SW Kim, B Li, T Che, D Xu, S Fidler, ... International Conference on Learning Representations, 2024 | 100 | 2024 |
| Fixed Neural Network Steganography: Train the images, not the network V Kishore, X Chen, Y Wang, B Li, KQ Weinberger International Conference on Learning Representations, 2022 | 69 | 2022 |
| PhysBench: Benchmarking and Enhancing Vision-Language Models for Physical World Understanding W Chow, J Mao, B Li, D Seita, V Guizilini, Y Wang International Conference on Learning Representations, 2025 | 61 | 2025 |
| Interactive Task Planning with Language Models B Li, P Wu, P Abbeel, J Malik Transactions on Machine Learning Research, 2025 | 59 | 2025 |
| Driving Everywhere with Large Language Model Policy Adaptation B Li, Y Wang, J Mao, B Ivanovic, S Veer, K Leung, M Pavone Conference on Computer Vision and Pattern Recognition, 2024 | 58 | 2024 |
| Tokenize the World into Object-level Knowledge to Address Long-tail Events in Autonomous Driving R Tian, B Li, X Weng, Y Chen, E Schmerling, Y Wang, B Ivanovic, ... Conference on Robot Learning, 2024 | 52 | 2024 |
| Describe Anything: Detailed Localized Image and Video Captioning L Lian, Y Ding, Y Ge, S Liu, H Mao, B Li, M Pavone, MY Liu, T Darrell, ... Proceedings of the IEEE International Conference on Computer Vision, 2025 | 40 | 2025 |
| Language-Image Models with 3D Understanding JH Cho, B Ivanovic, Y Cao, E Schmerling, Y Wang, X Weng, B Li, Y You, ... International Conference on Learning Representations, 2025 | 36 | 2025 |
| Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition S Yu, W Nie, DA Huang, B Li, J Shin, A Anandkumar International Conference on Learning Representations, 2024 | 32 | 2024 |
