| 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 (ICCV …, 2017 | 2255 | 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 | 2040 | 2019 |
| Language-driven Semantic Segmentation B Li, KQ Weinberger, S Belongie, V Koltun, R Ranftl International Conference on Learning Representations (ICLR), 2022 | 686 | 2022 |
| An all-in-one network for dehazing and beyond B Li, X Peng, Z Wang, J Xu, D Feng Women in Machine Learning Workshop (WiML), 2019 | 208 | 2019 |
| On Feature Normalization and Data Augmentation B Li, F Wu, SN Lim, S Belongie, KQ Weinberger Conference on Computer Vision and Pattern Recognition (CVPR), 2021 | 193 | 2021 |
| 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 (TMLR), 2024 | 158 | 2024 |
| 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 | 118 | 2018 |
| Positional Normalization B Li, F Wu, KQ Weinberger, S Belongie Advances in Neural Information Processing Systems (NeurIPS), 1622-1634, 2019 | 112 | 2019 |
| 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 (NeurIPS), 2023 | 97* | 2023 |
| LLM-grounded Video Diffusion Models L Lian, B Shi, A Yala, T Darrell, B Li International Conference on Learning Representations (ICLR), 2024 | 56 | 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 (ICLR), 2024 | 49 | 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 (ICLR), 2022 | 49 | 2022 |
| Self-correcting LLM-controlled Diffusion Models TH Wu, L Lian, JE Gonzalez, B Li, T Darrell Conference on Computer Vision and Pattern Recognition (CVPR), 2024 | 34 | 2024 |
| Interactive Task Planning with Language Models B Li, P Wu, P Abbeel, J Malik Transactions on Machine Learning Research (TMLR), 2025 | 28 | 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 (ICLR), 2024 | 24 | 2024 |
| 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 (CVPR), 2024 | 23 | 2024 |
| 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 (ICLR), 2025 | 12 | 2025 |
| 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 (CoRL), 2024 | 7 | 2024 |
| FastFusionNet: New State-of-the-Art for DAWNBench SQuAD F Wu, B Li, L Wang, N Lao, J Blitzer, KQ Weinberger Tech Report, 2019 | 7 | 2019 |
| Re-evaluating the need for visual signals in unsupervised grammar induction B Li, R Corona, K Mangalam, C Chen, D Flaherty, S Belongie, ... Findings of the Association for Computational Linguistics: NAACL 2024, 1113-1123, 2024 | 6* | 2024 |
