Urmăriți
Li Bo
Li Bo
Alte numeBrian Bo Li
PhD Student, MM@NTU, Singapore
Adresă de e-mail confirmată pe e.ntu.edu.sg - Pagina de pornire
Titlu
Citat de
Citat de
Anul
Mmbench: Is your multi-modal model an all-around player?
Y Liu, H Duan, Y Zhang, B Li, S Zhang, W Zhao, Y Yuan, J Wang, C He, ...
European conference on computer vision, 216-233, 2024
8022024
MIMIC-IT: Multi-modal in-context instruction tuning
B Li, Y Zhang, L Chen, J Wang, F Pu, J Yang, C Li, Z Liu
arXiv preprint arXiv:2306.05425, 2023
6282023
Llava-next: Improved reasoning, ocr, and world knowledge
H Liu, C Li, Y Li, B Li, Y Zhang, S Shen, YJ Lee
URL https://llava-vl. github. io/blog/2024-01-30-llava-next, 2024
5292024
A review of single-source deep unsupervised visual domain adaptation
S Zhao, X Yue, S Zhang, B Li, H Zhao, B Wu, R Krishna, JE Gonzalez, ...
IEEE Transactions on Neural Networks and Learning Systems 33 (2), 473-493, 2020
3262020
Llava-onevision: Easy visual task transfer
B Li, Y Zhang, D Guo, R Zhang, F Li, H Zhang, K Zhang, P Zhang, Y Li, ...
arXiv preprint arXiv:2408.03326, 2024
3062024
OpenOOD: Benchmarking Generalized Out-of-Distribution Detection
J Yang, P Wang, D Zou, Z Zhou, K Ding, W Peng, H Wang, G Chen, B Li, ...
NeurIPS 2022 Datasets and Benchmarks Track, 2022
2622022
Multi-source domain adaptation for semantic segmentation
S Zhao, B Li, X Yue, Y Gu, P Xu, R Hu, H Chai, K Keutzer
NeurIPS 2019, 2019
1992019
Multi-source domain adaptation in the deep learning era: A systematic survey
S Zhao, B Li, P Xu, K Keutzer
arXiv preprint arXiv:2002.12169, 2020
1472020
Self-Supervised Pretraining Improves Self-Supervised Pretraining
CJ Reed, X Yue, A Nrusimha, S Ebrahimi, V Vijaykumar, R Mao, B Li, ...
WACV 2022, 2021
1262021
Llava-next-interleave: Tackling multi-image, video, and 3d in large multimodal models
F Li, R Zhang, H Zhang, Y Zhang, B Li, W Li, Z Ma, C Li
arXiv preprint arXiv:2407.07895, 2024
1222024
Invariant Information Bottleneck for Domain Generalization
B Li, Y Shen, Y Wang, W Zhu, CJ Reed, D Li, K Keutzer, H Zhao
AAAI 2022, 2021
1202021
Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation
B Li, Y Wang, S Zhang, D Li, T Darrell, K Keutzer, H Zhao
CVPR 2021, 2020
1072020
ePointDA: An End-to-End Simulation-to-Real Domain Adaptation Framework for LiDAR Point Cloud Segmentation
S Zhao, Y Wang, B Li, B Wu, Y Gao, P Xu, T Darrell, K Keutzer
AAAI 2021, 2020
962020
Madan: multi-source adversarial domain aggregation network for domain adaptation
S Zhao, B Li, P Xu, X Yue, G Ding, K Keutzer
International Journal of Computer Vision 129 (8), 2399-2424, 2021
742021
Sparse Mixture-of-Experts are Domain Generalizable Learners
B Li, J Yang, J Ren, Y Wang, Z Liu
ICLR 2023 (Oral), 2022
672022
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
Y Wang, B Li, T Che, K Zhou, D Li, Z Liu
ICCV 2021, 2021
662021
Rethinking distributional matching based domain adaptation
B Li, Y Wang, T Che, S Zhang, S Zhao, P Xu, W Zhou, Y Bengio, ...
arXiv preprint arXiv:2006.13352, 2020
642020
Llava-next: Stronger llms supercharge multimodal capabilities in the wild
B Li, K Zhang, H Zhang, D Guo, R Zhang, F Li, Y Zhang, Z Liu, C Li
May, 2024
582024
Otterhd: A high-resolution multi-modality model
B Li, P Zhang, J Yang, Y Zhang, F Pu, Z Liu
arXiv preprint arXiv:2311.04219, 2023
502023
Octopus: Embodied vision-language programmer from environmental feedback
J Yang, Y Dong, S Liu, B Li, Z Wang, H Tan, C Jiang, J Kang, Y Zhang, ...
European Conference on Computer Vision, 20-38, 2024
492024
Sistemul nu poate realiza operația în acest moment. Încercați din nou mai târziu.
Articole 1–20