BabyVLM-V2: Toward Developmentally Grounded Pretraining and Benchmarking of Vision Foundation Models

BabyVLM-V2: Toward Developmentally Grounded Pretraining and Benchmarking of Vision Foundation Models. Wang, S., Wang, W., Wang, Z., Whitton, M., Wakeham, M., Chandra, A., Huang, J., Zhu, P., Chen, H., Li, D., Li, J., Li, S., Zagula, A., Zhao, A., Zhu, A., Nakamura, S., Yamamoto, Y., Yokono, J. J., Mueller, A., Plummer, B. A., Saenko, K., Saligrama, V., & Gong, B. CoRR, 2025.

Paper doi bibtex

@article{DBLP:journals/corr/abs-2512-10932,
  author       = {Shengao Wang and
                  Wenqi Wang and
                  Zecheng Wang and
                  Max Whitton and
                  Michael Wakeham and
                  Arjun Chandra and
                  Joey Huang and
                  Pengyue Zhu and
                  Helen Chen and
                  David Li and
                  Jeffrey Li and
                  Shawn Li and
                  Andrew Zagula and
                  Amy Zhao and
                  Andrew Zhu and
                  Sayaka Nakamura and
                  Yuki Yamamoto and
                  Jerry Jun Yokono and
                  Aaron Mueller and
                  Bryan A. Plummer and
                  Kate Saenko and
                  Venkatesh Saligrama and
                  Boqing Gong},
  title        = {BabyVLM-V2: Toward Developmentally Grounded Pretraining and Benchmarking
                  of Vision Foundation Models},
  journal      = {CoRR},
  volume       = {abs/2512.10932},
  year         = {2025},
  url          = {https://doi.org/10.48550/arXiv.2512.10932},
  doi          = {10.48550/ARXIV.2512.10932},
  eprinttype    = {arXiv},
  eprint       = {2512.10932},
  timestamp    = {Fri, 23 Jan 2026 00:00:00 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2512-10932.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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