Toward video-LLM driven workflow for behavioral segmentation and scoring in mice performing a skilled water-reaching task: an evaluation of recent LLM models
- DOI
- 10.1117/1.nph.13.3.036601
- Published
- 2026-08-04
- Container
- Neurophotonics
- Publisher
- SPIE-Intl Soc Optical Eng
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1117/1.nph.13.3.036601,
title = {Toward video-LLM driven workflow for behavioral segmentation and scoring in mice performing a skilled water-reaching task: an evaluation of recent LLM models},
author = {Tony Fong and Hao Hu and Haozong Zeng and Parnian Abbasi and Timothy H. Murphy},
year = {2026},
journal = {Neurophotonics},
doi = {10.1117/1.nph.13.3.036601},
url = {https://doi.org/10.1117/1.nph.13.3.036601}
}RIS
TY - JOUR TI - Toward video-LLM driven workflow for behavioral segmentation and scoring in mice performing a skilled water-reaching task: an evaluation of recent LLM models AU - Tony Fong AU - Hao Hu AU - Haozong Zeng AU - Parnian Abbasi AU - Timothy H. Murphy PY - 2026 JO - Neurophotonics DO - 10.1117/1.nph.13.3.036601 UR - https://doi.org/10.1117/1.nph.13.3.036601 ER -
APA
Fong, T., Hu, H., Zeng, H., Abbasi, P., & Murphy, T. H. (2026). Toward video-LLM driven workflow for behavioral segmentation and scoring in mice performing a skilled water-reaching task: an evaluation of recent LLM models. Neurophotonics. https://doi.org/10.1117/1.nph.13.3.036601
Source records
- crossref · retrieved 2026-09-25T11:23:52.312Z