Toward video-LLM driven workflow for behavioral segmentation and scoring in mice performing a skilled water-reaching task: an evaluation of recent LLM models

Tony Fong, Hao Hu, Haozong Zeng, Parnian Abbasi, Timothy H. Murphy

Open source

DOI
10.1117/1.nph.13.3.036601
Published
2026-08-04
Container
Neurophotonics
Publisher
SPIE-Intl Soc Optical Eng
Open access
unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

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