Hugging Face Trending Papers

TraMP-LLaMA: Generative Interpretability with Decoupled Instruction Tuning for Facial Expression Quality Assessment

Read the original on Hugging Face Trending Papers →

Existing facial expression quality assessment (FEQA) methods typically produce only a severity score, without explicitly communicating the observable facial motion evidence that supports the prediction. This limits interpretability and makes it difficult to inspect the basis of model outputs in Parkinson's disease assessment.

Summary generated by The Flow from the publisher's feed. The full article lives at Hugging Face Trending Papers.