Fine-Tuning, Medical LLMs, and Clinical Alignment
By Zeineb
Zeineb improves AutoScanAI through fine-tuning and adds a Medical LLM Explainer to deliver robust, clinically interpretable, WHO-aware AI outputs.
By Zeineb
Zeineb improves AutoScanAI through fine-tuning and adds a Medical LLM Explainer to deliver robust, clinically interpretable, WHO-aware AI outputs.
More from the Lab
Zeineb shares progress on her model, discussing recent experiments and how she's refining the system while evaluating results as the project moves forward.
Mugi updates SignMate's motion generation system by adding face tracking and fingerspelling to improve ASL accuracy, expressiveness, and realism.
Mugi updates her project by moving from a single-camera setup to a dual-camera solution, improving motion capture accuracy and overall system reliability.
What makes an AI interviewer trustworthy? Not intelligence — behavior. Four research-backed principles for building Yield.
Research-backed principles that make AI interviews feel more natural and trustworthy.