-
LLaVA-o1: Let Vision Language Models Reason Step-by-Step
Paper • 2411.10440 • Published • 129 -
ClinicalBench: Can LLMs Beat Traditional ML Models in Clinical Prediction?
Paper • 2411.06469 • Published • 17 -
Sharingan: Extract User Action Sequence from Desktop Recordings
Paper • 2411.08768 • Published • 9 -
AnimateAnything: Consistent and Controllable Animation for Video Generation
Paper • 2411.10836 • Published • 24
Tran Minh Quan
quantranvr
AI & ML interests
None yet
Organizations
None yet
-
LLaVA-o1: Let Vision Language Models Reason Step-by-Step
Paper • 2411.10440 • Published • 129 -
ClinicalBench: Can LLMs Beat Traditional ML Models in Clinical Prediction?
Paper • 2411.06469 • Published • 17 -
Sharingan: Extract User Action Sequence from Desktop Recordings
Paper • 2411.08768 • Published • 9 -
AnimateAnything: Consistent and Controllable Animation for Video Generation
Paper • 2411.10836 • Published • 24
models
0
None public yet
datasets
0
None public yet