Finetuning VLMs on perception tasks produces positive and negative transfers that can be mapped with a new normalized metric called Perfection Gap Factor across 13 tasks and three models.
How well do contrastively trained models transfer? InFirst Workshop on Pre-training: Perspectives, Pitfalls, and Paths Forward at ICML 2022
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Understanding Task Transfer in Vision-Language Models
Finetuning VLMs on perception tasks produces positive and negative transfers that can be mapped with a new normalized metric called Perfection Gap Factor across 13 tasks and three models.