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Found 2 papers, 1 papers with code
HEMM: Holistic Evaluation of Multimodal Foundation Models
Through comprehensive experiments across the 30 tasks in HEMM, we (1) identify key dataset dimensions (e. g., basic skills, information flows, and use cases) that pose challenges to today's models, and (2) distill performance trends regarding how different modeling dimensions (e. g., scale, pre-training data, multimodal alignment, pre-training, and instruction tuning objectives) influence performance.
Exploring Answer Information Methods for Question Generation with Transformers
There has been a lot of work in question generation where different methods to provide target answers as input, have been employed.
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