VQA

AbstractAlthough current evaluation of question-answering systems treats predictions in isolation, we need to consider the relationship between predictions to measure true understanding. A model should be penalized for answering “no” …...

AbstractRecent work establishes dataset difficulty and removes annotation artifacts via partial-input baselines (e.g., hypothesis-only model for SNLI or question-only model for VQA). A successful partial-input baseline indicates that the dataset …...

AbstractLarge pre-trained vision-language (VL) models can learn a new task with a handful of examples and generalize to a new task without fine-tuning. However, these VL models are hard to …...

AbstractIn traditional Visual Question Generation (VQG), most images have multiple concepts (e.g. objects and categories) for which a question could be generated, but models are trained to mimic an arbitrary …...