Papers by Ashish Thapliyal

2 papers
MaXM: Towards Multilingual Visual Question Answering (2023.findings-emnlp)

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Challenge: Visual Question Answering (VQA) has been studied in the English language, but in other languages it would require a considerable amount of resources.
Approach: They propose scalable solutions to multilingual visual question answering using an English language framework and an annotation protocol.
Outcome: The proposed framework reduces human annotation efforts and creates a test-only VQA benchmark in 7 languages.
Emergence of Abstract State Representations in Embodied Sequence Modeling (2023.emnlp-main)

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Challenge: Sequence modeling is a simple yet versatile task that can be applied to more complex decision-making domains.
Approach: They build a sequence modeling Transformer which takes a language instruction, actions, and environmental observations as inputs and then trains a model to reconstruct environmental layouts.
Outcome: The proposed model can reconstruct environmental layouts from the inputs of the model and language instructions play a role in the reconstruction accuracy.

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