Papers by Aadit Vyas

2 papers
DART: Open-Domain Structured Data Record to Text Generation (2021.naacl-main)

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Challenge: Data-to-text annotations can be costly when dealing with tables with nontrivial structures.
Approach: They propose a procedure for extracting semantic triples from tables that encodes their structures by exploiting table headers and table title.
Outcome: The proposed method exploits the semantic dependencies between table headers and title to extract semantic triples from tables.
ESPRIT: Explaining Solutions to Physical Reasoning Tasks (2020.acl-main)

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Challenge: Neural networks lack the ability to reason about qualitative physics and cannot generalize to scenarios and tasks unseen during training.
Approach: They propose a framework for reasoning about qualitative physics in natural language that generates interpretable descriptions of physical events.
Outcome: The proposed framework generates explanations of how the physical simulation will causally evolve so that an agent or a human can reason about a solution using interpretable descriptions.

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