TAPAS (Table Parser) is a weakly supervised Transformer-based question answering model that reasons over tables without generating logical forms. Instead, it predicts a minimal program by selecting a relevant subset of table cells + the most likely aggregation operator to be executed on top of these cells, jointly. This allows TAPAS to learn operations based on natural language without requiring some explicit formalism.
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