Papers with end-task supervision

2 papers
Neural Compositional Denotational Semantics for Question Answering (D18-1)

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Challenge: a new model for compositional questions is needed to answer multi-step reasoning . the model is inspired by formal approaches to compositional semantics .
Approach: They propose an end-to-end differentiable model for interpreting compositional questions . they build a latent tree of interpretable expressions over a sentence .
Outcome: The proposed model outperforms RNN encoders when test questions are longer than training questions.
Paired Examples as Indirect Supervision in Latent Decision Models (2021.emnlp-main)

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Challenge: a new method to learn compositional structured models is needed . end-task supervision provides only a weak indirect signal on values the latent decisions should take.
Approach: They propose a way to leverage paired examples that provide stronger cues for learning latent decisions . they use a DROP dataset to acquire paired questions that provide strong cue signals .
Outcome: The proposed approach improves compositional question answering on a DROP dataset.

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