Papers with stepwise method

2 papers
Generating Natural Language Proofs with Verifier-Guided Search (2022.emnlp-main)

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Challenge: Existing stepwise methods struggle to generate valid proof steps based on the hypothesis . instead, they generate invalid steps .
Approach: They propose a stepwise method which generates relevant steps conditioning on the hypothesis.
Outcome: The proposed method improves correctness of predicted proofs from 27.7% to 33.3% on EntailmentBank and RuleTaker.
ProofInfer: Generating Proof via Iterative Hierarchical Inference (2022.emnlp-main)

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Challenge: Existing proof generation models focus on generating several proof paths instead of a whole tree.
Approach: They propose a method that generates the proof tree via iterative hierarchical inference . they propose coding the proof as plain text without losing structure information .
Outcome: The proposed proof generation model significantly improves performance on widely-used datasets.

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