Papers with top-100 accuracy

2 papers
Multi-Task Dense Retrieval via Model Uncertainty Fusion for Open-Domain Question Answering (2021.findings-emnlp)

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Challenge: Existing approaches to multitask dense retrieval are not effective due to corpus inconsistency.
Approach: They propose to train individual dense passage retrievers for different open-domain question-answering tasks and aggregate their predictions during test time.
Outcome: The proposed method achieves state-of-the-art performance on 5 benchmark QA datasets, with up to 10% improvement in top-100 accuracy compared to a joint-training multi-task DPR on SQuAD.
Semantic Scaffolds for Pseudocode-to-Code Generation (2020.acl-main)

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Challenge: Existing methods for program generation use lightweight structures to represent high-level semantics and syntactic composition of a program.
Approach: They propose a method for program generation based on semantic scaffolds . they use line-level natural language pseudocode annotations to search for programs .
Outcome: The proposed method achieves 10% improvement in top-100 accuracy over the current state-of-the-art method.

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