knowledge-base-4
Models Alignment
3260 papers • 126 benchmarks • 313 datasets
Models Alignment is the process of ensuring that multiple models used in a machine learning system are consistent with each other and aligned with the goals of the system. This involves defining clear and consistent objectives for each model, identifying and addressing any inconsistencies or biases in the data used to train each model, testing and validating each model to ensure its accuracy, and ensuring that the predictions and decisions made by each model are consistent and aligned with the overall goals of the system.
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Most implemented papers
Answering Numerical Reasoning Questions in Table-Text Hybrid Contents with Graph-based Encoder and Tree-based Decoder
Shizhu He, Xiang Lorraine Li, Kang Liu, Fangyu Lei, Jun Zhao•Thu Sep 15 2022
A Relational Graph enhanced Hybrid table-text Numerical reasoning model with Tree decoder (RegHNT) and a novel relational graph modeling method, which models alignment between questions, tables, and paragraphs is proposed.
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