2020年9月15日 · We propose to perform link prediction with MLMs to address both the KBs scalability issues and the MLMs interpretability issues. To do that we introduce MLMLM, Mean …

MLMLM is a link prediction model using Mean Likelihood Masked Language Model.

Masked Language Models (MLMs), such as BERT, scale with computing power as well as unstruc-tured raw text data. The knowledge contained within these models is however not …

2025年3月10日 · Louis Clouatre, Philippe Trempe, Amal Zouaq, and Sarath Chandar. 2021. MLMLM: Link Prediction with Mean Likelihood Masked Language Model. In Findings of the …

本文是论文 MLMLM: Link Prediction with Mean Likelihood Masked Language Model 的一些笔记与实验心得，该论文是2020年发表在arxiv上的一篇文章，用来解决 知识图谱 -链路预测（Link …

2024年3月8日 · Knowledge Bases (KBs) are easy to query, verifiable, and interpretable. They however scale with man-hours and high-quality data. Masked Language Models (MLMs), such …

We propose to perform link prediction with MLMs to address both the KBs scalability issues and the MLMs interpretability issues. To do that we introduce MLMLM, Mean Likelihood Masked …

2020年9月15日 · This work introduces MLMLM, Mean Likelihood Masked Language Model, an approach comparing the mean likelihood of generating the different entities to perform link …

2020年9月15日 · We propose to perform link prediction with MLMs to address both the KBs scalability issues and the MLMs interpretability issues. To do that we introduce MLMLM, Mean …

2021年1月1日 · MLMLM [3] proposes a mean likelihood method to compare the likelihood of different text of different token lengths sampled from a Masked LM to perform LP. Even though …