SemPool: Simple, Robust, and Interpretable KG Pooling for Enhancing Language Models

Author:

Mavromatis Costas,Karypis Petros,Karypis George

Publisher

Springer Nature Singapore

Reference37 articles.

1. Agarwal, O., Ge, H., Shakeri, S., Al-Rfou, R.: Knowledge graph based synthetic corpus generation for knowledge-enhanced language model pre-training. In: NAACL (2021)

2. Clark, P., et al.: From ‘F’ to ‘A’ on the NY regents science exams: an overview of the aristo project. AI Mag. 41(4), 39–53 (2020)

3. Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)

4. Feng, Y., Chen, X., Lin, B.Y., Wang, P., Yan, J., Ren, X.: Scalable multi-hop relational reasoning for knowledge-aware question answering. In: EMNLP (2020)

5. Gilmer, J., Schoenholz, S.S., Riley, P.F., Vinyals, O., Dahl, G.E.: Neural message passing for quantum chemistry. In: ICML (2017)

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