Deep contextualized word representations
Peters et al., 2018, Deep contextualized word representations (Proceedings of the 2018 Conference of the North American Chapter of ACL: Human Language Technologies (NAACL-HLT 2018))
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5.5 Visualization of learned weights
- What layer weights did tasks learn for ELMo?At the input, tasks favoured the first biLSTM layer, strongly so for coreference and SQuAD; at the output, weights were fairly balanced with a slight preference for lower layers.
- Peters et al., 2018, Deep contextualized word representations (Proceedings of the 2018 Conference of the North American Chapter of ACL: Human Language Technologies (NAACL-HLT 2018)), §5.5, p. 2234
Source
- Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee and Luke Zettlemoyer. 2018. Deep contextualized word representations. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2018), pp. 2227–2237. License: CC BY 4.0. Flashcards adapted from this work. doi:10.18653/v1/N18-1202 https://aclanthology.org/N18-1202/