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Found 4 papers, 2 papers with code
Exploring Internal Numeracy in Language Models: A Case Study on ALBERT
It has been found that Transformer-based language models have the ability to perform basic quantitative reasoning.
Wavebender GAN: An architecture for phonetically meaningful speech manipulation
Deep learning has revolutionised synthetic speech quality.
The Case for Translation-Invariant Self-Attention in Transformer-Based Language Models
In this paper, we analyze the position embeddings of existing language models, finding strong evidence of translation invariance, both for the embeddings themselves and for their effect on self-attention.
Entity, Relation, and Event Extraction with Contextualized Span Representations
We examine the capabilities of a unified, multi-task framework for three information extraction tasks: named entity recognition, relation extraction, and event extraction.
Ranked #6 on
Joint Entity and Relation Extraction
on SciERC
