3 papers
cs.CL2021
Separating Retention from Extraction in the Evaluation of End-to-end Relation Extraction
Bruno Taillé, Vincent Guigue, Geoffrey Scoutheeten +1
State-of-the-art NLP models can adopt shallow heuristics that limit their generalization capability (McCoy et al., 2019). Such heuristics include lexical overlap with the training…
cs.CL2020
Let's Stop Incorrect Comparisons in End-to-end Relation Extraction!
Bruno Taillé, Vincent Guigue, Geoffrey Scoutheeten +1
Despite efforts to distinguish three different evaluation setups (Bekoulis et al., 2018), numerous end-to-end Relation Extraction (RE) articles present unreliable performance compa…
cs.CL2020
Contextualized Embeddings in Named-Entity Recognition: An Empirical Study on Generalization
Bruno Taillé, Vincent Guigue, Patrick Gallinari
Contextualized embeddings use unsupervised language model pretraining to compute word representations depending on their context. This is intuitively useful for generalization, esp…