An ELMo-inspired approach to SemDeep-5's Word-in-Context task

LIAAD at SemDeep-5 Challenge: Word-in-Context (WiC)

This paper describes the LIAAD system that was ranked second place in the Word-in-Context challenge (WiC) featured in SemDeep-5. Our solution is based on a novel system for Word Sense Disambiguation (WSD) using contextua…

LIMSI-MULTISEM at the IJCAI SemDeep-5 WiC Challenge: Context Representations for Word Usage Similarity Estimation

Word Sense Disambiguation with Transformer Models

In this paper, we tackle the task of Word Sense Disambiguation (WSD). We present our system submitted to the Word-in-Context Target Sense Verification challenge, part of the SemDeep workshop at IJCAI 2020 (Breit et al., …

How Contextual are Contextualized Word Representations? Comparing the Geometry of BERT, ELMo, and GPT-2 Embeddings

Replacing static word embeddings with contextualized word representations has yielded significant improvements on many NLP tasks. However, just how contextual are the contextualized representations produced by models suc…

CTLR@WiC-TSV: Target Sense Verification using Marked Inputs andPre-trained Models

This paper describes the CTRL participation in the Target Sense Verification of the Words in Context challenge (WiC-TSV) at SemDeep6. Our strategy is based on a simplistic annotation scheme of the target words to later b…