Papers by Ali Saad-Eldin

2 papers
Bilingual Lexicon Induction for Low-Resource Languages using Graph Matching via Optimal Transport (2022.emnlp-main)

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Challenge: Existing literature on bilingual lexicon induction fails in low-resource scenarios . a language dataset is considered low- resource based on its own embedding space .
Approach: They propose a graph-matching method that improves bilingual lexicon induction performance across 40 language pairs using optimal transport.
Outcome: The proposed method is especially strong with low amounts of supervision.
An Analysis of Euclidean vs. Graph-Based Framing for Bilingual Lexicon Induction from Word Embedding Spaces (2021.findings-emnlp)

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Challenge: Existing work in bilingual lexicon induction views word embeddings as vectors in Euclidean space.
Approach: They propose to use word embeddings as nodes in a weighted graph to examine a node’s graph neighborhood without assuming a linear transform.
Outcome: The proposed approaches are compared under different data conditions and show that they complement each other when combined.

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