Research map / Label-efficient and robust learning / Recognition and long-tail
Bilingual Lexicon Induction from Non-Parallel Data with Minimal Supervision
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add the matching term to the learning objective (vs seed term only) (ablation) | bilingual embedding lexicon inducer · zh-en, 50 seeds | accuracy | Helped |
| reduce seed lexicon from 100 to 10 pairs (ablation) | Ours · zh-en | accuracy | No clear effect |
| reduce seed lexicon size | TM, IA, STAT, BilBOWA baselines · zh-en | accuracy | Hurt |
| reduce seed lexicon to 10 for Turkish-English (ablation) | Ours · tr-en | accuracy | Hurt |
| set matching weight too large (ablation) | Ours · validation set | accuracy | Hurt |
| set matching weight too low (ablation) | Ours · validation set | accuracy | Hurt |
| replace TM with IA (isometric constraint) | translation matrix · es-en, 50 seeds | accuracy (%): 10.76 -> 32.36 | Helped |
Closest papers by meaning
- Word translation without parallel data (ICLR 2018 · similarity 0.91)
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- Enhancing Bilingual Lexicon Induction via Bi-directional Translation Pair Retrieving (AAAI 2024 · similarity 0.89)
- Unsupervised Bilingual Lexicon Induction from Mono-Lingual Multimodal Data (AAAI 2019 · similarity 0.89)
- Building Earth Mover's Distance on Bilingual Word Embeddings for Machine Translation (AAAI 2016 · similarity 0.88)
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