Papers › Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond

Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond

26 Dec 2018TACL 2019 3arXiv:1812.10464archive 2025-07-28

Mikel Artetxe, Holger Schwenk

We introduce an architecture to learn joint multilingual sentence representations for 93 languages, belonging to more than 30 different families and written in 28 different scripts. Our system uses a single BiLSTM encoder with a shared BPE vocabulary for all languages, which is coupled with an auxiliary decoder and trained on publicly available parallel corpora. This enables us to learn a classifier on top of the resulting embeddings using English annotated data only, and transfer it to any of the 93 languages without any modification. Our experiments in cross-lingual natural language inference (XNLI dataset), cross-lingual document classification (MLDoc dataset) and parallel corpus mining (BUCC dataset) show the effectiveness of our approach. We also introduce a new test set of aligned sentences in 112 languages, and show that our sentence embeddings obtain strong results in multilingual similarity search even for low-resource languages. Our implementation, the pre-trained encoder and the multilingual test set are available at https://github.com/facebookresearch/LASER

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13 repositories listed; official and paper-mentioned ones first.

facebookresearch/LASER officialmentioned in papermentioned on GitHubpytorch report
LawrenceDuan/myLASER mentioned on GitHubpytorch report
Tony4469/laser-agir mentioned on GitHubpytorchNOASSERTION report
Unbabel/COMET mentioned on GitHubpytorch report
facebookresearch/vizseq mentioned on GitHub report
imamathcat/LASER_Dependencies mentioned on GitHubpytorchNOASSERTION report
jeongukjae/smaller-labse mentioned on GitHubtfApache-2.0 report
jiamingkong/infoxlm_paddle mentioned on GitHubpaddle report
kmkwon94/ainize-laser mentioned on GitHubpytorchNOASSERTION report
prabhakar267/LASER-improved mentioned on GitHubpytorchNOASSERTION report
raymondhs/fairseq-laser mentioned on GitHubpytorchMIT report
transducens/LASERtrain mentioned on GitHubpytorch report
yannvgn/laserembeddings mentioned on GitHubpytorchBSD-3-Clause report

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BuccOptimize LawrenceDuan/myLASER/tasks/bucc/bucc.py community (archive-listed) ran · honoured contract licence not identified · pointer only · ff90acbe13627868 · report
buffered_arange transducens/LASERtrain/fairseq-modules/multilingual_lstm_laser.py community (archive-listed) ran · honoured contract fingerprinted no licence file found · pointer only · b635d11e8b643e36 · report
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adapt_bpe_codes yannvgn/laserembeddings/laserembeddings/utils.py community (archive-listed) unverified BSD-3-Clause (permissive) · 13a068cfdda041fe · report
add_decoder_language raymondhs/fairseq-laser/laser/laser_dataset.py community (archive-listed) unverified MIT (permissive) · ccb4f61614cf3799 · report
buffered_arange yannvgn/laserembeddings/laserembeddings/encoder.py community (archive-listed) unverified BSD-3-Clause (permissive) · b2ad3933e6341902 · report
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uniform_sampler raymondhs/fairseq-laser/laser/laser_dataset.py community (archive-listed) unverified MIT (permissive) · 50e8df121d8ca072 · report

Tasks

Cross-Lingual Bitext MiningCross-Lingual Document ClassificationCross-Lingual Natural Language InferenceCross-Lingual TransferDecoderDocument ClassificationJoint Multilingual Sentence RepresentationsNatural Language InferenceParallel Corpus MiningSentenceSentence EmbeddingsZero-Shot Cross-Lingual Transfer

Datasets

Introduced by this paper, per the archive.

Tatoeba

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Cross-Lingual Bitext Mining BUCC Chinese-to-English Massively Multilingual Sentence Embeddings F1 score 92.27 #1 of 1 Archive leaderboard report
Cross-Lingual Bitext Mining BUCC French-to-English Massively Multilingual Sentence Embeddings F1 score 93.91 #1 of 3 Archive leaderboard report
Cross-Lingual Bitext Mining BUCC German-to-English Massively Multilingual Sentence Embeddings F1 score 96.19 #1 of 3 Archive leaderboard report
Cross-Lingual Bitext Mining BUCC Russian-to-English Massively Multilingual Sentence Embeddings F1 score 93.3 #1 of 1 Archive leaderboard report
Cross-Lingual Document Classification MLDoc Zero-Shot English-to-Chinese Massively Multilingual Sentence Embeddings Accuracy 71.93 #5 of 5 Archive leaderboard report
Cross-Lingual Document Classification MLDoc Zero-Shot English-to-French Massively Multilingual Sentence Embeddings Accuracy 77.95 #3 of 6 Archive leaderboard report
Cross-Lingual Document Classification MLDoc Zero-Shot English-to-German Massively Multilingual Sentence Embeddings Accuracy 84.78% #3 of 5 Archive leaderboard report
Cross-Lingual Document Classification MLDoc Zero-Shot English-to-Italian Massively Multilingual Sentence Embeddings Accuracy 69.43 #2 of 4 Archive leaderboard report
Cross-Lingual Document Classification MLDoc Zero-Shot English-to-Japanese Massively Multilingual Sentence Embeddings Accuracy 60.3 #3 of 3 Archive leaderboard report
Cross-Lingual Document Classification MLDoc Zero-Shot English-to-Russian Massively Multilingual Sentence Embeddings Accuracy 67.78 #3 of 5 Archive leaderboard report
Cross-Lingual Document Classification MLDoc Zero-Shot English-to-Spanish Massively Multilingual Sentence Embeddings Accuracy 77.33 #3 of 6 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

BPEBiLSTMLSTMSigmoid ActivationTanh Activation

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