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LASER: shared multilingual sentence embeddings for transfer and mining

Contribution grade

Multilingual sentence representations · Human-designed research method or resource

Reference score125,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Trained a shared BiLSTM encoder with max pooling, joint subword vocabulary and an auxiliary translation decoder to obtain fixed-dimensional sentence vectors for cross-lingual transfer and parallel-sentence retrieval.

Scientific scope

Trained a shared BiLSTM encoder with max pooling, joint subword vocabulary and an auxiliary translation decoder to obtain fixed-dimensional sentence vectors for cross-lingual transfer and parallel-sentence retrieval. Zero-shot downstream transfer is not zero parallel supervision: representation training uses parallel corpora. Original93-language encoder and122-language test resource have different coverage. Later LASER variants are not treated as part of this original architecture.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Zero-shot downstream transfer is not zero parallel supervision: representation training uses parallel corpora. Original93-language encoder and122-language test resource have different coverage. Later LASER variants are not treated as part of this original architecture.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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