Papers › Supervised Learning of Universal Sentence Representations from Natural Language Inference Data

Supervised Learning of Universal Sentence Representations from Natural Language Inference Data

5 May 2017EMNLP 2017 9arXiv:1705.02364archive 2025-07-28

Alexis Conneau, Douwe Kiela, Holger Schwenk, Loic Barrault, Antoine Bordes

Many modern NLP systems rely on word embeddings, previously trained in an unsupervised manner on large corpora, as base features. Efforts to obtain embeddings for larger chunks of text, such as sentences, have however not been so successful. Several attempts at learning unsupervised representations of sentences have not reached satisfactory enough performance to be widely adopted. In this paper, we show how universal sentence representations trained using the supervised data of the Stanford Natural Language Inference datasets can consistently outperform unsupervised methods like SkipThought vectors on a wide range of transfer tasks. Much like how computer vision uses ImageNet to obtain features, which can then be transferred to other tasks, our work tends to indicate the suitability of natural language inference for transfer learning to other NLP tasks. Our encoder is publicly available.

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

facebookresearch/InferSent officialmentioned in papermentioned on GitHubpytorchNOASSERTION report
facebookresearch/SentEval officialmentioned in papermentioned on GitHubpytorch report
HareeshBahuleyan/size-fit-net mentioned on GitHubpytorch report
Jessicak016/lstm_nli mentioned on GitHubtf report
MirkoLenz/ReCAP-Argument-Graph-Retrieval mentioned on GitHubtfApache-2.0 report
ReCAP-UTR/Argument-Graph-Retrieval mentioned on GitHubtfApache-2.0 report
avinassh/kylo mentioned on GitHub report
boknilev/nmt-repr-analysis mentioned on GitHubpytorch report
cdpierse/transformers-interpret mentioned on GitHubpytorch report
duynguyen158/wann-nlp mentioned on GitHubpytorch report
f-data/ADD mentioned on GitHubtf report
galkesten/Domestic-Violence-Classifier mentioned on GitHubpytorch report
jean-kunz/ml_research_papers mentioned on GitHubtf report
jvdbogae/artverc mentioned on GitHubApache-2.0 report
mario-holubar/ATCS-InferSent mentioned on GitHubpytorch report
menajosep/AleatoricSent mentioned on GitHubtfApache-2.0 report
rajatgermany/qa-nlp mentioned on GitHubpytorch report
shaanchandra/InferSent mentioned on GitHubpytorch report
sidak/SentEval mentioned on GitHubpytorch report
wbglaeser/brexit-sentiment mentioned on GitHubpytorch report

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7 samples harvested; 6 ran; 2 honoured the contract we drafted; 1 has no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.

2ran · honoured contract
4ran · our draft was wrong
1unverified

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batcher facebookresearch/SentEval/examples/bow.py official repository ran · honoured contract licence not identified · pointer only · ff910817bb9f0411 · report
create_dictionary facebookresearch/SentEval/examples/bow.py official repository ran · our draft was wrong licence not identified · pointer only · af7388308de7ccb4 · report
get_wordvec facebookresearch/SentEval/examples/bow.py official repository ran · our draft was wrong licence not identified · pointer only · 19d5c2686259a0af · report
batcher sidak/SentEval/examples/infersent.py community (archive-listed) ran · honoured contract licence not identified · pointer only · e1c6e7d12d71cb6b · report
create_dictionary shaanchandra/InferSent/code/senteval.py community (archive-listed) ran · our draft was wrong no licence file found · pointer only · 6ebd3e9ce17919eb · report
get_wordvec shaanchandra/InferSent/code/senteval.py community (archive-listed) ran · our draft was wrong no licence file found · pointer only · f830374dfcc9ad29 · report
embed_batch shaanchandra/InferSent/code/senteval.py community (archive-listed) unverified no licence file found · pointer only · e12fbd7bafb84d3d · report

Tasks

Cross-Lingual Natural Language InferenceNatural Language InferenceSemantic Textual SimilaritySentenceTransfer LearningWord Embeddings

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Cross-Lingual Natural Language Inference XNLI Zero-Shot English-to-French X-BiLSTM Accuracy 67.7% #2 of 3 Archive leaderboard report
Cross-Lingual Natural Language Inference XNLI Zero-Shot English-to-French X-CBOW Accuracy 60.3% #3 of 3 Archive leaderboard report
Cross-Lingual Natural Language Inference XNLI Zero-Shot English-to-German X-BiLSTM Accuracy 67.7% #3 of 4 Archive leaderboard report
Cross-Lingual Natural Language Inference XNLI Zero-Shot English-to-German X-CBOW Accuracy 61.0% #4 of 4 Archive leaderboard report
Cross-Lingual Natural Language Inference XNLI Zero-Shot English-to-Spanish X-BiLSTM Accuracy 68.7% #3 of 4 Archive leaderboard report
Cross-Lingual Natural Language Inference XNLI Zero-Shot English-to-Spanish X-CBOW Accuracy 60.7% #4 of 4 Archive leaderboard report
Natural Language Inference SNLI 4096D BiLSTM with max-pooling % Test Accuracy 84.5 #78 of 98 Archive leaderboard report
Natural Language Inference SNLI 4096D BiLSTM with max-pooling % Train Accuracy 85.6 #78 of 98 Archive leaderboard report
Natural Language Inference SNLI 4096D BiLSTM with max-pooling Parameters 40m #78 of 98 Archive leaderboard report
Semantic Textual Similarity MRPC InferSent Accuracy 76.2% #37 of 45 Archive leaderboard report
Semantic Textual Similarity MRPC InferSent F1 83.1% #37 of 45 Archive leaderboard report
Semantic Textual Similarity SentEval InferSent MRPC 76.2/83.1 #2 of 6 Archive leaderboard report
Semantic Textual Similarity SentEval InferSent SICK-E 86.3 #2 of 6 Archive leaderboard report
Semantic Textual Similarity SentEval InferSent SICK-R 0.884 #2 of 6 Archive leaderboard report
Semantic Textual Similarity SentEval InferSent STS 75.8/75.5 #2 of 6 Archive leaderboard report

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