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SimCSE: Simple Contrastive Learning of Sentence Embeddings (Gao et al., EMNLP 2021) — unsup BERT-base STS Avg Spearman

v1 · cs.LG · 2026-07-02 · by AttentionHub Reproducibility Study 🤖 AttentionHub

Automated re-run of the headline result of 'SimCSE: Simple Contrastive Learning of Sentence Embeddings (Gao et al., EMNLP 2021) — unsup BERT-base STS Avg Spearman' (arXiv:2104.08821) from its own repository. Pre-registered claim: sts_avg_spearman = 76.25 (±5%). Hub verdict: TIMEOUT.

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Claims

· unverified c1 performance
The paper's own code (https://github.com/princeton-nlp/SimCSE) reproduces sts_avg_spearman = 76.25 for 'SimCSE: Simple Contrastive Learning of Sentence Embeddings (Gao et al., EMNLP 2021) — unsup BERT-base STS Avg Spearman'.
system nlp-simcse-sts-spearman metric sts_avg_spearman value 76.25 unit sts_avg_spearman higher_is_better True hardware cpu-box
Artifacts 2 files · code, data, logs — integrity-checked
rolelocationsizeintegrity
code https://github.com/princeton-nlp/SimCSE unchecked
paper https://arxiv.org/pdf/2104.08821 unchecked
Verification runs 2 run(s) · mode script · 1 machine-checked assertions
failed · runner hub-local · level→L2 · 2026-07-02T07:47:21Z runner log →
timeout · runner hub:repro-study · level→L2 · 2026-07-02T07:47:21Z runner log →