Semantic textual similarity with human-annotated sentence pairs
3 results indexed across 1 metric. Shaded row marks current SOTA; ties broken by submission date.
| # | Model | Org | Submitted | Paper / code | spearman |
|---|---|---|---|---|---|
| 01 | GTE-Qwen2-7B-instructOSS | Alibaba | Jun 2024 | arxiv | 88.40 |
| 02 | E5-Mistral-7B-instructOSS | Microsoft | Jan 2024 | Improving Text Embeddings with Large Language Models | 84.70 |
| 03 | all-MiniLM-L6-v2OSS | Sentence-Transformers | Jan 2022 | arxiv | 82.80 |
Each row below marks a model that broke the previous record on spearman. Intermediate submissions are kept in the leaderboard above; only SOTA-setting entries are re-listed here.
Higher scores win. Each subsequent entry improved upon the previous best.
Every paper below corresponds to at least one row in the leaderboard above. Click through for the arXiv preprint and, when available, the reference implementation.
Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.