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license: apache-2.0

mutual information Contrastive Sentence Embedding (miCSE):

arXiv Language model of the pre-print arXiv paper titled: "miCSE: Mutual Information Contrastive Learning for Low-shot Sentence Embeddings"

Training miCSE imposes alignment between the attention pattern of different views during contrastive learning. Learning sentence embeddings with miCSE entails enforcing the syntactic consistency across augmented views for every single sentence, making contrastive self-supervised learning more sample efficient.

Benchmark

Model results on SentEval Benchmark:

+-------+-------+-------+-------+-------+--------------+-----------------+--------+                                               
| STS12 | STS13 | STS14 | STS15 | STS16 | STSBenchmark | SICKRelatedness | S.Avg. |                                               
+-------+-------+-------+-------+-------+--------------+-----------------+--------+                                               
| 71.71 | 83.09 | 75.46 | 83.13 | 80.22 |    79.70     |      73.62      | 78.13  |                                               
+-------+-------+-------+-------+-------+--------------+-----------------+--------+  

Authors: