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Found 2 papers, 1 papers with code
ConIsI: A Contrastive Framework with Inter-sentence Interaction for Self-supervised Sentence Representation
To conquer these issues, we propose a novel Contrastive framework with Inter-sentence Interaction (ConIsI), which introduces a sentence-level objective to improve sentence representation based on contrastive learning by fine-grained interaction between sentences.
SimCLF: A Simple Contrastive Learning Framework for Function-level Binary Embeddings
A practical embedding learning framework relies on the robustness of the assembly code representation and the accuracy of function-pair annotation, which is traditionally accomplished using supervised learning-based frameworks.
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