Abstract
Sentence embedding methods have made remarkable progress, yet they still struggle to capture the implicit semantics within sentences. This can be attributed to the inherent limitations of conventional sentence embedding methods that assign only a single vector per sentence. To overcome this limitation, we propose DualCSE, a sentence embedding method that assigns two embeddings to each sentence: one representing the explicit semantics and the other representing the implicit semantics. These embeddings coexist in the shared space, enabling the selection of the desired semantics for specific purposes such as information retrieval and text classification. Experimental results demonstrate that DualCSE can effectively encode both explicit and implicit meanings and improve the performance of the downstream task.
Abstract (translated)
句子嵌入方法已经取得了显著的进步，但仍难以捕捉句子中的隐含语义。这可以归因于传统句子嵌入方法固有的限制，即每句话仅分配一个向量。为了克服这一局限性，我们提出了一种名为DualCSE的句子嵌入方法，该方法为每个句子分配两个嵌入：一个是表示显式语义的嵌入，另一个是表示隐含语义的嵌入。这些嵌入共存于共享空间中，从而可以在诸如信息检索和文本分类等特定用途下选择所需的语义。实验结果表明，DualCSE能够有效地编码显性和隐性含义，并提高下游任务的表现。
URL
https://arxiv.org/abs/2510.09293
