Bi-Encoder和Cross-Encoder的准确性和效率比较研究有哪些? Bi-Encoder和Cross-Encoder的准确性和效率比较研究表明,虽然Cross-Encoder通常被认为在准确性上表现更好,但Bi-Encoder模型在处理句子嵌入方面具有优势。具体来说: 效率方面:Bi-Encoder模型因为可以在查询时间之前对所有文档进行预处理而非常高效。这意味着它们能够...
Bi-encoder和Cross-encoder是在自然语言理解任务模型的两种不同方法,在信息检索和相似性搜索二者的使用更为广泛。在LLM大火的今天,RAG的pipe line中这两个模块作为提升检索精度的模块更是备受瞩目。 使用哪个: Bi-encoder:当您拥有大规模数据集和计算资源时,使用Bi-encoder。由于相似性得分可以独立计算,它们在推理期间...
Cross-Encoder:同时将两个句子传递给 Transformer 网络。它产生一个介于 0 和 1 之间的输出值,表示输入句对的相似性。不产生句子的 embedding。并且,无法将单个句子传递给Cross-Encoder。 论文解释:Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks Cross-Encoder比双编码器实现更好的性能。然而,对于许...
Bi-Encoder 和 Cross-Encoder 原理示意图 Bi-Encoder 和 Cross-Encoder 原理示意图 Retrieve & Re-Rank Pipeline 结合Bi-Encoder 和 Cross-Encoder pipeline 示意图 参考: Sentence-Transformers 文档 使用样例:
https://wanger-sjtu.github.io/encoder-cross-bi/ Wanger-SJTU added Gitalk 00b3bb178817a706ffc09289b578896d labels Jun 2, 2024 Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment Assignees No one assigned Labels 00b3bb178817a706ffc09289b57...
q_reps= self.encode(query)#两个encoder分别求embedding,这是模型叫Bi双塔的原因p_reps =self.encode(passage)ifself.training:ifself.negatives_cross_deviceandself.use_inbatch_neg: q_reps=self._dist_gather_tensor(q_reps) p_reps=self._dist_gather_tensor(p_reps) ...
elasticsearchpandaspytorchindexerchinesecosbm25sentence-embeddingsfaisssentence-transformersbi-encodercross-encoder UpdatedFeb 18, 2024 Python lemuria-wchen/CFC Star10 Code Issues Pull requests Code and created datasets for our ACL 2022 paper: "Contextual Fine-to-Coarse Distillation for Coarse-grained Respons...
Although mining the informative pairs is of central importance to training a ranking model, the current dominating ranking model, Cross-Encoder (CE), processes image-text pair jointly with cross-attention mechanisms, imposing O(N~2) encoding complexity. Consequently, with limited computational ...
A BERT-based Neural Ranking Model (NRM) can be either a crossencoder or a bi-encoder. Between the two, bi-encoder is highly efficient because all the documents can be pre-processed before the actual query time. In this work, we show two approaches for improving the performance of BERT-ba...
首先,我们简单的介绍下概念:所谓Bi-Encoder,先分别计算两个句子的特征,然后计算特征的相似度 (比如cosine similarity);而Cross-Encoder,是将两句话一起输入模型,可以直接输出两个句子的语义一致性得分。一般来说Cross-Encoder效果会优于Bi-Encoder,但是Cross-Encoder的计算量要大得多(参考【3】)。 图片来自https://...