Alignment 指标思想:微观,计算语义完全相同的文本对的对齐程度。 实验细节:可以制作一批测试集,也可以用公开的数据集,如PAWS语序对抗问题匹配数据集,把里面label=1(label=1表示语义相同)的文本对拿出来,用模型计算文本对的距离,距离越近,表现模型在Alignment上表现越高 指标细节:对齐度越高越好,但考虑到各向异性,就算...
论文阅读-Ovis:Structural Embedding Alignment for Multimodal Large Language Model 一抹清水画夕阳 创作声明:包含 AI 辅助创作 2 人赞同了该文章 动机 MLLM 中两种模态的嵌入策略之间的不对齐——基于嵌入查找表的结构文本嵌入和视觉编码器直接生成的连续嵌入——对视觉和文本信息的无缝融合提出了挑战。我们提出了Ovi...
表示分可以为两种:联合表示 Joint representations 和协调表示 Coordinated representations。 联合表示是将不同模态的数据映射到同一个向量中去表示;协调表示则是让不同模态的数据就存在自己的向量,这些向量是多模态表示的子空间,我们应该找到一种方式去让不同模式的向量进行对应,这也就是在一个研究重点Alignment。 Align...
Embedding alignmentIn recent years, dynamic graph embedding has attracted a lot of attention due to its usefulness in real-world scenarios. In this paper, we consider discrete-time dynamic graph representation learning, where embeddings are computed for each time window, and then are aggregated to ...
Unified Embedding Alignment with Missing Views Inferring for Incomplete Multi-View Clustering Info AAAI 2019 Jie Wen 论文介绍 摘要 现存的多视图缺失聚类问题的缺陷: 底层语义信息通常被忽略 数据局部结构没有被很好的探索 不同视图之间的重要性没有被有效的评估 ...
To address this, we introduce Supervised Embedding Alignment (SEA), a token-level alignment method that leverages vision-language pre-trained models, such as CLIP, to align visual tokens with the LLM's embedding space through contrastive learning. This approach ensures a more coherent integration ...
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Protein sequence alignment is a key component of most bioinformatics pipelines to study the structures and functions of proteins. Aligning highly divergent sequences remains, however, a difficult task that current algorithms often fail to perform accurat
图5.2. 现有模型的alignment和uniformity指标对比 如图所示,可以发现性能更优的模型通常有着更好的alignment和uniformity,BERT虽然有很好的alignment,但uniformity太差,而基于后处理的BERT-flow和BERT-whitening又恰恰走向了另一个极端,本文提出的SimCSE则是对这两个指标的一个很好的平衡,加入监督训练后,SimCSE的两个指标会...
3. DecomposableAttention:这篇论文的核心就是alignment,即词与词的对应关系,文中的alignment用在了两个地方,一个attend部分,是用来计算两个句子之间的attention关系,另一个是compare部分,对两个句子之间的词进行比较,每次的处理都是以词为单位的,最后用前馈神经网络去做预测。很明显可以看到,这篇文章提到的模型并没...