Improved graph contrastive learning for short text classification[C]//Proceedings of the AAAI Conference on Artificial Intelligence. 2024, 38(17): 18716-18724. GIFT模型的github网址 整体框架图 首先,构建一个由Gw、Ge和Gp三个分量图组成的异构图。 然后对每个分量图进行GCNs,分别得到更新后的节点嵌入Hw、...
将摘要抽取模型训练的目标分布变成不确定的分布，其核心就是利用对比学习（contrastive learning）来构建一...
SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization,ACL2021,论文链接 4.1 提出问题 1)exposure bias,具体就是teacher-forcing导致误差累积 2)MLE的训练方式和ROUGE评估方式不匹配 为了解决这些问题,作者引入了一种基于对比学习的打分模型,通过先生成,再打分两阶段的方式,直接学习评价指标...
Official code for "GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models". GAugLLM is a novel framework for augmenting TAGs, leveraging advanced large language models like Mistral to enhance self-supervised graph learning. Pipeline of the GAugLLM The learn...
flux ocr transformers gemini supervision mistral xai textgeneration rag groq stable-diffusion anthropic llamacpp comfyui koboldcpp ollama lmstudio graphrag omost Updated Nov 27, 2024 Python yxuansu / SimCTG Star 466 Code Issues Pull requests [NeurIPS'22 Spotlight] A Contrastive Framework...
Contrastive learning trains a representation learning model by generating instances that exhibit either similarity or dissimilarity, so that a more general representation can be learned with a small number of samples. In this paper, we propose to directly integrate the word similarity matrix into BERT...
Contrastive learning 对比学习 Negative data augmentation 负数据增强 Augmentation controllers 增强控制器 Adversarial augmentation 对抗性增强 Stacking augmentations 堆叠增强 Tokenization Position embeddings Offline and online augmentation Curriculum learning 课程学习 ...
In the section, Practical Considerations for Implementation, we will present the use of consistency regularization and contrastive learning to further enforce the use of augmented data in training. Building on these ideas, we can use graph-structures to assign nearest neighbor assignments and regularize...
Keywords and Instances: A Hierarchical Contrastive Learning Framework Unifying Hybrid Granularities for Text Generation 收录会议: ACL 2022 论文链接: https://aclanthology.org/2022.acl-long.304.pdf 一. 动机 文本生成任务通常采用 teacher forcing 的方式进行训练,这种训练方式使得模型在训练过程中只能见到正样本...
Firstly, we transform the knowledge graph into a database of subgraph vectors and propose a BFS-style subgraph sampling strategy to avoid information loss, leveraging the analogy between BFS and the message-passing mechanism. In addition, we propose a bidirectional contrastive learning approach for ...