几篇论文实现代码:《Knowledge-Enhanced Ensemble Learning for Word Embeddings》(WWW 2019) GitHub:http://t.cn/EtMJ0yE 《Exposure: A White-Box Photo Post-Processing Framework》(SIGGRAPH 2018) GitHub:...
Knowledge-enhanced multi-task recommendation in hyperbolic space Multi-task learning has recently inspired a series of fruitful research in the field of recommendation due to its ability to handle complex scenarios by as... J Zhu,Y Zhang,RYM Wang - Applied Intelligence: The International Journal ...
1 概览 HTML, arXiv, Github, bilibili. 2023-07-23. (AI4Med Series) Knowledge-enhanced Multimodal Foundation Model in Medicine Abstract: While multi-modal foundation models pre-trained on large-scale …
This paper proposes a knowledge-enhanced deep reinforcement learning (DRL) method for intelligent ELS. Firstly, the Markov decision process (MDP) of the knowledge-enhanced DRL model for ELS is established based on transie...
论文来自于百度在2020年AAAI上提出的知识增强视觉-语言预训练模型 《ERNIE-ViL: Knowledge Enhanced Vision-Language Representations Through Scene Graph》,在多个比赛上获得了 SOTA 的结果。 我们在看 CLIP 的时候,可能会震惊于 4亿的训练数据 和 大量的训练资源。 过多的数据导致数据质量可能层次不齐,而大量的 GP...
Technology-enhanced learning in the workplace These emerging technologies fundamentally change our contemporary understanding, and allow a more prominent position of workplace learning in today's human resource development policies.This chapter commences with exploring the concept of work... VDK Marcel,H...
Down syndromeintellectual disabilitylanguageletter–sound correspondencereadingChildren with Down syndrome and severe intellectual disability have difficulties in learning a language. Enhanced learning procedure, including mora segmentation is beneficial to understand letter–sound correspondence in such children....
关键词:预训练模型,knowledge-Enhanced NLP, Knowledge Embedding,GNN 1.背景及问题描述 之前的一些knowledge-Enhanced预训练语言模型,一般都是使用浅层的、静态的并且独立训练的实体embedding,如TransE等,直接融入到预训练模型中,并且实体embedding也不参与训练,他们之间是天然存在gap的。而一些task,比如实体链接、关系抽取...
learning, researchers have tried to leverage deep neural networks to boost tasks’ performances with dynamic semantic embeddings. At first, people were still limited to the paradigm of supervised learning and thought without enough labeled data it would be difficult to unleash the potential of deep ...
2)KEMLP的 accuracy 指数级收敛于1 3) 当逻辑模型的稳健性有保证时,KEMLP的能力强于主任务模型 文章的理论结果 文章通过引入逻辑关系和推断相关因子的辅助模型来帮助机器学习模型提升应对对抗样本的能力,对于 Learning with logic、Robust Learning 具有启发意义。