recommendation time-aware knowledge reasoning
论文解读（AAD）《Knowledge distillation for BERT unsupervised domain adaptation》
Note：[ wechat：Y466551 | 可加勿骚扰，付费咨询 ] 论文信息 论文标题：Knowledge distillation for BERT unsupervised domain adaptation论文作者：Minho Ryu、Geonseok Lee、Kichun Lee论文来 ......
论文解读（Moka‑ADA）《Moka‑ADA: adversarial domain adaptation with model‑oriented knowledge adaptation for cross‑domain sentiment analysis》
Note：[ wechat：Y466551 | 可加勿骚扰，付费咨询 ] 论文信息 论文标题：Moka‑ADA: adversarial domain adaptation with model‑oriented knowledge adaptation for cross‑domain senti ......
Knowledge-QA-LLM: 基于本地知识库+LLM的问答系统
## ⚠️注意：后续更新，请移步[README](https://github.com/RapidAI/Knowledge-QA-LLM) ## Knowledge QA LLM =3.8, - 基于本地知识库+LLM的问答系统。该项目的思路是由[langchain-ChatGLM](https:/ ......
RabbitMQ Exception (403) Reason: "no access to this vhost"
可能原因： 1）没有配置该用户的访问权限,可以通过rabbitmqctl add_vhost admin来添加，并赋予权限： rabbitmqctl set_permissions -p 用户名 admin "." "." ".*" 代码在连接的时候，必须制定对应的vhost，否则是没有访问权限：c ......
ACM-knowledge <bitset>
关于bitset，详见[参考](https://www.cnblogs.com/yifusuyi/p/10072729.html)； ```cpp #include #include using namespace std; using LL = long long; int main() { bi ......
《STaR: Self-Taught Reasoner Bootstrapping Reasoning With Reasoning》论文学习
一、Introduction 受到人类做决策的思维过程的启发，即通过将一个问题逐个分解为多个子问题，并按照链式的方式串行思考，最终得到思考结果，这个过程被成为”思维链（chain-of-thoughts）“。 研究表明，中间推理过程（intermediate reasoning (“rational ......
Large Language Models are Zero-Shot Reasoners
[TOC] > [Kojima T., Gu S. S., Reid M., Matsuo Y. and Iwasawa Y. Large language models are zero-shot reasoners. NIPS, 2022.](http://arxiv.org/abs/2205. ......
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
[TOC] > [Wei J., Wang X., Schuurmans D., Bosma M., Ichter B., Xia F., Chi E. H., Le Q. V. and Zhou D. Chain-of-thought prompting elicits reasoning in ......
解决PHP Warning: putenv() has been disabled for security reasons in phar:
在使用composer的时候报一下错误，这是因为php禁用了putenv() 函数 PHP Warning: putenv() has been disabled for security reasons in phar:///usr/bin/composer/vendor/composer/xde ......
Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions
[TOC] > [Trivedi H., Balasubramanian N., Khot T., Sabharwal A. Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-st ......
【861】R programming related knowledge
Ref: R 字符串 Ref: R语言遍历文件和批量输出文件 head(x, n)Returns the first or last parts of a vector, matrix, table, data frame or function. Since head() and tail() a ......
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
[TOC] > [Lewis P. and Perez E., et al. Retrieval-augmented generation for knowledge-intensive nlp tasks. NIPS, 2020.](http://arxiv.org/abs/2005.11401) ......
Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning
图的作用： 图结构捕捉不同类型节点（即用户、项目和属性）之间丰富的关联信息，使我们能够发现协作用户对属性和项目的偏好。因此，我们可以利用图结构将推荐和对话组件有机地整合在一起，其中对话会话可以被视为在图中维护的节点序列，以动态地利用对话历史来预测下一轮的行动。 由四个主要组件组成：基于图的 MDP ......
粗读Multi-Task Recommendations with Reinforcement Learning
论文： Multi-Task Recommendations with Reinforcement Learning 地址： https://arxiv.org/abs/2302.03328 # 摘要 In recent years, Multi-task Learning (MTL) has yi ......
Query2box Reasoning over Knowledge Graphs in Vector Space using Box Embeddings
[TOC] > [Ren H., Hu W. and Leskovec J. Query2box: Reasoning over knowledge graphs in vector space using box embeddings. ICLR, 2020.](http://arxiv.org/ ......
MEANTIME Mixture of Attention Mechanisms with Multi-temporal Embeddings for Sequential Recommendation
[TOC] > [Cho S., Park E. and Yoo S. MEANTIME: Mixture of attention mechanisms with multi-temporal embeddings for sequential recommendation. RecSys, 20 ......
《ReAct: SYNERGIZING REASONING AND ACTING IN LANGUAGE MODELS》论文学习
一、论文主要思想 本文首先认为，到目前为止，LLM 在语言理解方面令人印象深刻，它们已被用来生成 CoT（思想链）来解决一些问题，它们也被用于执行和计划生成。 尽管这两者是分开研究的，但本文旨在以交错的方式将推理和行动结合起来，以提高LLM的表现。 这个想法背后的原因是，如果你考虑一下作为一个人，你 ......
Memory Augmented Graph Neural Networks for Sequential Recommendation
[TOC] > [Ma C., Ma L., Zhang Y., Sun J., Liu X. and Coates M. Memory augmented graph neural networks for sequential recommendation. AAAI, 2021.](http: ......
关于Deep Neural Networks for YouTube Recommendations的一些思考和实现
作者自己实现该文章的时候遇到的一些值得思考的地方： - [关于Deep Neural Networks for YouTube Recommendations的一些思考和实现](https://cloud.tencent.com/developer/article/1170340) - [备份网址] ......
pycharm中的gihub copilot中报错Sign in failed. Reason: Request signInInitiate failed with message: getaddri无法使用问题
pycharm中的gihub copilot中报错Sign in failed. Reason: Request signInInitiate failed with message: getaddri无法使用问题 解决方法:idea打开我们的插件 settings-plugins-找到插件，点击h ......
Graph Masked Autoencoder for Sequential Recommendation
[TOC] > [Ye Y., Xia L. and Huang C. Graph masked autoencoder for sequential recommendation. SIGIR, 2023.](http://arxiv.org/abs/2305.04619) ## 概 图 + MA ......
混合性对话：Towards Conversational Recommendation over Multi-Type Dialogs
## 混合型对话 传统的人机对话研究专注于单一类型的对话，并且往往预设用户一开始就清楚对话目标。但实际应用中，人机对话常常混合了多种类型，例如闲聊、任务导向对话、推荐对话、问答等，并且用户目标是未知的。在这样的混合型对话中，机器人需要主动自然地进行对话推荐。 “混合型对话”这个新颖的任务于2020年 ......
Time Interval Aware Self-Attention for Sequential Recommendation
[TOC] > [Li J., Wang Y., McAuley J. Time interval aware self-attention for sequential recommendation. WSDM, 2020.](https://dl.acm.org/doi/10.1145/3336 ......
使用Postman的Get请求遇到："type": "parsing_exception","reason": "Unknown key for a START_OBJECT in [mappings].",的问题
**错误如图**  **原因** postman自身的的bug问题。body里面写了json参数，结果postma ......
Exploiting Positional Information for Session-based Recommendation
[TOC] > [Qiu R., Huang Z., Chen T. and Yin H. Exploiting positional information for session-based recommendation. ACM Transactions on Information Syst ......
Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation
[TOC] > [Qiu R., Huang Z., Ying H. and Wang Z. Contrastive learning for representation degeneration problem in sequential recommendation. WSDM, 2022.] ......
Incrementer：Transformer for Class-Incremental Semantic Segmentation with Knowledge Distillation Focusing on Old Class论文阅读笔记
## 摘要 目前已有的连续语义分割方法通常基于卷积神经网络，需要添加额外的卷积层来分辨新类别，且在蒸馏特征时没有对属于旧类别/新类别的区域加以区分。为此，作者提出了基于Transformer的网络incrementer，在学习新类别时只需要往decoder中加入对应的token。同时，作者还提出了对 ......
读书笔记: Psychological Power between knowledge and practice; Inverted Totalitarianism;
John Dewey once remarked that equality becomes dangerous when it is widely praised but empty in practice. Perhaps the most crucial element in the stru ......
Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation
[TOC] > [Xia X., Yin H., Yu J., Wang Q., Cui L and Zhang X. Self-supervised hypergraph convolutional networks for session-based recommendation. AAAI, ......
Self-Supervised Graph Co-Training for Session-based Recommendation
[TOC] > [Xia X., Yin H., Yu J., Shao Y. and Cui L. Self-supervised graph co-training for session-based recommendation. CIKM, 2021.](http://arxiv.org/a ......