<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title>Bing: Conversation Knowledge Graph</title><link>http://www.bing.com:80/search?q=Conversation+Knowledge+Graph</link><description>Search results</description><image><url>http://www.bing.com:80/s/a/rsslogo.gif</url><title>Conversation Knowledge Graph</title><link>http://www.bing.com:80/search?q=Conversation+Knowledge+Graph</link></image><copyright>Copyright © 2026 Microsoft. All rights reserved. These XML results may not be used, reproduced or transmitted in any manner or for any purpose other than rendering Bing results within an RSS aggregator for your personal, non-commercial use. Any other use of these results requires express written permission from Microsoft Corporation. By accessing this web page or using these results in any manner whatsoever, you agree to be bound by the foregoing restrictions.</copyright><item><title>Advanced Memory in LangChain - Comet</title><link>https://www.comet.com/site/blog/advanced-memory-in-langchain/</link><description>Knowledge Graph Memory ConversationKGMemory, also known as Conversation Knowledge Graph Memory, is a feature in LangChain that allows the model to store and retrieve information as a knowledge graph.</description><pubDate>Wed, 08 Apr 2026 05:31:00 GMT</pubDate></item><item><title>GitHub - XiaoMi/C3KG</title><link>https://github.com/XiaoMi/C3KG</link><description>Existing commonsense knowledge bases often organize tuples in an isolated manner, which is deficient for commonsense conversational models to plan the next steps. To fill the gap, we curate a large-scale multi-turn human-written conversation corpus, and create the first Chinese commonsense conversation knowledge graph which incorporates both social commonsense knowledge and dialog flow ...</description><pubDate>Thu, 02 Apr 2026 23:25:00 GMT</pubDate></item><item><title>Billion-scale pre-trained knowledge graph model for conversational ...</title><link>https://www.sciencedirect.com/science/article/pii/S092523122401124X</link><description>First, a billion-scale conversation knowledge graph is constructed, inspired by real-world application scenarios. Then, the conversation knowledge graph is pretrained to capture the semantic and structure information respectively.</description><pubDate>Sat, 14 Mar 2026 15:34:00 GMT</pubDate></item><item><title>C3 KG: A Chinese Commonsense Conversation Knowledge Graph</title><link>https://aclanthology.org/2022.findings-acl.107.pdf</link><description>Abstract Existing commonsense knowledge bases often organize tuples in an isolated manner, which is deficient for commonsense conversational mod-els to plan the next steps. To fill the gap, we cu-rate a large-scale multi-turn human-written con-versation corpus, and create the first Chinese commonsense conversation knowledge graph which incorporates both social commonsense knowledge and dialog ...</description><pubDate>Mon, 30 Mar 2026 09:17:00 GMT</pubDate></item><item><title>C3KG：中文常识对话知识图谱 - 知乎</title><link>https://zhuanlan.zhihu.com/p/501111403</link><description>论文题目：C3KG: A Chinese Commonsense Conversation Knowledge Graph [1] 该文章是小米AI实验室发表在ACL2022会议上的一篇论文，因为现有的常识知识库是以孤立的方式组织元组，这对于常识对话模型 目标规划 是不够的。 因此，作者构建了多轮人工对话语料库，并创建了第一个结合了社会常识知识和对话流信息的 ...</description><pubDate>Wed, 01 Apr 2026 14:58:00 GMT</pubDate></item><item><title>C3KG: A Chinese Commonsense Conversation Knowledge Graph</title><link>https://ar5iv.labs.arxiv.org/html/2204.02549</link><description>To fill the gap, we curate a large-scale multi-turn human-written conversation corpus, and create the first Chinese commonsense conversation knowledge graph which incorporates both social commonsense knowledge and dialog flow information.</description><pubDate>Sun, 01 Mar 2026 18:41:00 GMT</pubDate></item><item><title>More Than Just A Conversation: A Multi-agent Reasoning Graph Knowledge ...</title><link>https://dl.acm.org/doi/abs/10.1145/3726302.3730232</link><description>To fully leverage the in-context learning capabilities of LLMs, we design a reasoning knowledge editing mechanism that internalizes new information by aligning the output distribution of smaller language models with both the conversational history and the knowledge derived from the multi-agent reasoning graph.</description><pubDate>Wed, 08 Apr 2026 11:15:00 GMT</pubDate></item><item><title>C3KG: A Chinese Commonsense Conversation Knowledge Graph</title><link>https://openreview.net/pdf?id=U9KwypIe7yU</link><description>Abstract Existing commonsense knowledge bases often organize tuples in an isolated manner, which is deficient for commonsense conversational mod-els to plan the next steps. To fill the gap, we cu-rate a large-scale multi-turn human-written con-versation corpus, and create the first Chinese commonsense conversation knowledge graph which incorporates both social commonsense knowledge and dialog ...</description><pubDate>Tue, 17 Mar 2026 08:13:00 GMT</pubDate></item><item><title>C3KG: A Chinese Commonsense Conversation Knowledge Graph</title><link>https://www.researchgate.net/publication/359786494_C3KG_A_Chinese_Commonsense_Conversation_Knowledge_Graph</link><description>To fill the gap, we curate a large-scale multi-turn human-written conversation corpus, and create the first Chinese commonsense conversation knowledge graph which incorporates both social ...</description><pubDate>Fri, 01 Dec 2023 08:47:00 GMT</pubDate></item><item><title>Conversation Knowledge Graph Memory — LangChain 0.0.107</title><link>https://langchain-doc.readthedocs.io/en/latest/modules/memory/types/kg.html</link><description>Conversation Knowledge Graph Memory # This type of memory uses a knowledge graph to recreate memory. Let’s first walk through how to use the utilities</description><pubDate>Sat, 04 Apr 2026 05:22:00 GMT</pubDate></item></channel></rss>