问答技术

【论文简介】KQA Pro：带有可解释性程序和准确SPARQL的大规模知识库问答数据集
https://zhuanlan.zhihu.com/p/352808683

[论文解读]KQA Pro 一个120K有SPARQL标注的KBQA数据集
https://zhuanlan.zhihu.com/p/348851375

https://github.com/BDBC-KG-NLP/QA-Survey-CN

https://github.com/shijx12/KQAPro_Baselines

华为史佳欣：基于知识图谱的复杂问题推理问答
http://www.uml.org.cn/ai/202205311.asp

针对复杂问题的知识图谱问答最新进展
https://zhuanlan.zhihu.com/p/134090164

复杂知识图谱问答综述方法、挑战和解决办法
https://blog.csdn.net/u011983997/article/details/122727274

复杂问题的知识问答技术介绍
https://zhuanlan.zhihu.com/p/184966381

论文导读 | 基于查询图生成的复杂知识图谱问答
https://www.modb.pro/db/403452

CIKM 2020 | 知识库问答复杂问题的分层查询图生成方法
https://blog.csdn.net/c9Yv2cf9I06K2A9E/article/details/109567445

ACL2020 KBQA 基于查询图生成回答多跳复杂问题
https://blog.csdn.net/devcloud/article/details/108772855

TED对话策略：Dialogue Transformers
https://zhuanlan.zhihu.com/p/483823239

DIET: Lightweight Language Understanding for Dialogue System
https://blog.csdn.net/weixin_42486623/article/details/122198536

kopl
https://kopl.xlore.cn/doc/0_intro.html

KoPL：面向知识的推理问答编程语言
https://xw.qq.com/cmsid/20211110A06TZR00


ProgramTransfer：基于知识库的复杂问答
https://zhuanlan.zhihu.com/p/499048106

TransferNet：一个用于关系图多跳问答的透明有效框架
https://zhuanlan.zhihu.com/p/498409048

QQ浏览器智能问答技术探索实践
https://zhuanlan.zhihu.com/p/413822447

美团知识图谱问答技术实践与探索
https://zhuanlan.zhihu.com/p/429816769

斯坦福任泓宇：知识图谱多步推理及SMORE框架介绍
https://zhuanlan.zhihu.com/p/546169083

CCKS 2019 | 基于知识图谱的寿险问答系统
https://zhuanlan.zhihu.com/p/89983691

对话动作集定义CUED Standard Dialogue Acts
https://blog.csdn.net/iin729/article/details/109221672

项目实操：KBQA常规实现流程与医疗知识图谱问答源码解读
https://blog.csdn.net/asd8705/article/details/125059552

EMNLP 2019 结合单词级别意图识别的stack-propagation框架进行口语理解
https://zhuanlan.zhihu.com/p/85792864

【论文解读系列】NER方向：SoftLexicon(ACL 2020)
https://blog.csdn.net/ljp1919/article/details/126742431

杨韬：微信搜一搜中的智能问答技术
https://zhuanlan.zhihu.com/p/530648272

2021-ACL论文：问答检索方向论文整理
https://zhuanlan.zhihu.com/p/388148753

智能客服FAQ问答任务的技术选型探讨
https://zhuanlan.zhihu.com/p/50799128

智能问答系统：问句预处理、检索和深度语义匹配技术
https://zhuanlan.zhihu.com/p/70203821

MGIMN：用于Few-shot文本分类的多粒度交互式匹配网络
https://blog.csdn.net/be_humble/article/details/127652630

https://github.com/ymcui/expmrc

知识库问题生成（KBQG）技术介绍
https://zhuanlan.zhihu.com/p/274735752?utm_source=wechat_session

A Review on Question Generation from Natural Language Text阅读笔记
https://blog.csdn.net/Cc2018qaq/article/details/121973874

BERTScore: Evaluating Text Generation with BERT
https://arxiv.org/abs/1904.09675v3

问题生成领域的评估
https://zhuanlan.zhihu.com/p/569381350

面向文本生成任务的评估指标
https://zhuanlan.zhihu.com/p/380929670

文本生成13：万字长文梳理文本生成评价指标
https://zhuanlan.zhihu.com/p/144182853

Active Evaluation: Efficient NLG Evaluation with Few Pairwise Comparisons
https://arxiv.org/abs/2203.06063

Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation Practices for Generated Text
https://arxiv.org/abs/2202.06935

Analyzing and Evaluating Faithfulness in Dialogue Summarization
https://arxiv.org/abs/2210.11777

基于深度神经网络的自动问题生成
https://zhuanlan.zhihu.com/p/393610558

Question Generation
https://paperswithcode.com/task/question-generation

A Survey of Evaluation Metrics Used for NLG Systems
https://arxiv.org/abs/2008.12009

中文机器阅读理解（片段抽取）数据集整理
https://zhuanlan.zhihu.com/p/395788175

Question-Generation-Paper-List
https://github.com/teacherpeterpan/Question-Generation-Paper-List

Assisting the Human Fact-Checkers: Detecting All Previously Fact-Checked Claims in a Document
https://arxiv.org/abs/2109.07410

临床问答中领域适配的多样化问题生成
https://zhuanlan.zhihu.com/p/342603647

Asking Questions the Human Way: Scalable Question-Answer Generation from Text Corpus
https://paperswithcode.com/paper/asking-questions-the-human-way-scalable

以文档为额外知识的生成式对话
https://www.jiqizhixin.com/articles/2020-09-23-2

https://github.com/sherlcok314159/ChineseMRC-Data

Fusion-in-decoder 生成式答案踩坑
https://zhuanlan.zhihu.com/p/603091623

Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering
https://arxiv.org/abs/2007.01282
https://github.com/facebookresearch/FiD

Fusion-in-Decoder (FiD) 简读
https://zhuanlan.zhihu.com/p/564043932

基于检索的自然语言处理模型研究梳理
https://blog.csdn.net/Kaiyuan_sjtu/article/details/123059539

ACL-2022|Internet-Augmented Dialogue Generation
https://zhuanlan.zhihu.com/p/591603674

ReAct: Synergizing Reasoning and Acting in Language Models
https://arxiv.org/abs/2210.03629

信息搜索QA中的挑战：无法回答的问题和段落检索
https://zhuanlan.zhihu.com/p/580057408

QA-based事实一致性检测与改进综述
https://zhuanlan.zhihu.com/p/285770986

ChatGPT作为知识库问答系统的问答能力评测
https://zhuanlan.zhihu.com/p/613649876

Ask what's missing and what's useful: Improving Clarification Question Generation using Global Knowledge
https://arxiv.org/abs/2104.06828


RoR: Read-over-Read for Long Document Machine Reading Comprehension
https://arxiv.org/abs/2109.04780


Answering while Summarizing: Multi-task Learning for Multi-hop QA with Evidence Extraction
https://blog.csdn.net/qq_36426650/article/details/117589980
https://arxiv.org/abs/1905.08511

Learning to Retrieve In-Context Examples for Large Language Models
https://arxiv.org/abs/2307.07164


《Learning To Retrieve Prompts for In-Context Learning 》论文阅读
https://zhuanlan.zhihu.com/p/530531916

RecallM: An Architecture for Temporal Context Understanding and Question Answering
https://arxiv.org/abs/2307.02738


Transformer Memory as a Differentiable Search Index
https://zhuanlan.zhihu.com/p/633411368

ChatGPT时代，垂直搜索如何破？
https://blog.csdn.net/VucNdnrzk8iwX/article/details/129722260

A Unified Generative Retriever for Knowledge-Intensive Language Tasks via Prompt Learning
https://arxiv.org/abs/2304.14856

Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation
https://arxiv.org/abs/2206.10128

Understanding Differential Search Index for Text Retrieval
https://arxiv.org/abs/2305.02073

Self-Polish: Enhance Reasoning in Large Language Models via Problem Refinement
https://arxiv.org/abs/2305.14497