近几年有关大语言模型推荐系统、会话推荐系统以及公平性相关的文献

# Literature-list-of-Recommender-Systems01 近几年有关大语言模型推荐系统、会话推荐系统以及公平性相关的文献 # 一、Conversation Recommender 会话推荐系统 - Unified conversational recommendation policy learning via graph-based reinforcement learning 通过基于图的强化学习进行统一的对话推荐策略学习 [SIGIR 2021] [(PDF)](https://arxiv.org/pdf/2105.09710.pdf) - Learning to ask appropriate questions in conversational recommendation 对会话推荐系统进行了重新定义，提出了一种基于KG的会话推荐系统KBQG [SIGIR 2021] [(PDF)](https://arxiv.org/pdf/2105.04774.pdf) [(code)](https://github.com/XuhuiRen/KBQG) - Improving conversational recommender systems via transformer-based sequential modelling 提出了一种基于变压器的序列会话推荐方法TSCR [SIGIR 2022] [(PDF)](https://personal.ntu.edu.sg/c.long/paper/22-SIGIR-conversation.pdf) - Variational Reasoning about User Preferences for Conversational Recommendation 关于会话推荐的用户偏好的变分推理 [SIGIR 2022] [(PDF)](https://staff.fnwi.uva.nl/m.derijke/wp-content/papercite-data/pdf/ren-2022-variational.pdf) - Hoops: Human-in-the-loop graph reasoning for conversational recommendation [SIGIR 2021] [(PDF)](https://par.nsf.gov/servlets/purl/10295248) [(code)](https://github.com/zuohuif/HOOPS) - User-centric conversational recommendation with multi-aspect user modeling 以用户为中心的基于多功能用户建模的对话推荐 [SIGIR 2022] [(PDF)](https://dl.acm.org/doi/pdf/10.1145/3477495.3532074) [(code)](https://github.com/lisk123/UCCR) - Learning to infer user implicit preference in conversational recommendation 在会话推荐中推断用户的隐式偏好 [SIGIR 2022] [(PDF)](https://scholar.archive.org/work/jwrl6j46n5ffjhwtdw6mud6re4/access/wayback/https://dl.acm.org/doi/pdf/10.1145/3477495.3531844) - Comparison-based conversational recommender system with relative bandit feedback 基于比较的会话推荐系统 [SIGIR 2021] [(PDF)](https://arxiv.org/pdf/2208.09837) - Analyzing and simulating user utterance reformulation in conversational recommender systems [SIGIR 2022] [(PDF)](https://arxiv.org/pdf/2205.01763) - MMConv: an environment for multimodal conversational search across multiple domains [SIGIR 2021] [(PDF)](https://dl.acm.org/doi/pdf/10.1145/3404835.3462970) [(code)](https://github.com/lizi-git/MMConv) - Challenges and research opportunities in ecommerce search and recommendations [SIGIR 2021] [(PDF)](https://assets.amazon.science/23/86/ca2f1a034fa084d524962af2fdaa/challenges-and-research-opportunities-in-ecommerce-search-and-recommendations.pdf) - On interpretation and measurement of soft attributes for recommendation 推荐软属性的解释与测量 [SIGIR 2021] [(PDF)](https://dl.acm.org/doi/pdf/10.1145/3404835.3462893) - Towards multi-modal conversational information seeking [SIGIR 2021] [(PDF)](https://www.researchgate.net/profile/Yashar-Deldjoo/publication/350958354_Towards_Multi-Modal_Conversational_Information_Seeking/links/609fcc49299bf147699cdd63/Towards-Multi-Modal-Conversational-Information-Seeking.pdf) - Simulating user satisfaction for the evaluation of task-oriented dialogue systems 模拟用户满意度评估面向任务的对话系统 [SIGIR 2021] [(PDF)](https://arxiv.org/pdf/2105.03748) [(code)](https://github.com/huggingface/transformers) - Asking clarifying questions based on negative feedback in conversational search [SIGIR 2021] [(PDF)](https://arxiv.org/pdf/2107.05760) [(code)](https://github.com/huggingface/transformers) - Tutorial on fairness of machine learning in recommender systems [SIGIR 2021] [(PDF)](https://fairness-tutorial.github.io/files/Tutorial_on_Fairness_in_Recommendation.pdf) - On Natural Language User Profiles for Transparent and Scrutable Recommendation [SIGIR 2022] [(PDF)](https://dl.acm.org/doi/pdf/10.1145/3477495.3531873) - Wizard of search engine: Access to information through conversations with search engines [SIGIR 2021] [(PDF)](https://arxiv.org/pdf/2105.08301) - Explainable fairness in recommendation [SIGIR 2022] [(PDF)](https://dl.acm.org/doi/pdf/10.1145/3477495.3531973) - Priming and actions: An analysis in conversational search systems [SIGIR 2023] [(PDF)](https://www.researchgate.net/profile/**ao-Fu-41/publication/370628441_Priming_and_Actions_An_Analysis_in_Conver-sational_Search_Systems/links/645a627239c408339b3798c8/Priming-and-Actions-An-Analysis-in-Conver-sational-Search-Systems.pdf) - Hierarchical multi-task graph recurrent network for next poi recommendation [SIGIR 2022] [(PDF)](https://dl.acm.org/doi/pdf/10.1145/3477495.3531989) - Curriculum contrastive context denoising for few-shot conversational dense retrieval [SIGIR 2022] [(PDF)](https://qhjqhj00.github.io/files/22curriculum.pdf) - Weighted Knowledge Graph Embedding [SIGIR 2023] [(PDF)](https://dl.acm.org/doi/pdf/10.1145/3539618.3591784) - Using Machine Learning Classifiers and A Virtual Voice Assistant for Common Tasks, An Employee Performance Evaluation Model is Used [WWW] [(PDF)](https://www.researchgate.net/profile/Ramesh-Byali/publication/362659843_Using_Machine_Learning_Classifiers_and_A_Virtual_Voice_Assistant_for_Common_Tasks_An_Employee_Performance_Evaluation_Model_is_Used/links/62faefe1ceb9764f72fea4b3/Using-Machine-Learning-Classifiers-and-A-Virtual-Voice-Assistant-for-Common-Tasks-An-Employee-Performance-Evaluation-Model-is-Used.pdf) - Mixed-Modality Interaction in Conversational Recommender Systems 会话推荐系统中的混合模态交互作用 [RecSys 2021] [(PDF)](http://ceur-ws.org/Vol-2948/paper2.pdf) - ConvEx-DS:_A Dataset for Conversational Explanations in Recommender SystemS 会话解释 [RecSys 2021] [(PDF)](https://ceur-ws.org/Vol-2948/paper1.pdf) [(code)](https://github.com/intsys-ude/Datasets/tree/main/ConvEx-DS) - A general model for fair and explainable recommendation in the loan domain 提出新模型，旨在提供更公平更透明的建议[RecSys 2021] [(PDF)](https://ceur-ws.org/Vol-2960/paper12.pdf) - Psychological User Characteristics and Meta-Intents in a Conversational Product Advisor 对话性产品顾问中的心理用户特征和元意图——提出元意图概念 [RecSys 2022] [(PDF)](https://ceur-ws.org/Vol-3222/paper2.pdf) - Meta-Intents in Conversational Recommender Systems 提出了一套元意图因素和提出了一个CRS框架 [RecSys 2022] [(PDF)](https://ceur-ws.org/Vol-3294/long6.pdf) - TripRec-A Recommender System for Planning Composite City Trips Based on Travel Mobility Analysis 设计并开发了第一个用于个性化、复合城市出行计算的目的地推荐系统 [WSDM] [(PDF)](https://ceur-ws.org/Vol-2855/main_short_2.pdf) - Fairness-Aware Graph Sampling for Network Analysis 开发一种方法量度结构板保存性的能力以及提出一种贪婪算法[ICDM 2022] [(PDF)](https://www.cse.msu.edu/~ptan/papers/icdm2022.pdf) - Hyper Meta-Path Contrastive Learning for Multi -Behavior Recommendation 提出了超元路径的概念和一个新的框架[ICDM 2021] [(PDF)](https://arxiv.org/pdf/2109.02859.pdf) - One Person, One Model—Learning Compound Router for Sequential Recommendation 顺序推荐 [ICDM 2022] [(PDF)](https://arxiv.org/pdf/2211.02824.pdf) [(code)](https://github.com/Lyken17/pytorch-OpCounter) - privacy-Preserved Neural Graph Similarity Learning 相似性学习 [ICDM 2022] [(PDF)](https://www.cse.msu.edu/~ptan/papers/icdm2022.pdf) [(code)](https://github.com/RUCAIBox/PPGM.) - Cola: Improving conversational recommender systems by collaborative augmentation [AAAI 2023] [(PDF)](https://ojs.aaai.org/index.php/AAAI/article/download/25567/25339) [(code)](https://github.com/DongdingLin/COLA) - CP-Rec: contextual prompting for conversational recommender systems 会话推荐系统的上下文提示 [AAAI 2023] [(PDF)](https://ojs.aaai.org/index.php/AAAI/article/view/26487/26259) - Efficient explorative key-term selection strategies for conversational contextual bandits 上下文 [AAAI 2023] [(PDF)](https