2022年第36届人工智能顶级会议AAAI论文列表已经放出，此次会议共收到9251篇论文提交，其中9020篇论文被审稿。最终录取篇数为1349篇，录取率为可怜的15%。由于境外疫情形势依然严峻，大会将在2月22日到3月1日在线上进行举办。
较之历年接受率来说，今年的录取率可以说是断崖式下跌。下图对2017年至今年的投稿量以及接受率进行了可视化，可以说今年的投稿量之多与接受率之低形成了鲜明的对比。
关于对顶级会议历年论文的分析与整理可点击下方链接：
- AAAI2021推荐系统论文清单
- AAAI2020推荐系统论文集锦
- CIKM2021推荐系统论文集锦
- RecSys2021推荐系统论文集锦
与往年的惯例相同，我们分析了今年接收论文的标题，可以发现以下结论：
- 深度学习技术仍然是比较火热的技术之一；
- 对图数据的研究依然是大家关注的数据形式之一；
- 自监督学习、半监督学习、多智能体、表示学习是大家主要使用的学习范式；
- 机器学习应用如目标检测、文本分类、语义分割等是目前大家比较关注的方向。
完整版清单可从官网下载查看。
https://aaai.org/Conferences/AAAI-22/wp-content/uploads/2021/12/AAAI-22_Accepted_Paper_List_Main_Technical_Track.pdf
接下来，特意从1349篇论文中筛选出与推荐系统相关的15篇文章供大家欣赏（去年的推荐系统论文文章的比例为33/1692），提前领略学术前沿趋势与牛人的最新想法。
1. Meta-Learning for Online Update of Recommender Systems
Minseok Kim, Hwanjun Song, Yooju Shin, Dongmin Park, Kijung Shin, Jae-Gil Lee
https://minseokkim.net/publication/2022melon_aaai/2022melon_aaai.pdf
2. DiPS: Differentiable Policy for Sketching in Recommender Systems
Aritra Ghosh, Saayan Mitra, Andrew Lan
https://arxiv.org/pdf/2112.07616
3. Low-pass Graph Convolutional Network for Recommendation
Wenhui Yu, Zixin Zhang, Zheng Qin
4. Online certification of preference-based fairness for personalized recommender systems
Virginie Do, Sam Corbett-Davies, Jamal Atif, Nicolas Usunier
https://arxiv.org/pdf/2104.14527
5. Modeling Attrition in Recommender Systems with Departing Bandits
Omer Ben-Porat, Lee Cohen, Liu Leqi, Zachary Lipton, Yishay Mansour
6. A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations
Krishna P Neupane, Ervine Zheng, Yu Kong, Qi Yu
7. Context Uncertainty in Contextual Bandits with Applications to Recommender Systems
Hao Wang, Yifei Ma, Hao Ding, Yuyang Wan
8. Multi-view Intent Disentangle Graph Networks for Bundle Recommendation
Sen Zhao, Wei Wei, Ding Zou, Xian-Ling Mao
9. SMINet: State-Aware Multi-Aspect Interests Representation Network for Cold-Start Users Recommendation
Wanjie Tao, Yu Li, Liangyue Li, Zulong Chen, Hong Wen, Peilin Chen, Tingting Liang, Quan Lu
10. Leaping Through Time with Gradient-based Adaptation for Recommendation
Nuttapong Chairatanakul, Hoang NT, Xin Liu, Tsuyoshi Murata
https://arxiv.org/pdf/2112.05914
11. Cross-Task Knowledge Distillation in Multi-Task Recommendation
Chenxiao Yang, Junwei Pan, Xiaofeng Gao, Tingyu Jiang, Dapeng Liu, Guihai Chen
12. FPAdaMetric: False-positive-aware Adaptive Metric Learning for Session-based Recommendation
Jongwon Jeong, Jeong Choi, Hyunsouk Cho, Sehee Chung
13. Offline Interactive Recommendation with Natural-Language Feedback
Ruiyi Zhang, Tong Yu, Yilin Shen, Hongxia Jin
14. Learning the Optimal Recommendation from Explorative Users
Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu
https://arxiv.org/pdf/2110.03068
15. Obtaining Calibrated Probabilities with Personalized Ranking Models
Wonbin Kweon, SeongKu Kang, Hwanjo Yu
通过整理发现，此次会议接收的推荐系统相关论文主要涉及基于元学习的推荐系统2篇，序列化推荐5篇，基于强化学习的推荐系统4篇以及冷启动推荐2篇。
