PAPER

Paper	Link	Done?
Cold Start Similar Artists Ranking with Gravity-Inspired Graph Autoencoders	https://arxiv.org/abs/2403.05185
Personalized Audiobook Recommendations at Spotify Through Graph Neural Networks	https://arxiv.org/abs/2403.05185
Learning Deep Structured Semantic Models for Web Search using Clickthrough Data	https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/cikm2013_DSSM_fullversion.pdf
A Semi-Personalized System for User Cold Start Recommendation on Music Streaming Apps	https://arxiv.org/abs/2106.03819
Collaborative Filtering for Implicit Feedback Datasets	http://yifanhu.net/PUB/cf.pdf
Self-Attentive Sequential Recommendation	https://arxiv.org/pdf/1808.09781
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer	https://arxiv.org/pdf/1904.06690
Turning Dross Into Gold Loss: is BERT4Rec really better than SASRec?	https://arxiv.org/pdf/2309.07602
Deep & Cross Network for Ad Click Predictions	https://arxiv.org/pdf/1708.05123
DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems	https://arxiv.org/pdf/2008.13535
Pixie: A System for Recommending 3+ Billion Items to 200+ Million Users in Real-Time	https://arxiv.org/pdf/1711.07601
PinnerSage: Multi-Modal User Embedding Framework for Recommendations at Pinterest	https://arxiv.org/pdf/2007.03634
PinnerFormer: Sequence Modeling for User Representation at Pinterest	https://arxiv.org/pdf/2205.04507
ItemSage: Learning Product Embeddings for Shopping Recommendations at Pinterest	https://arxiv.org/pdf/2205.11728
Rethinking Personalized Ranking at Pinterest: An End-to-End Approach	https://arxiv.org/pdf/2209.08435
OmniSearchSage: Multi-Task Multi-Entity Embeddings for Pinterest Search	https://arxiv.org/pdf/2404.16260
Reinforcement Learning for Budget Constrained Recommendations	https://netflixtechblog.com/reinforcement-learning-for-budget-constrained-recommendations-6cbc5263a32a
Search Personalization at Netflix	https://research.netflix.com/publication/search-personalization-at-netflix
Navigating the Feedback Loop in Recommender Systems: Insights and Strategies from Industry Practice	https://research.netflix.com/publication/navigating-the-feedback-loop-in-recommender-systems-insights-and-strategies
Artwork Personalization at Netflix	https://netflixtechblog.com/artwork-personalization-c589f074ad76
The Next Step in Personalization: Dynamic Sizzles	https://netflixtechblog.com/the-next-step-in-personalization-dynamic-sizzles-4dc4ce2011ef
Large-Scale Video Recommender Systems	https://videorecsys.com/
Practical Diversified Recommendations on YouTube with Determinantal Point Processes	https://jgillenw.com/cikm2018.pdf
Online Matching: A Real-time Bandit System for Large-scale Recommendations	https://arxiv.org/pdf/2307.15893