To Read
- https://netflixtechblog.com/improve-your-next-experiment-by-learning-better-proxy-metrics-from-past-experiments-64c786c2a3ac
- https://netflixtechblog.com/sequential-a-b-testing-keeps-the-world-streaming-netflix-part-1-continuous-data-cba6c7ed49df
- https://arxiv.org/abs/2407.02464
- https://arxiv.org/abs/2305.12102
- https://arxiv.org/abs/1709.03933
- https://arxiv.org/abs/2101.08769
- https://arxiv.org/abs/1205.2618 # BPR
- https://arxiv.org/abs/2312.08520 # InfoNCE+
- https://arxiv.org/abs/2308.06091 # MAWU
- https://arxiv.org/abs/2109.12613 # CCL
- https://arxiv.org/abs/2201.02327 # SSM
- https://arxiv.org/abs/2206.12811 # DirectAU
- KG-BERT
- XR-Transformer
- SetFit
- Lora vs Fine tuning
- Better Generalization with semantic IDs
- Mutual Information Neural Estimation
- Contrastive Learning with Hard Negatives
- Decoupled Contrastive Learning
- Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning
- Semi-Supervised Classification with Graph Convolutional Networks
- Ranking Distillation
- PinnerFormer
- BERT4Rec
- Retrieval as Attention
- Generate Rather than Retrieve
- PLM in Baidu Search
- Emebdding Based Retrieval in Facebook Search
- Self Attentive Sequential Recommendation
- Is BERT4Rec really better than SASRec?
- Transformers4Rec
- Pretrained Transformers for Text Ranking: BERT and Beyond
- Turning Dross Into Gold Loss: is BERT4Rec really better than SASRec?
- Modularized Transfomer-based Ranking Framework
- Pre-trained Language Model for Web-scale Retrieval in Baidu Search
- Related Pins at Pinterest: The Evolution of a Real-World Recommender System
- Improving Pinterest Search Relevance Using Large Language Models
- Pixie: A System for Recommending 3+ Billion Items to 200+ Million Users in Real-Time
- Towards Personalized and Semantic Retrieval: An End-to-End Solution for E-commerce Search via Embedding Learning
- Ranking Relevance in Yahoo Search
- Fine-Tuning LLaMA for Multi-Stage Text Retrieval
- Revisiting Deep Learning Models for Tabular Data
- OmniSearchSage: Multi-Task Multi-Entity Embeddings for Pinterest Search
- Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction
- Behavior Sequence Transformer for E-commerce Recommendation in Alibaba
- Graph Convolutional Neural Networks for Web-Scale Recommender Systems
- PinnerSage: Multi-Modal User Embedding Framework for Recommendations at Pinterest
- ItemSage: Learning Product Embeddings for Shopping Recommendations at Pinterest
- RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses
- Pretrained Language Model based Web Search Ranking: From Relevance to Satisfaction
- Rethink Training of BERT Rerankers in Multi-Stage Retrieval Pipeline
- Tevatron: An Efficient and Flexible Toolkit for Dense Retrieval
- SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval