Large Foundation Model for Ads Recommendation, Feedback-Driven Approaches in RAG, and More!
Vol.118 for Aug 18 - Aug 24, 2025
Stay Ahead of the Curve with the Latest Advancements and Discoveries in Information Retrieval.
This week’s newsletter highlights the following research: 
- Large Foundation Model for Ads Recommendation, from Tencent 
- A Survey of Feedback-Driven Approaches in Retrieval-Augmented Generation, from Rathee et al. 
- Scaling Laws for Click-Through Rate Prediction with Knowledge Distillation, from Meituan 
- Closing the Performance Gap in Generative Recommenders with Collaborative Tokenization and Efficient Modeling, from Lepage et al. 
- Can LLM-Generated QA Data Replace Human Benchmarks for RAG Systems?, from van Elburg et al. 
- Reducing False Positives in Sequential Recommendation through Explicit Negative Feedback Modeling, from Ivanova et al. 
- An Industry Study of RAG Implementation Challenges and Practices, from Brehme et al. 
- A Framework for Ultra-Long Behavioral Modeling in Candidate Retrieval, from ByteDance 
- Representation Quantization for Collaborative Filtering Augmentation, from Kuaishou 
- Task-Specialized Co-training for Information Retrieval and Semantic Similarity, from Tencent 
Keep reading with a 7-day free trial
Subscribe to Top Information Retrieval Papers of the Week to keep reading this post and get 7 days of free access to the full post archives.

