Identifying Cost-Effective CPU Architectures for Vector Databases, Lessons from Pinterest's Ad Conversion Models, and More!

Vol.104 for May 12 - May 18, 2025

Stay Ahead of the Curve with the Latest Advancements and Discoveries in Information Retrieval.

This week’s newsletter highlights the following research:

1. A Comprehensive CPU Performance Analysis for Vector Similarity Search, from Kuffo et al.

2. Designing Advanced Learning-to-Rank Models for E-commerce Search, from Airbnb

3. Comparing OCR and Vision-Based Document Retrieval, from Most et al.

4. A Traffic Allocation Strategy for Cold-Start Items in Recommendation Systems, from Google

5. Techniques for Optimizing Embedding Tables in Large-Scale Ad Recommendation, from Pinterest

6. Efficient Knowledge Distillation from LLMs for E-commerce Search, from Walmart

7. Measuring and Mitigating the Distracting Effect in RAG Systems, from Amiraz et al.

8. A Coarse-to-Fine Multimodal Retrieval Framework for Knowledge-Based Visual Question Answering, from Microsoft

9. A Comprehensive Survey on LLMs in Multimodal Recommender Systems, from López-Ávila et al.

10. Modeling User Interest Life Cycles for Enhanced Recommendation Performance, from NetEase