A Unified Approach to Job Search Query Understanding, Efficient Inference for Generative Recommenders, and More!

Vol.122 for Sep 15 - Sep 21, 2025

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

This week’s newsletter highlights the following research:

1. Scalable Cross-Entropy Loss with Negative Sampling for Industrial Recommendation Systems, from Zhelnin et al.

2. Unified LLM Architecture for Large-Scale Job Search Query Understanding, from LinkedIn

3. What News Recommendation Research Doesn't Teach About Building Real Systems, from Higley et al.

4. A Systematic Evaluation of Large Language Models for Cross-Lingual Information Retrieval, from LMU Munich

5. Interactive Two-Tower Architecture for Real-Time Candidate Filtering in Recommender Systems, from Ant Group

6. Efficient Inference for Generative LLM Recommenders via Hidden State Matching, from Wang et al.

7. A Framework for Training Embedding Models, from Scratch, from Tencent

8. A Comprehensive Review of Large Language Models in Document Intelligence, from Ke et al.

9. A Modular Analysis of LLM-Based Feature Extraction for Sequential Recommendation, from Shi et al.

10. Systematic Data Augmentation for Enhanced Generative Recommendation, from Lee et al.