Adding Reasoning Capabilities to Dense Retrievers, Making Scaling Laws Work in Industrial Recommender Systems, and More!
Vol.91 for Feb 10 - Feb 16, 2025
Stay Ahead of the Curve with the Latest Advancements and Discoveries in Information Retrieval.
This week’s newsletter highlights the following research:
Human-Guided Progressive Training for E-Commerce Ad Retrieval, from Walmart
A Mechanistic Interpretation of Cross-Encoder Relevance Scoring, from Lu et al.
A Graph-Enhanced RAG for Precise Medical Diagnosis and Treatment Recommendation, from NTU
A Decomposed Approach to Scaling Industrial Recommendation Models, from Alibaba
Experimental Lessons from Graph-Based Approximate Nearest Neighbor Search, from Azizi et al.
Learning Query-Dependent Neural Networks for Document Retrieval, from UMass Amherst
Reasoning-Augmented Dense Retrieval through Large Language Models, from Yan et al.
Coarse-to-Fine Tree Learning for Scalable Document Retrieval, from ServiceNow
mmE5: Efficient Multimodal Embeddings through Quality-Focused Data Synthesis, from Microsoft
A Framework for Designing Multi-Objective Ranking Models, from Amazon
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