Training Retrievers for Reasoning Tasks, A Unified Framework for Text, Image, and Video RAG, and More!
Vol.102 for Apr 28 - May 04, 2025
Stay Ahead of the Curve with the Latest Advancements and Discoveries in Information Retrieval.
This week’s newsletter highlights the following research:
A Multi-Modal, Multi-Granular Framework for Adaptive Knowledge Retrieval, from KAIST
Training Models for Reasoning-Intensive Information Retrieval, from Meta
Comparative Performance of Advanced Chunking Techniques in Retrieval-Augmented Generation, from the University of Bologna
Guardrails for Valid LLM-Based Evaluation in Information Retrieval, from Dietz et al.
Learning Universal User Representations for Multi-Surface Recommendation Systems, from Snap Inc.
Efficient Top-K Recommendation in Million-Item Catalogs Without Exhaustive Scoring, from Petrov et al.
A Dual-Process Framework for Dynamic Multi-Hop Question Answering, from Cheng et al.
Revealing the Limitations of Hallucination Detection Metrics, from Apple
Multi-Task Contrastive Learning for Universal Embeddings in Billion-Node Graphs, from Pinterest
Learning Sequential Recommendation Embeddings in the Null Space of Language Models, from Hu et al.
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