A Task-Specific Approach to Recommender System Design, Evidence of Systemic Bias in LLM-Based IR Evaluation, and More!
Vol.97 for Mar 24 - Mar 30, 2025
Stay Ahead of the Curve with the Latest Advancements and Discoveries in Information Retrieval.
This week’s newsletter highlights the following research:
A Task-Specific Approach to Recommender System Design, from Aixin Sun
Improving Product Search Through Negation Query Rewriting, from Amazon Search
Understanding Bias in LLM-Based Information Retrieval Evaluation, from Google DeepMind
Agentic Recommender Systems in the Age of Multimodal LLMs, from Huang et al.
A Framework for Logical Reasoning in Document Retrieval Systems, from Accenture
A Modular Framework for Efficient Retrieval-Augmented Generation on Graph Data, from NUS
Video-ColBERT: Enhancing Text-to-Video Retrieval with Multi-level Token Interactions, from Reddy et al.
A Systematic Review of LLM-based Question Answering Agents, from Murong Yue
Enhancing Small Language Models Through Integrated Search and Retrieval, from Hu et al.
A Framework for Reducing Generative Retrieval Hallucinations at Scale, from Ant Group
