Top Information Retrieval Papers of the Week

Top Information Retrieval Papers of the Week

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Sitemap - 2025 - Top Information Retrieval Papers of the Week

Towards AI Search Paradigm, Zero-Shot Mixture of Retrievers, and More!

BM25-Guided LLM Reranking for Complex Queries, Visual Analytics for GraphRAG Pipelines, and More!

When to Choose GraphRAG Over Traditional RAG, The Implicit Semantics Gap in Text Embedding Models, and More!

Extremely Long User History Modeling at Instagram, When Compact Embeddings Outperform Large Models in Hybrid RAG, and More!

Measuring Retrieval Robustness in LLMs, Training Small LLM Agents for End-to-End RAG, and More!

Training Multi-Vector Models with Inherent Clustering Structure, Reasoning-Enhanced Listwise Document Reranking, and More!

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

Efficient Hyper-Parameter Optimization for RAG, Negative-Sample-Free User Sequence Modeling, and More!

Training Retrievers for Reasoning Tasks, A Unified Framework for Text, Image, and Video RAG, and More!

Secure Hybrid Knowledge Retrieval for Enterprise Applications, Scaling RAG Evaluation with LLMs, and More!

Exploring RAG's Vulnerability to Real-World Query Variations, Breaking the Bounded-Recall Barrier in Multi-Stage Ranking, and More!

A Unified Framework for Document Reranking with LLMs, Unifying Search and Recommendation Through Generative Retrieval, and More!

Storage-Efficient Multi-Vector Retrieval, Enhancing Negation Detection in Text Embeddings, and More!

A Task-Specific Approach to Recommender System Design, Evidence of Systemic Bias in LLM-Based IR Evaluation, and More!

The Complete Guide to Training Image Retrieval Models, A Knowledge-Oriented Survey of RAG Technologies, and More!

The Critical Vulnerabilities of Dense Retrievers, A Survey of LLM Agents in Recommendation and Search, and More!

Enhancing Retrieval with Temporal Embeddings, Leveraging LLMs for Recommendation Initialization, and More!

Agent-centric Information Access, Leveraging LLMs for Efficient, Generalizable Dense Retrievers, and More!

Architectural Evolution of Information Retrieval Systems, The Impact of Context Size and Model Selection in RAG Systems and More!

Adding Reasoning Capabilities to Dense Retrievers, Making Scaling Laws Work in Industrial Recommender Systems, and More!

Text Data Augmentation Techniques in the Era of LLMs, A Function Calling Approach to Database Querying with LLMs, and More!

Fast and Efficient Multi-Vector Search, A Parameter-Space Approach to Retrieval Augmented Generation, and More!

Reducing Memory Footprint in Vector Search, A Systematic Evaluation of 35 Adaptive Retrieval Methods, and More!

The Evolution and Applications of Agentic RAG, Making RAG Work with Small Language Models, and More!

A Comprehensive Study of Long Context vs. RAG Performance, Search-o1: Agentic Search-Enhanced Large Reasoning Models, and More!

LinkedIn's Semantic Search Upgrade, Enabling Large-Scale Retrieval on Edge Devices, and More!

© 2025 Sumit Kumar
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