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🏛️ The Information Retrieval Crypt
cs.IR: Where Information Retrieval papers rest without their code.
11622
Total Papers
9061
No Code
371
Twilight
2190
Has Code
18.8%
Survival Rate
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Data-Driven Analysis of Text-Conditioned AI-Generated Music: A Case Study with Suno and Udio
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MatSKRAFT: A framework for large-scale materials knowledge extraction from scientific tables
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Diversified recommendations of cultural activities with personalized determinantal point processes
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We're Still Doing It (All) Wrong: Recommender Systems, Fifteen Years Later
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CESRec: Constructing Pseudo Interactions for Sequential Recommendation via Conversational Feedback
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Practice on Long Behavior Sequence Modeling in Tencent Advertising
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KLIPA: A Knowledge Graph and LLM-Driven QA Framework for IP Analysis
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Datasets for Navigating Sensitive Topics in Recommendation Systems
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Avoiding Over-Personalization with Rule-Guided Knowledge Graph Adaptation for LLM Recommendations
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Language Bias in Information Retrieval: The Nature of the Beast and Mitigation Methods
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DecoupleSearch: Decouple Planning and Search via Hierarchical Reward Modeling
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LESER: Learning to Expand via Search Engine-feedback Reinforcement in e-Commerce
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Fishing for Answers: Exploring One-shot vs. Iterative Retrieval Strategies for Retrieval Augmented Generation
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Multimodal Foundation Model-Driven User Interest Modeling and Behavior Analysis on Short Video Platforms
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Global-to-Local or Local-to-Global? Enhancing Image Retrieval with Efficient Local Search and Effective Global Re-ranking
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Safeguarding Patient Trust in the Age of AI: Tackling Health Misinformation with Explainable AI
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LLM-based Relevance Assessment for Web-Scale Search Evaluation at Pinterest
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Efficient Item ID Generation for Large-Scale LLM-based Recommendation
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LLMs for estimating positional bias in logged interaction data
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ACT: Automated Constraint Targeting for Multi-Objective Recommender Systems
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RankGraph: Unified Heterogeneous Graph Learning for Cross-Domain Recommendation
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HF-RAG: Hierarchical Fusion-based RAG with Multiple Sources and Rankers
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