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🏛️ The Information Retrieval Crypt
cs.IR: Where Information Retrieval papers rest without their code.
11667
Total Papers
9061
No Code
371
Twilight
2235
Has Code
19.2%
Survival Rate
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Transformers4NewsRec: A Transformer-based News Recommendation Framework
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Proactive Detection and Calibration of Seasonal Advertisements with Multimodal Large Language Models
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Unifying Economic and Language Models for Enhanced Sentiment Analysis of the Oil Market
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GaVaMoE: Gaussian-Variational Gated Mixture of Experts for Explainable Recommendation
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GleanVec: Accelerating vector search with minimalist nonlinear dimensionality reduction
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Author Unknown: Evaluating Performance of Author Extraction Libraries on Global Online News Articles
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Unraveling Movie Genres through Cross-Attention Fusion of Bi-Modal Synergy of Poster
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ERCache: An Efficient and Reliable Caching Framework for Large-Scale User Representations in Meta's Ads System
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A Parameter Update Balancing Algorithm for Multi-task Ranking Models in Recommendation Systems
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Liver Cancer Knowledge Graph Construction based on dynamic entity replacement and masking strategies RoBERTa-BiLSTM-CRF model
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CUPID: A Real-Time Session-Based Reciprocal Recommendation System for a One-on-One Social Discovery Platform
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Embedding derivatives and derivative Area operators of Hardy spaces into Lebesgue spaces
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On the Biased Assessment of Expert Finding Systems
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Item Cluster-aware Prompt Learning for Session-based Recommendation
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Ranking Policy Learning via Marketplace Expected Value Estimation From Observational Data
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Representing Web Applications As Knowledge Graphs
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LLMTemporalComparator: A Tool for Analysing Differences in Temporal Adaptations of Large Language Models
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Explaining the (Not So) Obvious: Simple and Fast Explanation of STAN, a Next Point of Interest Recommendation System
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Quantifying User Coherence: A Unified Framework for Cross-Domain Recommendation Analysis
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BayesCNS: A Unified Bayesian Approach to Address Cold Start and Non-Stationarity in Search Systems at Scale
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ECORS: An Ensembled Clustering Approach to Eradicate The Local And Global Outlier In Collaborative Filtering Recommender System
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DIIT: A Domain-Invariant Information Transfer Method for Industrial Cross-Domain Recommendation
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