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🏛️ The Information Retrieval Crypt
cs.IR: Where Information Retrieval papers rest without their code.
11581
Total Papers
9061
No Code
371
Twilight
2149
Has Code
18.6%
Survival Rate
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Task Aligned Meta-learning based Augmented Graph for Cold-Start Recommendation
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Using Sentence Embeddings and Semantic Similarity for Seeking Consensus when Assessing Trustworthy AI
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Unconventional application of k-means for distributed approximate similarity search
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The Impact of Feature Quantity on Recommendation Algorithm Performance: A Movielens-100K Case Study
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Lessons from Deep Learning applied to Scholarly Information Extraction: What Works, What Doesn't, and Future Directions
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Supervised Contrastive Learning Approach for Contextual Ranking
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Re-weighting Negative Samples for Model-Agnostic Matching
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GazBy: Gaze-Based BERT Model to Incorporate Human Attention in Neural Information Retrieval
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On the Effect of Ranking Axioms on IR Evaluation Metrics
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Modelling Users with Item Metadata for Explainable and Interactive Recommendation
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Two-Stage Neural Contextual Bandits for Personalised News Recommendation
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A Design of A Simple Yet Effective Exercise Recommendation System in K-12 Online Learning
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Sequential Nature of Recommender Systems Disrupts the Evaluation Process
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Would You Ask it that Way? Measuring and Improving Question Naturalness for Knowledge Graph Question Answering
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A Dataset for Sentence Retrieval for Open-Ended Dialogues
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Debiasing Neural Retrieval via In-batch Balancing Regularization
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A Birds Eye View on Knowledge Graph Embeddings, Software Libraries, Applications and Challenges
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Think outside the search box: A comparative study of visual and form-based query builders
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It's the Same Old Story! Enriching Event-Centric Knowledge Graphs by Narrative Aspects
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A Comparison of Approaches for Imbalanced Classification Problems in the Context of Retrieving Relevant Documents for an Analysis
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A Practical Two-stage Ranking Framework for Cross-market Recommendation
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LoL: A Comparative Regularization Loss over Query Reformulation Losses for Pseudo-Relevance Feedback
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