Advances in Information Retrieval

Table of Contents

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   Book Overview
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   Chapter 1 Efficient Multi-vector Dense Retrieval with Bit Vectors
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   Chapter 2 CrisisKAN: Knowledge-Infused and Explainable Multimodal Attention Network for Crisis Event Classification
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   Chapter 3 Utilizing Low-Dimensional Molecular Embeddings for Rapid Chemical Similarity Search
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   Chapter 4 Translate-Distill: Learning Cross-Language Dense Retrieval by Translation and Distillation
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   Chapter 5 Prompt-Based Generative News Recommendation (PGNR): Accuracy and Controllability
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   Chapter 6 CaseGNN: Graph Neural Networks for Legal Case Retrieval with Text-Attributed Graphs
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   Chapter 7 Ranking Heterogeneous Search Result Pages Using the Interactive Probability Ranking Principle
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   Chapter 8 DESIRE-ME: Domain-Enhanced Supervised Information Retrieval Using Mixture-of-Experts
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    Chapter 9 Probing Pretrained Language Models with Hierarchy Properties
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    Chapter 10 Query Exposure Prediction for Groups of Documents in Rankings
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    Chapter 11 ProMap: Product Mapping Datasets
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    Chapter 12 Context-Driven Interactive Query Simulations Based on Generative Large Language Models
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    Chapter 13 A Deep Learning Approach for Selective Relevance Feedback
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    Chapter 14 Investigating the Robustness of Sequential Recommender Systems Against Training Data Perturbations
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    Chapter 15 Exploring Large Language Models and Hierarchical Frameworks for Classification of Large Unstructured Legal Documents
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    Chapter 16 Emotional Insights for Food Recommendations
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    Chapter 17 HyperPIE: Hyperparameter Information Extraction from Scientific Publications
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    Chapter 18 LaQuE: Enabling Entity Search at Scale
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    Chapter 19 Analyzing Adversarial Attacks on Sequence-to-Sequence Relevance Models
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    Chapter 20 Conversational Search with Tail Entities
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    Chapter 21 An EcoSage Assistant: Towards Building A Multimodal Plant Care Dialogue Assistant
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    Chapter 22 Event-Specific Document Ranking Through Multi-stage Query Expansion Using an Event Knowledge Graph
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    Chapter 23 Two-Step SPLADE: Simple, Efficient and Effective Approximation of SPLADE
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    Chapter 24 Large Language Models are Zero-Shot Rankers for Recommender Systems
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    Chapter 25 Simulating Follow-Up Questions in Conversational Search
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    Chapter 26 Adapting Standard Retrieval Benchmarks to Evaluate Generated Answers
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    Chapter 27 Controllable Decontextualization of Yes/No Question and Answers into Factual Statements
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    Chapter 28 Evaluating the Impact of Content Deletion on Tabular Data Similarity and Retrieval Using Contextual Word Embeddings
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    Chapter 29 Multimodal Learned Sparse Retrieval with Probabilistic Expansion Control
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    Chapter 30 Alleviating Confounding Effects with Contrastive Learning in Recommendation