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Author:   Claudia Hauff ,  Craig Macdonald ,  Dietmar Jannach ,  Gabriella Kazai
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Volume:   15574
ISBN:  

9783031887130

ISBN 10:   3031887131
Pages:   465
Publication Date:   04 April 2025
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

.- exHarmony: Authorship and Citations for Benchmarking the Reviewer Assignment Problem. .- Unraveling the Impact of Visual Complexity on Search as Learning. .- Enhancing Utility in Differentially Private Recommendation Data Release via Exponential Mechanism. .- CountNet: Utilising Repetition Counts in Sequential Recommendation. .- The Impact of Mainstream-Driven Algorithms on Recommendations for Children. .- Leveraging Query Terms for Efficient Legal Document Recommendation. .- Inducing Diversity in Differentiable Search Indexing. .- EGL-DST: Error-Guided Learning for Multidimensional Evaluation Method of Dialogue State Tracking via GPT-4. .- Examining the Impact of Transcript Accuracy on Podcast Search and Re-Ranking. .- Ranking Generated Answers: On the Agreement of Retrieval Models with Humans on Consumer Health Questions. .- Counterfactual Query Rewriting to Use Historical Relevance Feedback. .- Improving Language Model Performance by Training on Prototypical Contradictions. .- LiT and Lean: Distilling Listwise Rerankers into Encoder-Decoder Models. .- The Impact of Incidental Multilingual Text on the Cross-Lingual Transferring in Monolingual Retrieval. .- Approximate Bag-of-Words Top-k Corpus Graphs. .- Gradual Negative Matching for LLM Unlearning. .- Fact-Driven Health Information Retrieval: Integrating LLMs and Knowledge Graphs to Combat Misinformation. .- Towards Interpretable Radiology Report Generation via Concept Bottlenecks using a Multi-Agentic RAG. .- Investigating the Performance of Dense Retrievers for Queries with Numerical Conditions. .- Hierarchical Skip Decoding for Efficient Autoregressive Language Model. .- Iterative Self-Training for Code Generation via Reinforced Re-Ranking. .- Efficient Constant-Space Multi-Vector Retrieval. .- DiffGR: A Discrete Diffusion-Based Model for Personalised Recommendation by Reconstructing User-Item Bipartite Graphs. .- BAAF - A Framework for Media Bias Detection. .- A Simple but Effective Closed-form Solution for Extreme Multi-label Learning. .- Efficient and Effective Conversational Search with Tail Entity Selection. .- Large Language Model Can Be a Foundation for Hidden Rationale- Based Retrieval. .- SAFERec: Self-Attention and Frequency Enriched Model for Next Basket Recommendation. .- Benchmarking Prompt Sensitivity in Large Language Models. .- Do LLMs Provide Consistent Answers to Health-Related Questions across Languages?. .- Rank-DistiLLM: Closing the Effectiveness Gap Between Cross-Encoders and LLMs for Passage Re-ranking. .- Benchmark Creation for Narrative Knowledge Delta Extraction Tasks: Can LLMs Help?. .- Passage Segmentation of Documents for Extractive Question Answering. .- Can Generative AI Adequately Protect Queries? Analyzing the Trade-off Between Privacy Awareness and Retrieval Effectiveness. .- Retrieval-Augmented Neural Team Formation. .- A Test Collection for Dataset Retrieval. .- A new dataset for keyword extraction from IT job descriptions. .- Entity-Aware Cross-Modal Pretraining for Knowledge-based Visual Question Answering. .- Patience in Proximity: A Simple Early Termination Strategy for HNSW Graph Traversal in Approximate k-Nearest Neighbor Search. .- Improving RAG for Personalization with Author Features and Contrastive Examples. .- E2Rank: Efficient and Effective Layer-wise Reranking. .- Token-Level Graphs for Short Text Classification. .- Investigating the Scalability of Approximate Sparse Retrieval Algorithms to Massive Datasets. .- A Comparative Analysis of Retrieval-Augmented Generation and Crowdsourcing for Fact-Checking. .- Exploring the Effectiveness of Multi-stage Fine-tuning for Cross-encoder Re-rankers.

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