Advances in information retrieval = ...
European Conference on IR Research (2025 :)

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  • Advances in information retrieval = 47th European Conference on Information Retrieval, ECIR 2025, Lucca, Italy, April 6-10, 2025 : proceedings.. Part III /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: Advances in information retrieval/ edited by Claudia Hauff ... [et al.].
    其他題名: 47th European Conference on Information Retrieval, ECIR 2025, Lucca, Italy, April 6-10, 2025 : proceedings.
    其他題名: ECIR 2025
    其他作者: Hauff, Claudia.
    團體作者: European Conference on IR Research
    出版者: Cham :Springer Nature Switzerland : : 2025.,
    面頁冊數: xxv, 465 p. :ill. (some col.), digital ;24 cm.
    內容註: 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.
    Contained By: Springer Nature eBook
    標題: Information retrieval - Congresses. -
    電子資源: https://doi.org/10.1007/978-3-031-88714-7
    ISBN: 9783031887147
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