{"product_id":"advances-in-information-retrieval-9783031887130","title":"Advances in Information Retrieval","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e.- exHarmony: Authorship and Citations for Benchmarking the Reviewer Assignment Problem.\u003c\/p\u003e\u003cp\u003e.- Unraveling the Impact of Visual Complexity on Search as Learning.\u003c\/p\u003e\u003cp\u003e.- Enhancing Utility in Differentially Private Recommendation Data Release via Exponential Mechanism.\u003c\/p\u003e\u003cp\u003e.- CountNet: Utilising Repetition Counts in Sequential Recommendation.\u003c\/p\u003e\u003cp\u003e.- The Impact of Mainstream-Driven Algorithms on Recommendations for Children.\u003c\/p\u003e\u003cp\u003e.- Leveraging Query Terms for Efficient Legal Document Recommendation.\u003c\/p\u003e\u003cp\u003e.- Inducing Diversity in Differentiable Search Indexing.\u003c\/p\u003e\u003cp\u003e.- EGL-DST: Error-Guided Learning for Multidimensional Evaluation Method of Dialogue State Tracking via GPT-4.\u003c\/p\u003e\u003cp\u003e.- Examining the Impact of Transcript Accuracy on Podcast Search and Re-Ranking.\u003c\/p\u003e\u003cp\u003e.- Ranking Generated Answers: On the Agreement of Retrieval Models with Humans on Consumer Health Questions.\u003c\/p\u003e\u003cp\u003e.- Counterfactual Query Rewriting to Use Historical Relevance Feedback.\u003c\/p\u003e\u003cp\u003e.- Improving Language Model Performance by Training on Prototypical Contradictions.\u003c\/p\u003e\u003cp\u003e.- LiT and Lean: Distilling Listwise Rerankers into Encoder-Decoder Models.\u003c\/p\u003e\u003cp\u003e.- The Impact of Incidental Multilingual Text on the Cross-Lingual Transferring in Monolingual Retrieval.\u003c\/p\u003e\u003cp\u003e.- Approximate Bag-of-Words Top-k Corpus Graphs.\u003c\/p\u003e\u003cp\u003e.- Gradual Negative Matching for LLM Unlearning.\u003c\/p\u003e\u003cp\u003e.- Fact-Driven Health Information Retrieval: Integrating LLMs and Knowledge Graphs to Combat Misinformation.\u003c\/p\u003e\u003cp\u003e.- Towards Interpretable Radiology Report Generation via Concept Bottlenecks using a Multi-Agentic RAG.\u003c\/p\u003e\u003cp\u003e.- Investigating the Performance of Dense Retrievers for Queries with Numerical Conditions.\u003c\/p\u003e\u003cp\u003e.- Hierarchical Skip Decoding for Efficient Autoregressive Language Model.\u003c\/p\u003e\u003cp\u003e.- Iterative Self-Training for Code Generation via Reinforced Re-Ranking.\u003c\/p\u003e\u003cp\u003e.- Efficient Constant-Space Multi-Vector Retrieval.\u003c\/p\u003e\u003cp\u003e.- DiffGR: A Discrete Diffusion-Based Model for Personalised Recommendation by Reconstructing User-Item Bipartite Graphs.\u003c\/p\u003e\u003cp\u003e.- BAAF - A Framework for Media Bias Detection.\u003c\/p\u003e\u003cp\u003e.- A Simple but Effective Closed-form Solution for Extreme Multi-label Learning.\u003c\/p\u003e\u003cp\u003e.- Efficient and Effective Conversational Search with Tail Entity Selection.\u003c\/p\u003e\u003cp\u003e.- Large Language Model Can Be a Foundation for Hidden Rationale- Based Retrieval.\u003c\/p\u003e\u003cp\u003e.- SAFERec: Self-Attention and Frequency Enriched Model for Next Basket Recommendation.\u003c\/p\u003e\u003cp\u003e.- Benchmarking Prompt Sensitivity in Large Language Models.\u003c\/p\u003e\u003cp\u003e.- Do LLMs Provide Consistent Answers to Health-Related Questions across Languages?.\u003c\/p\u003e\u003cp\u003e.- Rank-DistiLLM: Closing the Effectiveness Gap Between Cross-Encoders and LLMs for Passage Re-ranking.\u003c\/p\u003e\u003cp\u003e.- Benchmark Creation for Narrative Knowledge Delta Extraction Tasks: Can LLMs Help?.\u003c\/p\u003e\u003cp\u003e.- Passage Segmentation of Documents for Extractive Question Answering.\u003c\/p\u003e\u003cp\u003e.- Can Generative AI Adequately Protect Queries? Analyzing the Trade-off Between Privacy Awareness and Retrieval Effectiveness.\u003c\/p\u003e\u003cp\u003e.- Retrieval-Augmented Neural Team Formation.\u003c\/p\u003e\u003cp\u003e.- A Test Collection for Dataset Retrieval.\u003c\/p\u003e\u003cp\u003e.- A new dataset for keyword extraction from IT job descriptions.\u003c\/p\u003e\u003cp\u003e.- Entity-Aware Cross-Modal Pretraining for Knowledge-based Visual Question Answering.\u003c\/p\u003e\u003cp\u003e.- Patience in Proximity: A Simple Early Termination Strategy for HNSW Graph Traversal in Approximate k-Nearest Neighbor Search.\u003c\/p\u003e\u003cp\u003e.- Improving RAG for Personalization with Author Features and Contrastive Examples.\u003c\/p\u003e\u003cp\u003e.- E2Rank: Efficient and Effective Layer-wise Reranking.\u003c\/p\u003e\u003cp\u003e.- Token-Level Graphs for Short Text Classification.\u003c\/p\u003e\u003cp\u003e.- Investigating the Scalability of Approximate Sparse Retrieval Algorithms to Massive Datasets.\u003c\/p\u003e\u003cp\u003e.- A Comparative Analysis of Retrieval-Augmented Generation and Crowdsourcing for Fact-Checking.\u003c\/p\u003e\u003cp\u003e.- Exploring the Effectiveness of Multi-stage Fine-tuning for Cross-encoder Re-rankers.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Default Title","offer_id":53195468505431,"sku":"9783031887130","price":123.49,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/advances-in-information-retrieval-9783031887130","provider":"Book Curl","version":"1.0","type":"link"}