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cs.IR updates on arXiv.org

From Top-1 to Top-K: A Reproducibility Study and Benchmarking of Counterfactual Explanations for Recommender Systems Impact of large language models on peer review opinions from a fine-grained perspective: Evidence from top conference proceedings in AI Diagnosable ColBERT: Debugging Late-Interaction Retrieval Models Using a Learned Latent Space as Reference Enhancing Unsupervised Keyword Extraction in Academic Papers through Integrating Highlights with Abstract CAST: Modeling Semantic-Level Transitions for Complementary-Aware Sequential Recommendation IndiaFinBench: An Evaluation Benchmark for Large Language Model Performance on Indian Financial Regulatory Text Think Before Writing: Feature-Level Multi-Objective Optimization for Generative Citation Visibility RARE: Redundancy-Aware Retrieval Evaluation Framework for High-Similarity Corpora Personalized Benchmarking: Evaluating LLMs by Individual Preferences Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations JFinTEB: Japanese Financial Text Embedding Benchmark UsefulBench: Towards Decision-Useful Information as a Target for Information Retrieval SIMMER: Cross-Modal Food Image--Recipe Retrieval via MLLM-Based Embedding Rethinking the Necessity of Adaptive Retrieval-Augmented Generation through the Lens of Adaptive Listwise Ranking BioHiCL: Hierarchical Multi-Label Contrastive Learning for Biomedical Retrieval with MeSH Labels Learning Behaviorally Grounded Item Embeddings via Personalized Temporal Contexts Collaborative Filtering Through Weighted Similarities of User and Item Embeddings IG-Search: Step-Level Information Gain Rewards for Search-Augmented Reasoning Metric-agnostic Learning-to-Rank via Boosting and Rank Approximation GenRec: A Preference-Oriented Generative Framework for Large-Scale Recommendation Uncertainty-aware Generative Learning Path Recommendation with Cognition-Adaptive Diffusion CPGRec+: A Balance-oriented Framework for Personalized Video Game Recommendations Don't Retrieve, Navigate: Distilling Enterprise Knowledge into Navigable Agent Skills for QA and RAG NewsTorch: A PyTorch-based Toolkit for Learner-oriented News Recommendation Controlling Authority Retrieval: A Missing Retrieval Objective for Authority-Governed Knowledge APEX-MEM: Agentic Semi-Structured Memory with Temporal Reasoning for Long-Term Conversational AI ID and Graph View Contrastive Learning with Multi-View Attention Fusion for Sequential Recommendation Large Language Models to Enhance Business Process Modeling: Past, Present, and Future Trends Dual-Enhancement Product Bundling: Bridging Interactive Graph and Large Language Model Evaluation of Agents under Simulated AI Marketplace Dynamics
Open Access and Discovery Tools: How do Primo Libraries M...
François Renaville · 2015-09-15 · via cs.IR updates on arXiv.org

Scholarly Open Access repositories contain lots of treasures including rare or otherwise unpublished materials and articles that scholars self-archive, often as part of their institution's mandate. But it can be hard to discover this material unless users know exactly where to look. Since the very beginning, libraries have played a major role in supporting the OA movement. Next to all services they can provide to support the deposit of research output in the repositories, they can make Open Access materials widely discoverable by their patrons through general search engines (Google, Bing...), specialized search engines (like Google Scholar) and library discovery tools, thus expanding their collection to include materials that they would not necessarily pay for. In this paper, we intend to focus on two aspects regarding Open Access and Primo discovery tool. In early 2013, Ex Libris Group started to add institutional repositories to Primo Central Index (PCI), their mega-aggregation of hundreds of millions of scholarly e-resources. After 2 years, it may be interesting to take stock of the current situation of PCI regarding Open Access institutional repositories. On basis of a survey to carry out among the Primo community, the paper also shows how libraries using Primo discovery tool integrate Green Open Access contents in their catalog. Two major ways are possible for them: Firstly, they can directly harvest, index and manage any repository in their Primo and display those free contents next to the more traditional library collections; Secondly, if they are PCI subscribers, they can quickly and easily activate any, if not all, of the Open Access repositories contained PCI, making thus the contents of those directly discoverable to their end users.