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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
Daily growth rate of scientific production on Covid-19. A...
Daniel Torres-Salinas · 2020-04-15 · via cs.IR updates on arXiv.org

The scientific community is facing one of its greatest challenges in solving a global health problem: COVID-19 pandemic. This situation has generated an unprecedented volume of publications. What is the volume, in terms of publications, of research on COVID-19? The general objective of this research work is to obtain a global vision of the daily growth of scientific production on COVID-19 in different databases (Dimensions, Web of Science Core Collection, Scopus-Elsevier, Pubmed and eight repositories). In relation to the results obtained, Dimensions indexes a total of 9435 publications (69% with peer review and 2677 preprints) well above Scopus (1568) and WoS (718). This is a classic biliometric phenomenon of exponential growth (R2 = 0.92). The global growth rate is 500 publications and the production doubles every 15 days. In the case of Pubmed the weekly growth is around 1000 publications. Of the eight repositories analysed, Pubmed Central, Medrxiv and SSRN are the leaders. Despite their enormous contribution, the journals continue to be the core of scientific communication. Finally, it has been established that three out of every four publications on the COVID-19 are available in open access. The information explosion demands a serious and coordinated response from information professionals, which places us at the centre of the information pandemic.