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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
Interactive GIS Web-Atlas for Twelve Pacific Islands Coun...
Fabrice Lartigou, Michael Govorov, Tofiga Aisake, Pankajeshwara · 2021-07-15 · via cs.IR updates on arXiv.org

This article deals with the development of an interactive up-to-date Pacific Islands Web GIS Atlas. It focuses on the compilation of spatial data from the twelve member countries of the University of the South Pacific (Cook Islands, Fiji Islands, Kiribati Islands, Marshall Islands, Nauru, Niue, Tonga, Tuvalu, Tokelau, Solomon Islands, Vanuatu, and Western Samoa). A previous bitmap web Atlas was created in 1996, and was a pilot activity investigating the potential for using Geographical Information Systems (GIS) in the South Pacific. The objective of the new atlas is to provide sets of spatial and attributive data and maps for use of educators, students, researchers, policy makers and other relevant user groups and the public. GIS is a highly flexible and dynamic technology that allows the construction and analysis of maps and data sets from a variety of sources and formats. Nowadays, GIS application has moved from local and client-server applications to a three-tier architecture: Client (Web Browser) -- Application Web Map Server -- Spatial Data Warehouses. The objective of this project is to produce an Atlas that will include interactive maps and data on an Application Web Map Server. Intergraph products such as GeoMedia Professional, Web Map and Web Publisher have been selected for the web atlas production and design. In an interactive environment, an atlas will be composed from a series of maps and data profiles, which will be based on legend entries, queries, hot spots and cartographic tools. Only the first stage of development of the atlas and related technological solutions are outlined in this article.