mlsanityData to 14 Oct 2026

Scholar Inbox: Personalized Paper Recommendations for Scientists

arXiv 2504.08385 ↗First posted 11 Apr 2025cs.CL cs.AI cs.IRcited by 3

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Abstract (arXiv)

Scholar Inbox is a new open-access platform designed to address the challenges researchers face in staying current with the rapidly expanding volume of scientific literature. We provide personalized recommendations, continuous updates from open-access archives (arXiv, bioRxiv, etc.), visual paper summaries, semantic search, and a range of tools to streamline research workflows and promote open research access. The platform's personalized recommendation system is trained on user ratings, ensuring that recommendations are tailored to individual researchers' interests. To further enhance the user experience, Scholar Inbox also offers a map of science that provides an overview of research across domains, enabling users to easily explore specific topics. We use this map to address the cold start problem common in recommender systems, as well as an active learning strategy that iteratively prompts users to rate a selection of papers, allowing the system to learn user preferences quickly. We evaluate the quality of our recommendation system on a novel dataset of 800k user ratings, which we make publicly available, as well as via an extensive user study. https://www.scholar-inbox.com/

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 14 of its 46 references that are in the map. First posted on arXiv 11 Apr 2025.

Builds on

14 of 46 references.

References · 14

  1. 2024Qwen2.5 Technical Reportcited by 4,942
  2. 2017Neural Collaborative Filteringcited by 1,111
  3. 2023Towards General Text Embeddings with Multi-stage Contrastive Learningcited by 723
  4. 2020SPECTER: Document-level Representation Learning using Citation-informed Transformerscited by 430
  5. 2022Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddingscited by 75
  6. 2024OpenResearcher: Unleashing AI for Accelerated Scientific Researchcited by 24
  7. 2020Scientific Paper Recommendation: A Surveycited by 20
  8. 2021Bursting Scientific Filter Bubbles: Boosting Innovation via Novel Author Discoverycited by 13
  9. 2014The Matthew effect in empirical datacited by 10
  10. 2022Scientific Paper Recommendation Systems: a Literature Review of recent Publicationscited by 10
  11. 2023Biases in Scholarly Recommender Systems: Impact, Prevalence, and Mitigationcited by 2
  12. 2021Chronological Citation Recommendation with Time Preferencecited by 1
2 more
  1. 2022Tag-Aware Document Representation for Research Paper Recommendationcited by 1
  2. 2024Academic Article Recommendation Using Multiple Perspectivescited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.