What is Problem Mining? This is a tool based on data of arXiv.org which periodically scans packets of full texts of papers hosted on arXiv and available through arXiv's bulk data access policy, with the aim to automatically detect papers containing discussions on open problems or conjectures. It then creates a list from the detected papers putting together papers' descriptive data and some short snippets extracted from the full texts displaying an information on open problems or conjectures presented in the paper. The papers appearing on this list are only references to the arXiv's versions and we do NOT store the actual papers (TeX sources or PDFs) on our servers. To read any of the papers in this list one needs to follow the arXiv link displayed on the papers' blocks.

You can search within the list using keywords, author names, and subject area. By a simple click of the Interesting button, you may anonymously indicate your interest in the problem. If you think the automatic extraction resulted in incorrect data, you may click on the False positive button instead. The Stats section shows the worldwide interest by our users on a specific problem.

  • The Spaces of Data, Information, and Knowledge


    year of publication: 2014 arXiv

    • Artificial Intelligence
  • Form factors of descendant operators: Resonance identities in the sinh-Gordon model


    year of publication: 2014 arXiv

    • Exactly Solvable and Integrable Systems
    • Mathematical Physics
  • Rank-Based Inference over Web Databases


    year of publication: 2014 arXiv

    • Databases
  • Noncommutative minisuperspace, gravity-driven acceleration and kinetic inflation


    year of publication: 2014 arXiv

  • Classical and quantum behavior of the harmonic and the quartic oscillators


    year of publication: 2014 arXiv

    • Mathematical Physics
  • Dispersive and dissipative effects in quantum field theory in curved space-time to model condensed matter systems


    year of publication: 2014 arXiv

    • Quantum Gases
  • Search for a bound H-dibaryon using local six-quark interpolating operators


    year of publication: 2014 arXiv

  • Revisiting Directed Polymers with heavy-tailed disorder


    year of publication: 2014 arXiv

    • Disordered Systems and Neural Networks
    • Mathematical Physics
  • Power enhancement of heat engines via correlated thermalization in multilevel systems


    year of publication: 2014 arXiv

  • A Generic Sample Splitting Approach for Refined Community Recovery in Stochastic Block Models


    year of publication: 2014 arXiv

    • Machine Learning
    • Statistics Theory
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