Beyond Journals: Rethinking Research Evaluation in Hungarian Computer Science

• URL: http://arxiv.org/abs/2606.10726v1
• Date: Tue, 09 Jun 2026 11:33:51 GMT
• Title: Beyond Journals: Rethinking Research Evaluation in Hungarian Computer Science
• Abstract summary: This study examines the role of top-tier conference publications in Hungarian computer science research.<n>We show that the national scientometric practice diverges from international norms, creating incentive distortions in researcher evaluation.
• Score: 7.2636592672943285
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This study examines the role of top-tier conference publications in Hungarian computer science research. We show that the national scientometric practice, which is currently journal-oriented, diverges from international norms, creating incentive distortions in researcher evaluation. By linking multiple databases (iCore, DBLP, MTMT, MTA-ATT), we mapped Hungarian-affiliated CORE A* and A conference papers, their temporal and thematic distribution, and author trajectories. Our results indicate that, in theoretical fields, publishing at international conferences became common earlier than in applied fields. At the same time, in applied fields, successful researchers are more likely to continue their careers in foreign institutions or in industry positions. Overall, a substantial share of the already established, internationally most successful researchers are now affiliated with institutions abroad. We recommend recognizing CORE A* papers as equivalent to D1 and CORE A papers as equivalent to Q1 journals in national evaluation systems.

Related papers

• AutoResearchBench: Benchmarking AI Agents on Complex Scientific Literature Discovery [55.70879973230979]
  AutoResearchBench is a benchmark for autonomous scientific literature discovery.<n>Compared to previous benchmarks on agentic web browsing, AutoResearchBench is research-oriented.<n>Even the most powerful LLMs, despite having largely conquered general agentic web-browsing benchmarks such as BrowseComp, achieve only 9.39% accuracy on Deep Research and 9.31% IoU on Wide Research.
  arXiv  Detail & Related papers  (2026-04-28T06:05:17Z)
• WisPaper: Your AI Scholar Search Engine [55.07907253175705]
  textscWisPaper is an intelligent academic retrieval and literature management platform.<n>It provides a closed-loop workflow that seamlessly connects literature discovery, management, and continuous tracking of research frontiers.<n>The platform is publicly accessible and serves researchers across academia and industry.
  arXiv  Detail & Related papers  (2025-12-07T15:10:20Z)
• ICLR Points: How Many ICLR Publications Is One Paper in Each Area? [0.8702432681310401]
  We introduce the concept of ICLR points, defined as the average effort required to produce one publication at top-tier machine learning conferences.<n>We quantitatively measure and compare the average publication effort across 27 computer science sub-areas.<n>Our analysis reveals significant differences in average publication effort, validating anecdotal perceptions.
  arXiv  Detail & Related papers  (2025-03-20T18:23:35Z)
• Cultural Differences and Perverse Incentives in Science Create a Bad Mix: Exploring Country-Level Publication Bias in Select ACM Conferences [0.0789257770465417]
  In the era of big science, many national governments are helping to build well-funded teams of scientists to serve nationalistic ambitions.<n>We provide evidence that indicates significant inequality using standard Gini Index metrics in the publication rates of individual scientists.<n>Scientists who were affiliated with the top-5 countries were found to be contributing significantly more to the inequality in publication rates than others.
  arXiv  Detail & Related papers  (2025-01-28T18:52:59Z)
• Position: AI/ML Influencers Have a Place in the Academic Process [82.2069685579588]
  We investigate the role of social media influencers in enhancing the visibility of machine learning research. We have compiled a comprehensive dataset of over 8,000 papers, spanning tweets from December 2018 to October 2023. Our statistical and causal inference analysis reveals a significant increase in citations for papers endorsed by these influencers.
  arXiv  Detail & Related papers  (2024-01-24T20:05:49Z)
• Analyzing the Impact of Companies on AI Research Based on Publications [1.450405446885067]
  We compare academic- and company-authored AI publications published in the last decade. We find that the citation count an individual publication receives is significantly higher when it is (co-authored) by a company.
  arXiv  Detail & Related papers  (2023-10-31T13:27:04Z)
• A Comprehensive Study of Groundbreaking Machine Learning Research: Analyzing highly cited and impactful publications across six decades [1.6442870218029522]
  Machine learning (ML) has emerged as a prominent field of research in computer science and other related fields. It is crucial to understand the landscape of highly cited publications to identify key trends, influential authors, and significant contributions made thus far.
  arXiv  Detail & Related papers  (2023-08-01T21:43:22Z)
• Analyzing the State of Computer Science Research with the DBLP Discovery Dataset [0.0]
  We conduct a scientometric analysis to uncover the implicit patterns hidden in CS metadata. We introduce the CS-Insights system, an interactive web application to analyze CS publications with various dashboards, filters, and visualizations. Both D3 and CS-Insights are open-access, and CS-Insights can be easily adapted to other datasets in the future.
  arXiv  Detail & Related papers  (2022-12-01T16:27:42Z)
• Investigating Fairness Disparities in Peer Review: A Language Model Enhanced Approach [77.61131357420201]
  We conduct a thorough and rigorous study on fairness disparities in peer review with the help of large language models (LMs) We collect, assemble, and maintain a comprehensive relational database for the International Conference on Learning Representations (ICLR) conference from 2017 to date. We postulate and study fairness disparities on multiple protective attributes of interest, including author gender, geography, author, and institutional prestige.
  arXiv  Detail & Related papers  (2022-11-07T16:19:42Z)
• Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review [52.359007622096684]
  Peer review is a key component of the publishing process in most fields of science. Existing NLP studies focus on the analysis of individual texts. editorial assistance often requires modeling interactions between pairs of texts.
  arXiv  Detail & Related papers  (2022-04-22T16:39:38Z)
• What's New? Summarizing Contributions in Scientific Literature [85.95906677964815]
  We introduce a new task of disentangled paper summarization, which seeks to generate separate summaries for the paper contributions and the context of the work. We extend the S2ORC corpus of academic articles by adding disentangled "contribution" and "context" reference labels. We propose a comprehensive automatic evaluation protocol which reports the relevance, novelty, and disentanglement of generated outputs.
  arXiv  Detail & Related papers  (2020-11-06T02:23:01Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.