🔗 Who cites «Towards Data Contamination Detection for Modern Large Language Models: Limitations, Inconsistencies, and Oracle Challenges»

14 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · ← back to «Towards Data Contamination Detection for Modern Large Language Models: Limitations, Inconsistencies, and Oracle Challenges»

1. Towards Holistic Evaluation of Large Audio-Language Models: A Comprehensive SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Chih-Kai Yang, Neo S. Ho, Hung-yi Lee2025 · 17 citations
2. ClaimDB: A Fact Verification Benchmark over Large Structured DataAnnual Meeting of the Association for Computational Linguistics (ACL)Michael Theologitis, Preetam Prabhu Srikar Dammu, Chirag Shah, et al.2026 · 2 citations
3. Are LLM Benchmarks Already Contaminated? A Systematic Review of Contamination Detection MethodsWorkshop on Generation, Evaluation and Metrics (GEM)Erfan Nourbakhsh, Mohammad Sadegh Sirjani, Amir Mousavi, et al.2026
4. From Shijing to English and German: Resources and Evaluation for LLM Translation of Early Chinese PoetryFindings of the Association for Computational LinguisticsYing Jiao, Meng Sun2026
5. Obscuring Data Contamination Through Translation: Evidence from Arabic CorporaarXiv:2601.14994Chaymaa Abbas, Nour Shamaa, Mariette Awad2026
6. Text-to-SQL Task-oriented Dialogue Ontology ConstructionTransactions of the Association for Computational Linguistics (TACL)Renato Vukovic, Carel van Niekerk, Michael Heck, et al.2026

8 more papers of our library cite it; they have no page here yet.

This page in Markdown → https://md.research.elamur.ai/free/en/papers/samuel-2025-data-contamination-detection-modern-large/cited-by/