🔗 Who cites «Fishing for Magikarp: Automatically Detecting Under-trained Tokens in Large Language Models»

35 papers of our library cite it (of the 149,439 whose bibliographies we read) · 8 with a page here, the most cited first · ← back to «Fishing for Magikarp: Automatically Detecting Under-trained Tokens in Large Language Models»

1. The Impact of Token Granularity on the Predictive Power of Language Model SurprisalAnnual Meeting of the Association for Computational Linguistics (ACL)Byung-Doh Oh, William Schuler2025 · 12 citations
2. Attention Sinks in Diffusion Language ModelsFindings of the Association for Computational LinguisticsMaximo Eduardo Rulli, Simone Petruzzi, Edoardo Michielon, et al.2026 · 5 citations
3. Teaching Old Tokenizers New Words: Efficient Tokenizer Adaptation for Pretrained ModelsFindings of the Association for Computational LinguisticsTaido Purason, Pavel Chizhov, Ivan P. Yamshchikov, et al.2026 · 4 citations
4. FLEXITOKENS: Flexible Tokenization for Evolving Language ModelsFindings of the Association for Computational LinguisticsAbraham Toluwase Owodunni, Orevaoghene Ahia, Sachin Kumar2026 · 3 citations
5. Anchored Sliding Window: Toward Robust and Imperceptible Linguistic SteganographyAnnual Meeting of the Association for Computational Linguistics (ACL)Ruiyi Yan, Shiao Meng, Yugo Murawaki2026
6. Enabling Stroke-Level Structural Analysis of Hieroglyphic Scripts without Language-Specific PriorsFindings of the Association for Computational LinguisticsFuwen Luo, Zihao Wan, Ziyue Wang, et al.2026
7. MUTANT: A Recipe for Multilingual Tokenizer DesignAnnual Meeting of the Association for Computational Linguistics (ACL)Souvik Rana, Ashish Kulkarni, Arul Menezes, et al.2026
8. The Challenge of Identifying the Origin of Black-Box Large Language ModelsWorkshop on Privacy in Natural Language ProcessingZiqing Yang, Yixin Wu, Yun Shen, et al.2026

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

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