Elamur Research⌕
☰
home / authors / Byung-Doh Oh / cited by

Who cites Byung-Doh Oh

117 citations of their works from 111 papers of our library (of the 140,884 whose bibliographies we read) · 13 with a page here, the most cited first · ← Byung-Doh Oh

  1. Testing the Predictions of Surprisal Theory in 11 LanguagesEthan G. Wilcox, Tiago Pimentel, Clara Meister, et al.2023 · 158 citations
  2. On the Proper Treatment of Tokenization in PsycholinguisticsMario Giulianelli, Luca Malagutti, Juan Luis Gastaldi, et al.2024 · 23 citations
  3. The Impact of Token Granularity on the Predictive Power of Language Model SurprisalByung-Doh Oh, William Schuler2025 · 12 citations
  4. Are Frequent Phrases Directly Retrieved like Idioms? An Investigation with Self-Paced Reading and Language ModelsGiulia Rambelli, Emmanuele Chersoni, Marco S. G. Senaldi, et al.2023 · 11 citations
  5. An Existence Proof for Neural Language Models That Can Explain Garden-Path Effects via SurprisalRyo Yoshida, Shinnosuke Isono, Taiga Someya, et al.2026 · 1 citation
  6. Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze SurprisalSathvik Nair, Byung-Doh Oh2026 · 1 citation
  7. Human-like Fleeting Memory Improves Language Learning but Impairs Reading Time Prediction in Transformer Language ModelsAbishek Thamma, Micha Heilbron2026 · 1 citation
  8. Probing for Reading TimesEleftheria Tsipidi, Samuel Kiegeland, Francesco Ignazio Re, et al.2026 · 1 citation
  9. Surprisal and Metaphor Novelty Judgments: Moderate Correlations and Divergent Scaling Effects Revealed by Corpus-Based and Synthetic DatasetsOmar Momen, Emilie Sitter, Berenike Herrmann, et al.2026 · 1 citation
  10. A Transparent Model of Syntactic and Semantic Cue-based RetrievalShisen Yue, John T. Hale2026
  11. Causal Inferences Are Driven by Noun Concept Specificity Evidence from Self-Paced Reading and Large Language Model SurprisalFabian Schlotterbeck, Raphael Barth2026
  12. Open-access Dataset on Acceptability Ratings of Korean Clausal Constructions by Humans and GPT ModelsGyu-Ho Shin, Soo-Hwan Lee, Chanyoung Lee2026
  13. Word predictability estimates from language models are not robust to tokenizer vocabularyKien Nguyen, Suhas Arehalli2026

98 more citing papers of our library have no page here yet.

This page in Markdown → https://md.research.elamur.ai/free/en/authors/byung-doh-oh/cited-by/