Byung-Doh Oh
18 papers · 2019–2026 · 7 conferences · across top CS/AI conferences
Achievements
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🌉 Interdisciplinary Bridge 🌈 Renaissance Researcher (6) 🏃 Academic Marathon (6) 🌍 Conference Polyglot (7) 🗺️ Taxonomy Completionist (35)
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Taxonomy Completionist
(35)
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Keyword Pioneer
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Hot Topic Early Bird
🏆
Keyword Champion
(2)
🧬
Topic Evolution
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Dynamic Duo
(15)
💎
Century Club
(17)
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Unstoppable
(5)
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Keyword Collector
(65)
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The Questioner
(2)
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Prolific Year
(6)
Conferences
ACL (6)
EMNLP (5)
IJCNLP (2)
NAACL (2)
AACL (1)
COLING (1)
EACL (1)
Top co-authors
Keywords
reading time
(8)
language model
(6)
psycholinguistic modeling
(4)
cognitive modeling
(2)
word entropy
(2)
language modeling
(2)
language model surprisal
(2)
monte carlo estimation
(2)
self-paced reading
(2)
reading time prediction
(2)
sentence processing
(2)
word frequency
(2)
character model
(2)
surprisal estimation
(2)
first-token entropy
(2)
hidden state
(1)
grammar induction
(1)
semantic processing
(1)
probabilistic modeling
(1)
incremental parsing
(1)
Papers
Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze Surprisal
ACL 2026
How Well Does First-Token Entropy Approximate Word Entropy as a Psycholinguistic Predictor?
AACL 2025
The Impact of Token Granularity on the Predictive Power of Language Model Surprisal
ACL 2025
The Inverse Scaling Effect of Pre-Trained Language Model Surprisal Is Not Due to Data Leakage
ACL 2025
Linear Recency Bias During Training Improves Transformers’ Fit to Reading Times
COLING 2025
How Well Does First-Token Entropy Approximate Word Entropy as a Psycholinguistic Predictor?
IJCNLP 2025
Leading Whitespaces of Language Models’ Subword Vocabulary Pose a Confound for Calculating Word Probabilities
EMNLP 2024
Frequency Explains the Inverse Correlation of Large Language Models’ Size, Training Data Amount, and Surprisal’s Fit to Reading Times
EACL 2024
Transformer-Based Language Model Surprisal Predicts Human Reading Times Best with About Two Billion Training Tokens
EMNLP 2023
Token-wise Decomposition of Autoregressive Language Model Hidden States for Analyzing Model Predictions
ACL 2023
Entropy- and Distance-Based Predictors From GPT-2 Attention Patterns Predict Reading Times Over and Above GPT-2 Surprisal
EMNLP 2022
Team Ohio State at CMCL 2021 Shared Task: Fine-Tuned RoBERTa for Eye-Tracking Data Prediction
NAACL 2021
Coreference-aware Surprisal Predicts Brain Response
EMNLP 2021
Character-based PCFG Induction for Modeling the Syntactic Acquisition of Morphologically Rich Languages
EMNLP 2021
Surprisal Estimators for Human Reading Times Need Character Models
IJCNLP 2021
Surprisal Estimators for Human Reading Times Need Character Models
ACL 2021
Contributions of Propositional Content and Syntactic Category Information in Sentence Processing
NAACL 2021
THOMAS: The Hegemonic OSU Morphological Analyzer using Seq2seq
ACL 2019