2 citations · 3 across the 10 of their papers we have counts for
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Sakura at BEA 2026 Shared Task 1: What Makes Vocabulary Difficult?
Adam Nohejl, Xuanxin Wu, Yusuke Ide +3
We describe two types of models for vocabulary difficulty prediction: a high-accuracy black-box model, which achieved the top shared task result in the open track, and an explainab…
Towards Automated Lexicography: Generating and Evaluating Definitions for Learner's Dictionaries
Yusuke Ide, Adam Nohejl, Joshua Tanner +3
Dictionary definitions are an essential resource for learning word senses, but manually creating them is costly. We thus study dictionary definition generation (DDG), i.e., the gen…
Measuring the Robustness of Reference-Free Dialogue Evaluation Systems
Justin Vasselli, Adam Nohejl, Taro Watanabe
Advancements in dialogue systems powered by large language models (LLMs) have outpaced the development of reliable evaluation metrics, particularly for diverse and creative respons…
Dispersion Measures as Predictors of Lexical Decision Time, Word Familiarity, and Lexical Complexity
Adam Nohejl, Taro Watanabe
Various measures of dispersion have been proposed to paint a fuller picture of a word's distribution in a corpus, but only little has been done to validate them externally. We eval…
CoAM: Corpus of All-Type Multiword Expressions
Yusuke Ide, Joshua Tanner, Adam Nohejl +4
Multiword expressions (MWEs) refer to idiomatic sequences of multiple words. MWE identification, i.e., detecting MWEs in text, can play a key role in downstream tasks such as machi…
Difficult for Whom? A Study of Japanese Lexical Complexity
Adam Nohejl, Akio Hayakawa, Yusuke Ide +1
The tasks of lexical complexity prediction (LCP) and complex word identification (CWI) commonly presuppose that difficult to understand words are shared by the target population. M…
WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global Cuisines
Genta Indra Winata, Frederikus Hudi, Patrick Amadeus Irawan +48
Vision Language Models (VLMs) often struggle with culture-specific knowledge, particularly in languages other than English and in underrepresented cultural contexts. To evaluate th…
Beyond Film Subtitles: Is YouTube the Best Approximation of Spoken Vocabulary?
Adam Nohejl, Frederikus Hudi, Eunike Andriani Kardinata +5
Word frequency is a key variable in psycholinguistics, useful for modeling human familiarity with words even in the era of large language models (LLMs). Frequency in film subtitles…
Toward the Evaluation of Large Language Models Considering Score Variance across Instruction Templates
Yusuke Sakai, Adam Nohejl, Jiangnan Hang +2
The natural language understanding (NLU) performance of large language models (LLMs) has been evaluated across various tasks and datasets. The existing evaluation methods, however,…
Japanese Lexical Complexity for Non-Native Readers: A New Dataset
Yusuke Ide, Masato Mita, Adam Nohejl +2
Lexical complexity prediction (LCP) is the task of predicting the complexity of words in a text on a continuous scale. It plays a vital role in simplifying or annotating complex wo…