Search Results for author: Adam Nohejl

Found 8 papers, 6 papers with code

Measuring the Robustness of Reference-Free Dialogue Evaluation Systems

1 code implementation12 Jan 2025 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 responses.

Dialogue Evaluation TAG

Dispersion Measures as Predictors of Lexical Decision Time, Word Familiarity, and Lexical Complexity

1 code implementation11 Jan 2025 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.

Difficult for Whom? A Study of Japanese Lexical Complexity

1 code implementation24 Oct 2024 Adam Nohejl, Akio Hayakawa, Yusuke Ide, Taro Watanabe

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.

Complex Word Identification Lexical Complexity Prediction

Toward the Evaluation of Large Language Models Considering Score Variance across Instruction Templates

no code implementations22 Aug 2024 Yusuke Sakai, Adam Nohejl, Jiangnan Hang, Hidetaka Kamigaito, Taro Watanabe

In this study, we provide English and Japanese cross-lingual datasets for evaluating the NLU performance of LLMs, which include multiple instruction templates for fair evaluation of each task, along with regular expressions to constrain the output format.

Natural Language Understanding

Japanese Lexical Complexity for Non-Native Readers: A New Dataset

2 code implementations30 Jun 2023 Yusuke Ide, Masato Mita, Adam Nohejl, Hiroki Ouchi, Taro Watanabe

Lexical complexity prediction (LCP) is the task of predicting the complexity of words in a text on a continuous scale.

Lexical Complexity Prediction

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