1 citations · 1 across the 6 of their papers we have counts for
6 papers
CxMP: A Linguistic Minimal-Pair Benchmark for Evaluating Constructional Understanding in Language Models
Miyu Oba, Saku Sugawara
Recent work has examined language models from a linguistic perspective to better understand how they acquire language. Most existing benchmarks focus on judging grammatical accepta…
BabyLM Challenge: Exploring the Effect of Variation Sets on Language Model Training Efficiency
Akari Haga, Akiyo Fukatsu, Miyu Oba +2
While current large language models have achieved a remarkable success, their data efficiency remains a challenge to overcome. Recently it has been suggested that child-directed sp…
Can Language Models Induce Grammatical Knowledge from Indirect Evidence?
Miyu Oba, Yohei Oseki, Akiyo Fukatsu +4
What kinds of and how much data is necessary for language models to induce grammatical knowledge to judge sentence acceptability? Recent language models still have much room for im…
BQA: Body Language Question Answering Dataset for Video Large Language Models
Shintaro Ozaki, Kazuki Hayashi, Miyu Oba +3
A large part of human communication relies on nonverbal cues such as facial expressions, eye contact, and body language. Unlike language or sign language, such nonverbal communicat…
How to Make the Most of LLMs' Grammatical Knowledge for Acceptability Judgments
Yusuke Ide, Yuto Nishida, Justin Vasselli +4
The grammatical knowledge of language models (LMs) is often measured using a benchmark of linguistic minimal pairs, where the LMs are presented with a pair of acceptable and unacce…
Second Language Acquisition of Neural Language Models
Miyu Oba, Tatsuki Kuribayashi, Hiroki Ouchi +1
With the success of neural language models (LMs), their language acquisition has gained much attention. This work sheds light on the second language (L2) acquisition of LMs, while…