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Ethan Gotlieb Wilcox

ACL 2026×3对齐与偏好可解释性检索与知识多模态代码
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0 一作 · 3 篇 · ACL 2026

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2026 顶会论文

3
作者位次 #3/3ACL 2026Poster· Natural Language Processing

Function Words as Statistical Cues for Language Learning

Xiulin Yang · Heidi R. Getz · Ethan Gotlieb Wilcox

摘要

What statistical properties might support learning abstract grammatical knowledge from linear input? We address this question by examining the statistical distribution of function words. Function words have been argued to aid acquisition through three distributional properties: high frequency, re...

检索与知识对齐与偏好可解释性OpenReview 项目页
作者位次 #4/5ACL 2026Poster· Natural Language Processing

What Do Prosody and Text Convey? Characterizing How Meaningful Information is Distributed Across Multiple Channels

Aditya Yadavalli · Tiago Pimentel · Tamar I Regev · Ethan Gotlieb Wilcox · Alex Warstadt

摘要

Prosody—the melody of speech—conveys critical information often not captured by the words or text of a message.In this paper, we propose an information-theoretic approach to quantify how much is conveyed by prosody that is not recoverable from text alone, and, crucially, what prosody conveys.Our...

多模态代码理论与学习动力学OpenReview 项目页
作者位次 #4/4ACL 2026Poster· Natural Language Processing

Dual Alignment Between Language Model Layers and Human Sentence Processing

Tatsuki Kuribayashi · Alex Warstadt · Yohei Oseki · Ethan Gotlieb Wilcox

摘要

A recent study (CITATION) has shown that human sentence processing behavior, typically measured on syntactically unchallenging constructions, can be effectively modeled using surprisal from early layers of large language models (LLMs). This raises the question of whether such advantages of intern...

对齐与偏好可解释性评测与基准OpenReview 项目页

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