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20222026
most citedConstruction Grammar Provides Unique Insight into Neural Language Models

10 citations · 19 across the 12 of their papers we have counts for

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cs.CL2026

Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus Constructions

Wesley Scivetti, Ethan Wilcox, Nathan Schneider +2

Grasping the semantics of rare constructions (form-meaning pairings) has been shown to be a challenging problem that has currently only been solved by the largest LLMs. It remains…

cs.CL2024

Verbing Weirds Language (Models): Evaluation of English Zero-Derivation in Five LLMs

David R. Mortensen, Valentina Izrailevitch, Yunze Xiao +2

Lexical-syntactic flexibility, in the form of conversion (or zero-derivation) is a hallmark of English morphology. In conversion, a word with one part of speech is placed in a non-…

cs.CL2024★ 1 cited

UCxn: Typologically Informed Annotation of Constructions Atop Universal Dependencies

Leonie Weissweiler, Nina Böbel, Kirian Guiller +11

The Universal Dependencies (UD) project has created an invaluable collection of treebanks with contributions in over 140 languages. However, the UD annotations do not tell the full…

cs.CL2024

Hybrid Human-LLM Corpus Construction and LLM Evaluation for Rare Linguistic Phenomena

Leonie Weissweiler, Abdullatif Köksal, Hinrich Schütze

Argument Structure Constructions (ASCs) are one of the most well-studied construction groups, providing a unique opportunity to demonstrate the usefulness of Construction Grammar (…

cs.CL2024★ 1 cited

Constructions Are So Difficult That Even Large Language Models Get Them Right for the Wrong Reasons

Shijia Zhou, Leonie Weissweiler, Taiqi He +3

In this paper, we make a contribution that can be understood from two perspectives: from an NLP perspective, we introduce a small challenge dataset for NLI with large lexical overl…

cs.CL2023★ 2 cited

Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model

Leonie Weissweiler, Valentin Hofmann, Anjali Kantharuban +10

Large language models (LLMs) have recently reached an impressive level of linguistic capability, prompting comparisons with human language skills. However, there have been relative…

cs.CL2023★ 1 cited

A Crosslingual Investigation of Conceptualization in 1335 Languages

Yihong Liu, Haotian Ye, Leonie Weissweiler +4

Languages differ in how they divide up the world into concepts and words; e.g., in contrast to English, Swahili has a single concept for `belly' and `womb'. We investigate these di…

cs.CL2023★ 1 cited

How to Distill your BERT: An Empirical Study on the Impact of Weight Initialisation and Distillation Objectives

Xinpeng Wang, Leonie Weissweiler, Hinrich Schütze +1

Recently, various intermediate layer distillation (ILD) objectives have been shown to improve compression of BERT models via Knowledge Distillation (KD). However, a comprehensive e…

cs.CL2023

Crosslingual Transfer Learning for Low-Resource Languages Based on Multilingual Colexification Graphs

Yihong Liu, Haotian Ye, Leonie Weissweiler +2

In comparative linguistics, colexification refers to the phenomenon of a lexical form conveying two or more distinct meanings. Existing work on colexification patterns relies on an…

cs.CL2023★ 10 cited

Construction Grammar Provides Unique Insight into Neural Language Models

Leonie Weissweiler, Taiqi He, Naoki Otani +3

Construction Grammar (CxG) has recently been used as the basis for probing studies that have investigated the performance of large pretrained language models (PLMs) with respect to…

cs.CL2022★ 3 cited

The Better Your Syntax, the Better Your Semantics? Probing Pretrained Language Models for the English Comparative Correlative

Leonie Weissweiler, Valentin Hofmann, Abdullatif Köksal +1

Construction Grammar (CxG) is a paradigm from cognitive linguistics emphasising the connection between syntax and semantics. Rather than rules that operate on lexical items, it pos…

cs.CL2022

CaMEL: Case Marker Extraction without Labels

Leonie Weissweiler, Valentin Hofmann, Masoud Jalili Sabet +1

We introduce CaMEL (Case Marker Extraction without Labels), a novel and challenging task in computational morphology that is especially relevant for low-resource languages. We prop…