Cover Image

The Astonishing Ability of Large Language Models to Parse Jabberwockified Language

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lupyan, Gary, Yang, Senyi
Format:	Preprint
Published:	2026
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Large language models have learned to use language
by: Lupyan, Gary
Published: (2025)

The unreasonable effectiveness of pattern matching
by: Lupyan, Gary, et al.
Published: (2026)

How important is language for human-like intelligence?
by: Lupyan, Gary, et al.
Published: (2025)

Language models align with human judgments on key grammatical constructions
by: Hu, Jennifer, et al.
Published: (2024)

Arabic Morphosyntactic Tagging and Dependency Parsing with Large Language Models
by: Adel, Mohamed, et al.
Published: (2026)

Disentangling Memory and Reasoning Ability in Large Language Models
by: Jin, Mingyu, et al.
Published: (2024)

A System for Name and Address Parsing with Large Language Models
by: Tarannum, Adeeba, et al.
Published: (2026)

A Comparative Study on Large Language Models for Log Parsing
by: Astekin, Merve, et al.
Published: (2024)

Extracting and Combining Abilities For Building Multi-lingual Ability-enhanced Large Language Models
by: Chen, Zhipeng, et al.
Published: (2024)

Exploring Continual Fine-Tuning for Enhancing Language Ability in Large Language Model
by: Aggarwal, Divyanshu, et al.
Published: (2024)

ICLEval: Evaluating In-Context Learning Ability of Large Language Models
by: Chen, Wentong, et al.
Published: (2024)

MATA: Mindful Assessment of the Telugu Abilities of Large Language Models
by: Kranti, Chalamalasetti, et al.
Published: (2025)

Are Emergent Abilities in Large Language Models just In-Context Learning?
by: Lu, Sheng, et al.
Published: (2023)

First Tragedy, then Parse: History Repeats Itself in the New Era of Large Language Models
by: Saphra, Naomi, et al.
Published: (2023)

Rethinking Semantic Parsing for Large Language Models: Enhancing LLM Performance with Semantic Hints
by: An, Kaikai, et al.
Published: (2024)

Large Language Models have Intrinsic Self-Correction Ability
by: Liu, Dancheng, et al.
Published: (2024)

Psychological Counseling Ability of Large Language Models
by: Peng, Fangyu, et al.
Published: (2025)

Counting Ability of Large Language Models and Impact of Tokenization
by: Zhang, Xiang, et al.
Published: (2024)

STBench: Assessing the Ability of Large Language Models in Spatio-Temporal Analysis
by: Li, Wenbin, et al.
Published: (2024)

Distilling Reasoning Ability from Large Language Models with Adaptive Thinking
by: Chen, Xiaoshu, et al.
Published: (2024)

Challenging the Abilities of Large Language Models in Italian: a Community Initiative
by: Nissim, Malvina, et al.
Published: (2025)

Evaluating the Ability of Large Language Models to Reason about Cardinal Directions
by: Cohn, Anthony G, et al.
Published: (2024)

Deception Abilities Emerged in Large Language Models
by: Hagendorff, Thilo
Published: (2023)

Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue
by: Gu, Jia-Chen, et al.
Published: (2024)

Towards Compositionally Generalizable Semantic Parsing in Large Language Models: A Survey
by: Mannekote, Amogh
Published: (2024)

Emergent Abilities of Large Language Models under Continued Pretraining for Language Adaptation
by: Elhady, Ahmed, et al.
Published: (2025)

Evaluating and Advancing Multimodal Large Language Models in Perception Ability Lens
by: Chen, Feng, et al.
Published: (2024)

Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model
by: Geigle, Gregor, et al.
Published: (2025)

Investigating Large Language Models' Linguistic Abilities for Text Preprocessing
by: Braga, Marco, et al.
Published: (2025)

Eliciting Causal Abilities in Large Language Models for Reasoning Tasks
by: Wang, Yajing, et al.
Published: (2024)

Evaluating the Ability of Large Language Models to Reason about Cardinal Directions, Revisited
by: Cohn, Anthony G, et al.
Published: (2025)

The SIFo Benchmark: Investigating the Sequential Instruction Following Ability of Large Language Models
by: Chen, Xinyi, et al.
Published: (2024)

Evaluation of Instruction-Following Ability for Large Language Models on Story-Ending Generation
by: Hida, Rem, et al.
Published: (2024)

Large Language Model Displays Emergent Ability to Interpret Novel Literary Metaphors
by: Ichien, Nicholas, et al.
Published: (2023)

Can Perplexity Reflect Large Language Model's Ability in Long Text Understanding?
by: Hu, Yutong, et al.
Published: (2024)

Citation Parsing and Analysis with Language Models
by: Sarin, Parth, et al.
Published: (2025)

Self-Evolving Critique Abilities in Large Language Models
by: Tang, Zhengyang, et al.
Published: (2025)

Emergent Abilities in Large Language Models: A Survey
by: Berti, Leonardo, et al.
Published: (2025)

Unicode Normalization and Grapheme Parsing of Indic Languages
by: Ansary, Nazmuddoha, et al.
Published: (2023)

FinDABench: Benchmarking Financial Data Analysis Ability of Large Language Models
by: Liu, Shu, et al.
Published: (2024)