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cs.CL2026
Narrative Theory-Driven LLM Methods for Automatic Story Generation and Understanding: A Survey
David Y. Liu, Aditya Joshi, Paul Dawson
Applications of narrative theories using large language models (LLMs) deliver promising methods in automatic story generation and understanding tasks. Our survey examines how natur…
cs.CL2026
Retell, Reward, Repeat: Reinforcement Learning for Narrative Theory-Informed Story Retelling
David Y. Liu, Xanthe Muston, Dipankar Srirag +2
Counterfactual story retelling exposes LLM shortcomings in constrained narrative solution spaces where they can no longer rely on recalling memorised training data. Ground-truth-ba…
cs.CL2025
Prompt and circumstance: A word-by-word LLM prompting approach to interlinear glossing for low-resource languages
Micha Elsner, David Liu
Partly automated creation of interlinear glossed text (IGT) has the potential to assist in linguistic documentation. We argue that LLMs can make this process more accessible to lin…