collaborators

7 papers

cs.CL2026

Where Models Converge and Humans Diverge: A Coverage Framework for Distributional Pluralism in Open-Ended Generation

Zini Yang, Emily Wenger, Richard So

When a large language model (LLM) writes Harry Potter fanfiction, it reliably produces fundamental elements of the Hogwarts universe, such as recognizable places and characters. Hu…

cs.CL2026

Spoiler Alert: Narrative Forecasting as a Metric for Tension in LLM Storytelling

Peiqi Sui, Yutong Zhu, Tianyi Cheng +4

LLMs have so far failed both to generate consistently compelling stories and to recognize this failure--on the leading creative-writing benchmark (EQ-Bench), LLM judges rank zero-s…

cs.AI2026

Computational Hermeneutics: Evaluating generative AI as a cultural technology

Cody Kommers, Ruth Ahnert, Maria Antoniak +35

Generative AI systems are increasingly recognized as cultural technologies, yet current evaluation frameworks often treat culture as a variable to be measured rather than fundament…

cs.HC2026

What Does AI Do for Cultural Interpretation? A Randomized Experiment on Close Reading Poems with Exposure to AI Interpretation

Jiayin Zhi, Hoyt Long, Richard Jean So +1

AI demonstrates unprecedented reasoning capabilities, but its increasing integration into human reasoning via automated reading and summarization has provoked debate about its use…

cs.CL2026

Critical Confabulation: Can LLMs Hallucinate for Social Good?

Peiqi Sui, Eamon Duede, Hoyt Long +1

LLMs hallucinate, yet some confabulations can have social affordances if carefully bounded. We propose critical confabulation (inspired by critical fabulation from literary and soc…

cs.CL2026

Generative AI & Fictionality: How Novels Power Large Language Models

Edwin Roland, Richard Jean So

Generative models, like the one in ChatGPT, are powered by their training data. The models are simply next-word predictors, based on patterns learned from vast amounts of pre-exist…