activity
20142026
most citedComputational Hermeneutics: Evaluating generative AI as a cultural technology

4 citations · 8 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL2026

Calibrated Ambiguity in Multimodal Language Models: Humans reach for cultural references, while models describe the picture

Cody Kommers, Mingrui Ye, Evelyn Gius +4

Ambiguity is often treated as a bug for AI systems to resolve---but in human communication and culture, ambiguity can also be a generative resource. From humour to politics to art,…

cs.CL2026

The House with a Million Windows: Interactive Fiction for Narrative Restorying

Cody Kommers, Sarah G Immel, Drew Hemment +1

AI-assisted writing can flatten meaning in human storytelling, enabling the production of homogeneous outputs without the intentional effort and sense-making writing entails. To ad…

cs.AI2026★ 4 cited

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.AI2026

AI as Entertainment

Cody Kommers, Ari Holtzman

Generative AI systems are predominantly designed, evaluated, and marketed as intelligent systems which will benefit society by augmenting or automating human cognitive labor, promi…

cs.CY2025★ 1 cited

Why Slop Matters

Cody Kommers, Eamon Duede, Julia Gordon +6

AI-generated "slop" is often seen as digital pollution. We argue that this dismissal of the topic risks missing important aspects of AI Slop that deserve rigorous study. AI Slop se…

cs.CL2025

Meaning Is Not A Metric: Using LLMs to make cultural context legible at scale

Cody Kommers, Drew Hemment, Maria Antoniak +4

This position paper argues that large language models (LLMs) can make cultural context, and therefore human meaning, legible at an unprecedented scale in AI-based sociotechnical sy…

cs.CL2014★ 3 cited

Outperforming Word2Vec on Analogy Tasks with Random Projections

Abram Demski, Volkan Ustun, Paul Rosenbloom +1

We present a distributed vector representation based on a simplification of the BEAGLE system, designed in the context of the Sigma cognitive architecture. Our method does not requ…