{"ID":6267780,"CreatedAt":"2026-07-10T01:11:38.759438437Z","UpdatedAt":"2026-07-11T22:05:45.167736981Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.07952","arxiv_id":"2607.07952","title":"fog: Expressing Motion and Emotion through Function Composition of AI-Generated Code","abstract":"Motion and emotion are core parts of intelligent, expressive behavior. In this paper, we introduce fog, a function composition framework for implementing and compose motion functions. We demonstrate how fog can be used to express motion and emotion in Heider-Simmel style animations. This code generation framework can help users generate functions for verbs, adverbs, gestures, and emotions to create an open-ended motion vocabulary. It is complemented by an animation editor that helps users refine motion through direct manipulation and dynamically generated UI. We evaluate our approach with a perceptual evaluation, where we test 452 fog-generated animations to see if people can recognize the semantic meaning of the motion. We find that fog's motion functions can be recognized at 68% accuracy, a 2.68x improvement over a chance baseline. In a mixed-methods user study with professionals and novices, we show that fog in interface form can support users with more rapid iteration, exploration, and control.","short_abstract":"Motion and emotion are core parts of intelligent, expressive behavior. In this paper, we introduce fog, a function composition framework for implementing and compose motion functions. We demonstrate how fog can be used to express motion and emotion in Heider-Simmel style animations. This code generation framework can h...","url_abs":"https://arxiv.org/abs/2607.07952","url_pdf":"https://arxiv.org/pdf/2607.07952v1","authors":"[\"Vivian Liu\",\"Lydia Chilton\"]","published":"2026-07-08T22:09:03Z","proceeding":"cs.HC","tasks":"[\"cs.HC\",\"cs.CL\"]","methods":"[\"LoRA\"]","has_code":false}