Reproducible Multimodal Affordance Prediction

Tommaso Apicella; Alessio Xompero; Andrea Cavallaro

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arXiv · 2608.18317

Reproducible Multimodal Affordance Prediction

Tommaso Apicella·Alessio Xompero·Andrea Cavallaro

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Abstract

Affordance prediction is the identification of potential actions an agent can perform on a target object from multimodal inputs. Affordance prediction methods are difficult to evaluate and compare due to heterogeneous problem formulations, inconsistent dataset annotations, incomplete reporting of experimental protocols, and limited information about deployment conditions. These limitations challenge fair benchmarking and performance comparison. To promote transparency, we propose the Affordance Sheet, a documentation detailing task formulation with its input modalities, model architectures and training information, datasets, and experimental protocols. Affordance Sheets enable reproducible benchmarking and reliable evaluation of affordance models for real-world scenarios, including generalisation to novel conditions and human safety.

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Tommaso Apicella, Alessio Xompero, Andrea Cavallaro. 2026-08-18. Reproducible Multimodal Affordance Prediction. https://arxiv.org/abs/2608.18317

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