Safety
Reproducible Multimodal Affordance Prediction
arXiv:2608.18317v1 Announce Type: new Abstract: Affordance prediction is the identification of potential actions an agent can perform on a target object from multimodal inputs. Affordance prediction m
arXiv:2608.18317v1 Announce Type: new 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.
Related
- AgentHOI: Multi-Agent Reasoning for Human-Object-Interaction Video Generation via Implicit Representation Alignment
- X-OmniClaw Technical Report: A Unified Mobile Agent for Multimodal Understanding and Interaction
- LAWM-3D: Learning 3D-Aware Latent Actions from Human Videos for Generalizable Robot World Models
Source: arXiv cs.CV | 2026-08-20