AssemLM uses a specialized point cloud encoder inside a multimodal LLM to reach state-of-the-art 6D pose prediction for assembly tasks, backed by a new 900K-sample benchmark called AssemBench.
For modality ablation, we train and evaluate the model with one modality removed at a time, and report the results in the top part of Table V
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AssemLM: Spatial Reasoning Multimodal Large Language Models for Robotic Assembly
AssemLM uses a specialized point cloud encoder inside a multimodal LLM to reach state-of-the-art 6D pose prediction for assembly tasks, backed by a new 900K-sample benchmark called AssemBench.