2026
Dissecting Embodied Abilities in Multimodal Language Models through Skill-level Evaluation and Diagnosis
ICML 2026poster
Understanding the capability bottlenecks of embodied multimodal large language models (MLLMs) is crucial for improvement. However, existing embodied benchmarks fail to provide actionable insights because they focus on task-level evaluation rather than discovering capability bottlenecks. To address t…