6 accepted papers
In human-robot interaction, external force measurement is fundamental to achieving robot compliance control. Parameter identification based on robot dynamics enables external force detection without expensive sensors. However, the unmodeled dynamic errors inherent in real robots pose a challenge to
Despite the high accuracy, Vision Transformer (ViT) predictions can be driven by spurious cues. Interpreting their inner workings is therefore essential for safe deployment. Sparse autoencoders (SAEs) shed light on decomposing language-model representations into concepts. However, adapting SAE-based…
The technique of combining multiple votes to enhance the quality of a decision is the core of boosting algorithms in machine learning. In particular, boosting provably increases decision quality by combining multiple "weak learners"—hypotheses that are only slightly better than random guessing—into …
Multimodal emotion recognition has garnered significant attention for its ability to integrate data from multiple modalities to enhance performance. However, physiological signals like electroencephalogram are more challenging to acquire than visual data due to higher collection costs and complexity
This letter presents OMEGA, a new open-source, multi-mode hopping platform. It consists of a rig and a middle-size robot equipped with an omnidirectional parallel 3-RSR leg, allowing for 1D, 2D, and 3D hopping modes. All modes can be easily interchanged via detachable mechanisms. A control framework
Ensemble learning is a powerful approach for improving generalization under distribution shifts, but its effectiveness heavily depends on how individual models are combined. Existing methods often optimize ensemble weights based on validation data, which may not represent unseen test distributions,…