3 accepted papers
Jung et al. (2025) introduce a hypothesis testing framework for guaranteeing agreement between large language models (LLMs) and human judgments, relying on the assumption that the model’s estimated confidence is monotonic with respect to human-disagreement risk. In practice, however, this assumption…
When robots replicate human actions in peg-in-hole assembly tasks, such as USB Type-A insertion and removal, the complexity of the process and frequent obstructions from the inner walls make it difficult for robots to handle collisions or avoid jamming. These difficulties contribute to a low success
Earth observation foundation models have shown strong generalization across multiple Earth observation tasks, but their robustness under real-world perturbations remains underexplored. To bridge this gap, we introduce REOBench, the first comprehensive benchmark for evaluating the robustness of Earth…