Computational cognitive models are a fundamental tool in behavioral neuroscience.

Recently, extensive literature has shown that the relationship between SC and FC is complex and not a simple one-to-one mapping.

Vision-language pretrained models have seen remarkable success, but their application to safety-critical settings is limited by their lack of interpretability.

We thank all reviewers for their thorough reading of our paper and for their detailed and insightful reviews. We answer specific questions below and will incorporate all feedback. Can you give more details on the method runtime? Table 2 shows average MIP runtimes given different architectures and solvers. MIP), and a policy iteration may take up to an hour in parallel.

Machine learning models are increasingly being scaled in both sequence length and model dimension to reach longer contexts and better performance.

Knowledge editing technology has received widespread attention for low-cost updates of incorrect or outdated knowledge in large-scale language models. However, recent research has found that edited models often exhibit varying degrees of performance degradation. The reasons behind this phenomenon and potential solutions have not yet been provided. In order to investigate the reasons for the performance decline of the edited model and optimize the editing method, this work explores the underlying reasons from both data and model perspectives.