The paper “Scalable Neural Network Verification with Branch-and-bound Inferred Cutting Planes” by Duo Zhou (University of Illinois Urbana-Champaign), Christopher Brix, Grani A Hanasusanto (Illinois) and Huan Zhang (Illinois) has been accepted for the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024) in Vancouver. The paper describes how the branch-and-bound process in neural network verification can be used to extract cuts that reduce verification time by strengthening the computed bounds.