3 accepted papers
Despite recent advances in LLMs, the task of code generation is still challenging. To cope, code selection algorithms select the best program from multiple programs generated by an LLM. However, existing algorithms can fail to identify the correct program, either because they fail to distinguish non
Few-pixel attacks mislead a classifier by modifying a few pixels of an image. Their perturbation space is an ℓ₀-ball, which is not convex, unlike ℓₚ-balls for p ≥ 1. However, existing local robustness verifiers typically scale by relying on linear bound propagation, which captures convex perturbatio
We present DL2, a system for training and querying neural networks with logical constraints. Using DL2, one can declaratively specify domain knowledge constraints to be enforced during training, as well as pose queries on the model to find inputs that satisfy a set of constraints. DL2 works by trans…