{"total":17,"rows":[{"id":"2305.05172","title":"Logic for Explainable AI","created":"2023-05-09","cited_by_count":23,"area":null},{"id":"2301.07068","title":"The #DNN-Verification Problem: Counting Unsafe Inputs for Deep Neural Networks","created":"2023-01-17","cited_by_count":19,"area":null},{"id":"2505.18585","title":"RvLLM: LLM Runtime Verification with Domain Knowledge","created":"2025-05-24","cited_by_count":17,"area":null},{"id":"2103.07633","title":"Attack as Defense: Characterizing Adversarial Examples using Robustness","created":"2021-03-13","cited_by_count":14,"area":null},{"id":"2212.11138","title":"QVIP: An ILP-based Formal Verification Approach for Quantized Neural Networks","created":"2022-12-10","cited_by_count":12,"area":null},{"id":"2207.00759","title":"Abstraction and Refinement: Towards Scalable and Exact Verification of Neural Networks","created":"2022-07-02","cited_by_count":11,"area":null},{"id":"2206.03351","title":"AS2T: Arbitrary Source-To-Target Adversarial Attack on Speaker Recognition Systems","created":"2022-06-07","cited_by_count":10,"area":null},{"id":"2212.02781","title":"QEBVerif: Quantization Error Bound Verification of Neural Networks","created":"2022-12-06","cited_by_count":9,"area":null},{"id":"2208.08609","title":"A Scalable, Interpretable, Verifiable & Differentiable Logic Gate Convolutional Neural Network Architecture From Truth Tables","created":"2022-08-18","cited_by_count":4,"area":null},{"id":"2110.08042","title":"Adversarial Attacks on ML Defense Models Competition","created":"2021-10-15","cited_by_count":3,"area":null},{"id":"2502.16286","title":"Verification of Bit-Flip Attacks against Quantized Neural Networks","created":"2025-02-22","cited_by_count":2,"area":null},{"id":"2301.02288","title":"gRoMA: a Tool for Measuring the Global Robustness of Deep Neural Networks","created":"2023-01-05","cited_by_count":1,"area":null},{"id":"2312.05890","title":"Scaling #DNN-Verification Tools with Efficient Bound Propagation and Parallel Computing","created":"2023-12-10","cited_by_count":1,"area":null},{"id":"2405.17049","title":"Verifying Properties of Binary Neural Networks Using Sparse Polynomial Optimization","created":"2024-05-27","cited_by_count":1,"area":null},{"id":"2412.13229","title":"Training Verification-Friendly Neural Networks via Neuron Behavior Consistency","created":"2024-12-17","cited_by_count":1,"area":null},{"id":"2307.15907","title":"An Automata-Theoretic Approach to Synthesizing Binarized Neural Networks","created":"2023-07-29","cited_by_count":0,"area":null},{"id":"2602.13128","title":"Eventizing Traditionally Opaque Binary Neural Networks as 1-safe Petri net Models","created":"2026-02-13","cited_by_count":0,"area":null}],"next_cursor":null}