Titlebook: AI Verification; First International Guy Avni,Mirco Giacobbe,Christian Schilling Conference proceedings 2024 The Editor(s) (if applicable)

Interjection

書目名稱AI Verification影響因子(影響力)




書目名稱AI Verification影響因子(影響力)學科排名




書目名稱AI Verification網(wǎng)絡(luò)公開度




書目名稱AI Verification網(wǎng)絡(luò)公開度學科排名




書目名稱AI Verification被引頻次




書目名稱AI Verification被引頻次學科排名




書目名稱AI Verification年度引用




書目名稱AI Verification年度引用學科排名




書目名稱AI Verification讀者反饋




書目名稱AI Verification讀者反饋學科排名

fiscal

不法行為

,Concept-Based Analysis of?Neural Networks via?Vision-Language Models,cifications for vision tasks and the lack of efficient verification procedures. In this paper, we propose to leverage emerging multimodal, vision-language, foundation models (VLMs) as a lens through which we can reason about vision models. VLMs have been trained on a large body of images accompanied

爵士樂

,Parallel Verification for?,-Equivalence of?Neural Network Quantization,emory. However, it also brings in loss of generalization and even potential errors to the models. In this work, we propose a parallelization technique for formally . the . between quantized models and their original real-valued counterparts. In order to guarantee both . and ., mixed integer linear p

浸軟

Ledger

CLEFT

修飾語

浪費物質(zhì)

Iterative Counter-Example Guided Robustness Verification for Neural Networks,y considering different types of abstraction techniques focused toward the non-linearity in the computation in the neural network. We propose a complementary approach of abstracting the neural network by discarding the neurons. Our abstraction is based on the robustness property being verified. We t

創(chuàng)造性

Grundkurs Microsoft Dynamics AXout the laborious task of manual heuristic creation and tuning, data-driven approaches demonstrate significant potential by extracting crucial patterns from a small set of data points. However, at present, symbolic methods generally surpass data-driven solvers in performance. In this work, we develo