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A Fine-Tuning Approach to Belief State Modeling.

, , , , , и . ICLR, OpenReview.net, (2022)

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A Fine-Tuning Approach to Belief State Modeling., , , , , и . ICLR, OpenReview.net, (2022)Non-interactive Zero-Knowledge from Non-interactive Batch Arguments., и . CRYPTO (2), том 14082 из Lecture Notes in Computer Science, стр. 38-71. Springer, (2023)Watermarking PRFs from Lattices: Stronger Security via Extractable PRFs., и . CRYPTO (3), том 11694 из Lecture Notes in Computer Science, стр. 335-366. Springer, (2019)Batch Arguments for NP and More from Standard Bilinear Group Assumptions., и . IACR Cryptol. ePrint Arch., (2022)Succinct Vector, Polynomial, and Functional Commitments from Lattices., и . IACR Cryptol. ePrint Arch., (2022)Beyond Software Watermarking: Traitor-Tracing for Pseudorandom Functions., , , и . ASIACRYPT (3), том 13092 из Lecture Notes in Computer Science, стр. 250-280. Springer, (2021)Collusion Resistant Trace-and-Revoke for Arbitrary Identities from Standard Assumptions., и . ASIACRYPT (2), том 12492 из Lecture Notes in Computer Science, стр. 66-97. Springer, (2020)Lattice-based non-interactive argument systems.. Stanford University, USA, (2018)End-to-end text recognition with convolutional neural networks., , , и . ICPR, стр. 3304-3308. IEEE Computer Society, (2012)Deep learning with COTS HPC systems., , , , , и . ICML (3), том 28 из JMLR Workshop and Conference Proceedings, стр. 1337-1345. JMLR.org, (2013)