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The recent surge in artificial intelligence (AI), characterized by the prominence of large language models (LLMs), has ushered in fundamental transformations across the globe.
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PLONK: Permutations over Lagrange-bases for Oecumenical Noninteractive arguments of Knowledge
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plookup: A simplified polynomial protocol for lookup tables
Ariel Gabizon and Zachary J. Williamson. 2020 · 2020
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vCNN: Verifiable Convolutional Neural Network
Seunghwa Lee, Hankyung Ko, Jihye Kim, and Hyunok Oh. 2020 · 2020
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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Caulk: Lookup Arguments in Sublinear Time. In Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, CCS 2022, Los Angeles, CA, USA, November 7-11, 2022 , Heng Yin, Angelos Stavrou, Cas Cremers, and Elaine Shi (Eds.). ACM, 3121–3134
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Baloo: Nearly Optimal Lookup Arguments
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OPT: Open Pre-trained Transformer Language Models
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Gemini: A Family of Highly Capable Multimodal Models
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ZEN: Efficient Zero-Knowledge Proofs for Neural Networks
Boyuan Feng, Lianke Qin, Zhenfei Zhang, Yufei Ding, and Shumo Chu. 2021 · 2021
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zkCNN: Zero Knowledge Proofs for Convolutional Neural Network Predictions and Accuracy. In CCS ’21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15 - 19, 2021 , Yongdae Kim, Jong Kim, Giovanni Vigna, and Elaine Shi (Eds.). ACM, 2968–2985
Tianyi Liu, Xiang Xie, and Yupeng Zhang. 2021 · 2021
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Mystique: Efficient Conversions for Zero-Knowledge Proofs with Applications to Machine Learning. In 30th USENIX Security Symposium, USENIX Security 2021, August 11-13, 2021 , Michael Bailey and Rachel Greenstadt (Eds.). USENIX Association, 501–518
Chenkai Weng, Kang Yang, Xiang Xie, Jonathan Katz, and Xiao Wang. 2021 · 2021
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Doubly Efficient Interactive Proofs for General Arithmetic Circuits with Linear Prover Time. In CCS ’21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15 - 19, 2021 , Yongdae Kim, Jong Kim, Giovanni Vigna, and Elaine Shi (Eds.). ACM, 159–177
Jiaheng Zhang, Tianyi Liu, Weijie Wang, Yinuo Zhang, Dawn Song, Xiang Xie, and Yupeng Zhang. 2021 · 2021
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VeriML: Enabling Integrity Assurances and Fair Payments for Machine Learning as a Service
Lingchen Zhao, Qian Wang, Cong Wang, Qi Li, Chao Shen, and Bo Feng. 2021 · 2021
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Succinct Non-Interactive Arguments via Linear Interactive Proofs
Nir Bitansky, Alessandro Chiesa, Yuval Ishai, Rafail Ostrovsky, and Omer Paneth. 2022 · 2022
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LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale
Tim Dettmers, Mike Lewis, Younes Belkada, and Luke Zettlemoyer. 2022 · 2022
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cq: Cached quotients for fast lookups
Liam Eagen, Dario Fiore, and Ariel Gabizon. 2022 · 2022
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QuIP: 2-Bit Quantization of Large Language Models With Guarantees
Jerry Chee, Yaohui Cai, Volodymyr Kuleshov, and Christopher De Sa. 2023 · 2023
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HyperPlonk: Plonk with Linear-Time Prover and High-Degree Custom Gates. In Advances in Cryptology - EUROCRYPT 2023 - 42nd Annual International Conference on the Theory and Applications of Cryptographic Techniques, Lyon, France, April 23-27, 2023, Proceedings, Part II (Lecture Notes in Computer Science, Vol. 14005) , Carmit Hazay and Martijn Stam (Eds.). Springer, 499–530
Binyi Chen, Benedikt Bünz, Dan Boneh, and Zhenfei Zhang. 2023 · 2023
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PaLM: Scaling Language Modeling with Pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, and Noah Fiedel. 2023 · 2023
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QLoRA: Efficient Finetuning of Quantized LLMs
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer. 2023 · 2023
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QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models
Elias Frantar and Dan Alistarh. 2023 · 2023
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Experimenting with Zero-Knowledge Proofs of Training
Sanjam Garg, Aarushi Goel, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Guru-Vamsi Policharla, and Mingyuan Wang. 2023 · 2023
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Unbiased Watermark for Large Language Models
Zhengmian Hu, Lichang Chen, Xidong Wu, Yihan Wu, Hongyang Zhang, and Heng Huang. 2023 · 2023
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A Watermark for Large Language Models. In International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA (Proceedings of Machine Learning Research, Vol. 202) , Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, and Jonathan Scarlett (Eds.). PMLR, 17061–17084
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, and Tom Goldstein. 2023 · 2023
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AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Xingyu Dang, and Song Han. 2023 · 2023
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OpenAI. 2023 · 2023
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RoFormer: Enhanced transformer with Rotary Position Embedding
Jianlin Su, Murtadha H. M. Ahmed, Yu Lu, Shengfeng Pan, Wen Bo, and Yunfeng Liu. 2024 · 2023
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LLaMA: Open and Efficient Foundation Language Models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurélien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023a · 2023
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ezDPS: An Efficient and Zero-Knowledge Machine Learning Inference Pipeline
Haodi Wang and Thang Hoang. 2023 · 2023
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pvCNN: Privacy-Preserving and Verifiable Convolutional Neural Network Testing
Jia-Si Weng, Jian Weng, Gui Tang, Anjia Yang, Ming Li, and Jia-Nan Liu. 2023 · 2023
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SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models. In International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA (Proceedings of Machine Learning Research, Vol. 202) , Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, and Jonathan Scarlett (Eds.). PMLR, 38087–38099
Guangxuan Xiao, Ji Lin, Mickaël Seznec, Hao Wu, Julien Demouth, and Song Han. 2023 · 2023
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MCL: A portable and fast pairing-based cryptography library
Shigeo Mitsunari. 2023 · 2024
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Ligero++: A New Optimized Sublinear IOP. In CCS ’20: 2020 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, USA, November 9-13, 2020 , Jay Ligatti, Xinming Ou, Jonathan Katz, and Giovanni Vigna (Eds.). ACM, 2025–2038
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Zero Knowledge Proofs for Decision Tree Predictions and Accuracy. In CCS ’20: 2020 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, USA, November 9-13, 2020 , Jay Ligatti, Xinming Ou, Jonathan Katz, and Giovanni Vigna (Eds.). ACM, 2039–2053
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