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MICRO-36., pp. 7-18, IEEE, 2003."},{"key":"e_1_3_2_1_44_1","first-page":"241","volume-title":"Effort: Enhancing energy efficiency and error resilience of a near-threshold tensor processing unit,'' in 2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC)","author":"Gundi N. D.","year":"2020","unstructured":"N. D. Gundi, T. Shabanian, P. Basu, P. Pandey, S. Roy, K. Chakraborty, and Z. Zhang, ''Effort: Enhancing energy efficiency and error resilience of a near-threshold tensor processing unit,'' in 2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 241-246, IEEE, 2020."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2018.2841824"},{"key":"e_1_3_2_1_46_1","volume-title":"Algorithm-based fault tolerance for matrix operations,'' IEEE transactions on computers","author":"Huang K.-H.","unstructured":"K.-H. Huang and J. A. 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Silv\u00e9n, ''Algorithm level error detection in low voltage systolic array,'' IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 69, no. 2, pp. 569-573, 2021.","journal-title":"IEEE Transactions on Circuits and Systems II: Express Briefs"},{"key":"e_1_3_2_1_49_1","volume-title":"Approxabft: Approximate algorithm-based fault tolerance for vision transformers,'' arXiv preprint arXiv:2302.10469","author":"Xue X.","year":"2023","unstructured":"X. Xue, C. Liu, H. Huang, B. Liu, Y. Wang, B. Yang, T. Luo, L. Zhang, H. Li, and X. Li, ''Approxabft: Approximate algorithm-based fault tolerance for vision transformers,'' arXiv preprint arXiv:2302.10469, 2023."},{"key":"e_1_3_2_1_50_1","first-page":"1507","volume-title":"Automation & Test in Europe Conference & Exhibition (DATE)","author":"Schorn C.","year":"2019","unstructured":"C. Schorn, A. Guntoro, and G. Ascheid, ''An efficient bit-flip resilience optimization method for deep neural networks,'' in 2019 Design, Automation & Test in Europe Conference & Exhibition (DATE), pp. 1507-1512, IEEE, 2019."},{"key":"e_1_3_2_1_51_1","first-page":"1","volume-title":"Automation & Test in Europe Conference & Exhibition (DATE)","author":"Kim S.","year":"2018","unstructured":"S. Kim, P. Howe, T. Moreau, A. Alaghi, L. Ceze, and V. Sathe, ''Matic: Learning around errors for efficient low-voltage neural network accelerators,'' in 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE), pp. 1-6, IEEE, 2018."},{"key":"e_1_3_2_1_52_1","first-page":"1","article-title":"Noise injection adaption: End-to-end reram crossbar non-ideal effect adaption for neural network mapping","author":"He Z.","year":"2019","unstructured":"Z. He, J. Lin, R. Ewetz, J.-S. Yuan, and D. 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Raychowdhury, ''Mulberry: Enabling bit-error robustness for energy-efficient multi-agent autonomous systems,'' in Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2, pp. 746-762, 2024.","journal-title":"Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems"},{"key":"e_1_3_2_1_54_1","first-page":"88","volume-title":"Exploiting temporal data diversity for detecting safety-critical faults in av compute systems,'' in 2022 52nd Annual IEEE\/IFIP International Conference on Dependable Systems and Networks (DSN)","author":"Jha S.","year":"2022","unstructured":"S. Jha, S. Cui, T. Tsai, S. K. S. Hari, M. B. Sullivan, Z. T. Kalbarczyk, S. W. Keckler, and R. K. Iyer, ''Exploiting temporal data diversity for detecting safety-critical faults in av compute systems,'' in 2022 52nd Annual IEEE\/IFIP International Conference on Dependable Systems and Networks (DSN), pp. 88-100, IEEE, 2022."},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/3647638"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/3627828"},{"key":"e_1_3_2_1_57_1","first-page":"1","volume-title":"Storage and Analysis","author":"Li G.","year":"2017","unstructured":"G. Li, S. K. S. Hari, M. Sullivan, T. Tsai, K. Pattabiraman, J. Emer, and S. W. Keckler, ''Understanding error propagation in deep learning neural network (dnn) accelerators and applications,'' in Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pp. 1-12, 2017."},{"key":"e_1_3_2_1_58_1","first-page":"1","article-title":"A framework for quantifying the resilience of deep neural networks","author":"Reagen B.","year":"2018","unstructured":"B. Reagen, U. Gupta, L. Pentecost, P. Whatmough, S. K. Lee, N. Mulholland, D. Brooks, and G.-Y. Wei, ''Ares: A framework for quantifying the resilience of deep neural networks,'' in Proceedings of the 55th Annual Design Automation Conference, pp. 1-6, 2018.","journal-title":"Proceedings of the 55th Annual Design Automation Conference"},{"key":"e_1_3_2_1_59_1","first-page":"127","article-title":"Optimizing selective protection for cnn resilience","author":"Mahmoud A.","year":"2021","unstructured":"A. Mahmoud, S. K. S. Hari, C. W. Fletcher, S. V. Adve, C. Sakr, N. R. Shanbhag, P. Molchanov, M. B. Sullivan, T. Tsai, and S. W. Keckler, ''Optimizing selective protection for cnn resilience.,'' in ISSRE, pp. 127-138, 2021.","journal-title":"ISSRE"},{"key":"e_1_3_2_1_60_1","first-page":"841","volume-title":"Analyzing and improving fault tolerance of learning-based navigation systems,'' in 2021 58th ACM\/IEEE Design Automation Conference (DAC)","author":"Wan Z.","year":"2021","unstructured":"Z. Wan, A. Anwar, Y.-S. Hsiao, T. Jia, V. J. Reddi, and A. Raychowdhury, ''Analyzing and improving fault tolerance of learning-based navigation systems,'' in 2021 58th ACM\/IEEE Design Automation Conference (DAC), pp. 841-846, IEEE, 2021."},{"key":"e_1_3_2_1_61_1","first-page":"659","volume-title":"Resilience assessment of large language models under transient hardware faults,'' in 2023 IEEE 34th International Symposium on Software Reliability Engineering (ISSRE)","author":"Agarwal U. K.","year":"2023","unstructured":"U. K. Agarwal, A. Chan, and K. Pattabiraman, ''Resilience assessment of large language models under transient hardware faults,'' in 2023 IEEE 34th International Symposium on Software Reliability Engineering (ISSRE), pp. 659-670, IEEE, 2023."},{"key":"e_1_3_2_1_62_1","first-page":"1","volume-title":"Realm: Reliable and efficient large language model inference with statistical algorithm-based fault tolerance,'' in 2025 62nd ACM\/IEEE Design Automation Conference (DAC)","author":"Xie T.","year":"2025","unstructured":"T. Xie, J. Zhao, Z. Wan, Z. Zhang, Y. Wang, R. Wang, R. Huang, and M. Li, ''Realm: Reliable and efficient large language model inference with statistical algorithm-based fault tolerance,'' in 2025 62nd ACM\/IEEE Design Automation Conference (DAC), pp. 1-7, 2025."},{"issue":"240","key":"e_1_3_2_1_63_1","first-page":"1","article-title":"Palm: Scaling language modeling with pathways","volume":"24","author":"Chowdhery A.","year":"2023","unstructured":"A. Chowdhery, S. Narang, J. Devlin, M. Bosma, G. Mishra, A. Roberts, P. Barham, H. W. Chung, C. Sutton, S. Gehrmann, et al., ''Palm: Scaling language modeling with pathways,'' Journal of Machine Learning Research, vol. 24, no. 240, pp. 1-113, 2023.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_64_1","volume-title":"Mt-opt: Continuous multi-task robotic reinforcement learning at scale,'' arXiv preprint arXiv:2104.08212","author":"Kalashnikov D.","year":"2021","unstructured":"D. Kalashnikov, J. Varley, Y. Chebotar, B. Swanson, R. Jonschkowski, C. Finn, S. Levine, and K. Hausman, ''Mt-opt: Continuous multi-task robotic reinforcement learning at scale,'' arXiv preprint arXiv:2104.08212, 2021."},{"key":"e_1_3_2_1_65_1","first-page":"10740","article-title":"Alfred: A benchmark for interpreting grounded instructions for everyday tasks","author":"Shridhar M.","year":"2020","unstructured":"M. Shridhar, J. Thomason, D. Gordon, Y. Bisk, W. Han, R. Mottaghi, L. Zettlemoyer, and D. Fox, ''Alfred: A benchmark for interpreting grounded instructions for everyday tasks,'' in Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp. 10740-10749, 2020.","journal-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition"},{"key":"e_1_3_2_1_66_1","article-title":"Interactive language: Talking to robots in real time","author":"Lynch C.","year":"2023","unstructured":"C. Lynch, A. Wahid, J. Tompson, T. Ding, J. Betker, R. Baruch, T. Armstrong, and P. Florence, ''Interactive language: Talking to robots in real time,'' IEEE Robotics and Automation Letters, 2023.","journal-title":"IEEE Robotics and Automation Letters"},{"key":"e_1_3_2_1_67_1","first-page":"1877","volume-title":"Language models are few-shot learners,'' Advances in neural information processing systems","author":"Brown T.","year":"2020","unstructured":"T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, et al., ''Language models are few-shot learners,'' Advances in neural information processing systems, vol. 33, pp. 1877-1901, 2020."},{"key":"e_1_3_2_1_68_1","volume-title":"PMLR","author":"Blukis V.","year":"2022","unstructured":"V. Blukis, C. Paxton, D. Fox, A. Garg, and Y. Artzi, ''A persistent spatial semantic representation for high-level natural language instruction execution,'' in Conference on Robot Learning, pp. 706-717, PMLR, 2022."},{"key":"e_1_3_2_1_69_1","volume-title":"Pali-x: On scaling up a multilingual vision and language model,'' arXiv preprint arXiv:2305.18565","author":"Chen X.","year":"2023","unstructured":"X. Chen, J. Djolonga, P. Padlewski, B. Mustafa, S. Changpinyo, J. Wu, C. R. Ruiz, S. Goodman, X. Wang, Y. Tay, et al., ''Pali-x: On scaling up a multilingual vision and language model,'' arXiv preprint arXiv:2305.18565, 2023."},{"key":"e_1_3_2_1_70_1","first-page":"2442","article-title":"Minerl: a large-scale dataset of minecraft demonstrations","author":"Guss W. H.","year":"2019","unstructured":"W. H. Guss, B. Houghton, N. Topin, P. Wang, C. Codel, M. Veloso, and R. Salakhutdinov, ''Minerl: a large-scale dataset of minecraft demonstrations,'' in Proceedings of the 28th International Joint Conference on Artificial Intelligence, pp. 2442-2448, 2019.","journal-title":"Proceedings of the 28th International Joint Conference on Artificial Intelligence"},{"key":"e_1_3_2_1_71_1","first-page":"34892","volume-title":"Visual instruction tuning,'' Advances in neural information processing systems","author":"Liu H.","year":"2023","unstructured":"H. Liu, C. Li, Q. Wu, and Y. J. Lee, ''Visual instruction tuning,'' Advances in neural information processing systems, vol. 36, pp. 34892-34916, 2023."},{"key":"e_1_3_2_1_72_1","first-page":"44776","article-title":"Libero: Benchmarking knowledge transfer for lifelong robot learning","volume":"36","author":"Liu B.","year":"2023","unstructured":"B. Liu, Y. Zhu, C. Gao, Y. Feng, Q. Liu, Y. Zhu, and P. Stone, ''Libero: Benchmarking knowledge transfer for lifelong robot learning,'' Advances in Neural Information Processing Systems, vol. 36, pp. 44776-44791, 2023.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_73_1","volume-title":"Openflamingo: An open-source framework for training large autoregressive vision-language models,'' arXiv preprint arXiv:2308.01390","author":"Awadalla A.","year":"2023","unstructured":"A. Awadalla, I. Gao, J. Gardner, J. Hessel, Y. Hanafy, W. Zhu, K. Marathe, Y. Bitton, S. Gadre, S. Sagawa, et al., ''Openflamingo: An open-source framework for training large autoregressive vision-language models,'' arXiv preprint arXiv:2308.01390, 2023."},{"key":"e_1_3_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3180108"},{"key":"e_1_3_2_1_75_1","volume-title":"Octo: An open-source generalist robot policy,'' in Robotics: Science and Systems","author":"Ghosh D.","year":"2024","unstructured":"D. Ghosh, H. R. Walke, K. Pertsch, K. Black, O. Mees, S. Dasari, J. Hejna, T. Kreiman, C. Xu, J. Luo, et al., ''Octo: An open-source generalist robot policy,'' in Robotics: Science and Systems, 2024."},{"key":"e_1_3_2_1_76_1","first-page":"6892","volume-title":"Open x-embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collaboration 0,'' in 2024 IEEE International Conference on Robotics and Automation (ICRA)","author":"O'Neill A.","year":"2024","unstructured":"A. O'Neill, A. Rehman, A. Maddukuri, A. Gupta, A. Padalkar, A. Lee, A. Pooley, A. Gupta, A. Mandlekar, A. Jain, et al., ''Open x-embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collaboration 0,'' in 2024 IEEE International Conference on Robotics and Automation (ICRA), pp. 6892-6903, IEEE, 2024."},{"key":"e_1_3_2_1_77_1","first-page":"20413","article-title":"An embodied generalist agent in 3d world","author":"Huang J.","year":"2024","unstructured":"J. Huang, S. Yong, X. Ma, X. Linghu, P. Li, Y. Wang, Q. Li, S.-C. Zhu, B. Jia, and S. Huang, ''An embodied generalist agent in 3d world,'' in Proceedings of the 41st International Conference on Machine Learning, pp. 20413-20451, 2024.","journal-title":"Proceedings of the 41st International Conference on Machine Learning"},{"key":"e_1_3_2_1_78_1","volume-title":"Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality,'' See https:\/\/vicuna. lmsys.org (accessed","author":"Chiang W.-L.","year":"2023","unstructured":"W.-L. Chiang, Z. Li, Z. Lin, Y. Sheng, Z. Wu, H. Zhang, L. Zheng, S. Zhuang, Y. Zhuang, J. E. Gonzalez, et al., ''Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality,'' See https:\/\/vicuna. lmsys.org (accessed 14 April 2023), vol. 2, no. 3, p. 6, 2023."},{"key":"e_1_3_2_1_79_1","first-page":"202","volume-title":"Scanrefer: 3d object localization in rgb-d scans using natural language,'' in European conference on computer vision","author":"Chen D. Z.","year":"2020","unstructured":"D. Z. Chen, A. X. Chang, and M. Nie\u00dfner, ''Scanrefer: 3d object localization in rgb-d scans using natural language,'' in European conference on computer vision, pp. 202-221, Springer, 2020."},{"key":"e_1_3_2_1_80_1","volume-title":"Habitat-matterport 3d dataset (HM3d): 1000 large-scale 3d environments for embodied AI,'' in Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track","author":"Ramakrishnan S. K.","year":"2021","unstructured":"S. K. Ramakrishnan, A. Gokaslan, E. Wijmans, O. Maksymets, A. Clegg, J. M. Turner, E. Undersander, W. Galuba, A. Westbury, A. X. Chang, M. Savva, Y. Zhao, and D. Batra, ''Habitat-matterport 3d dataset (HM3d): 1000 large-scale 3d environments for embodied AI,'' in Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track, 2021."},{"key":"e_1_3_2_1_81_1","first-page":"69900","article-title":"Steve-1: A generative model for text-to-behavior in minecraft","volume":"36","author":"Lifshitz S.","year":"2023","unstructured":"S. Lifshitz, K. Paster, H. Chan, J. Ba, and S. McIlraith, ''Steve-1: A generative model for text-to-behavior in minecraft,'' Advances in Neural Information Processing Systems, vol. 36, pp. 69900-69929, 2023.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_82_1","volume-title":"PMLR","author":"Xiao G.","year":"2023","unstructured":"G. Xiao, J. Lin, M. Seznec, H. Wu, J. Demouth, and S. Han, ''Smoothquant: Accurate and efficient post-training quantization for large language models,'' in International Conference on Machine Learning, pp. 38087-38099, PMLR, 2023."},{"key":"e_1_3_2_1_83_1","volume-title":"Awq: Activation-aware weight quantization for llm compression and acceleration,'' arXiv preprint arXiv:2306.00978","author":"Lin J.","year":"2023","unstructured":"J. Lin, J. Tang, H. Tang, S. Yang, X. Dang, and S. Han, ''Awq: Activation-aware weight quantization for llm compression and acceleration,'' arXiv preprint arXiv:2306.00978, 2023."},{"key":"e_1_3_2_1_84_1","volume-title":"Rptq: Reorder-based post-training quantization for large language models,'' arXiv preprint arXiv:2304.01089","author":"Yuan Z.","year":"2023","unstructured":"Z. Yuan, L. Niu, J. Liu, W. Liu, X. Wang, Y. Shang, G. Sun, Q. Wu, J. Wu, and B. Wu, ''Rptq: Reorder-based post-training quantization for large language models,'' arXiv preprint arXiv:2304.01089, 2023."},{"key":"e_1_3_2_1_85_1","volume-title":"Spinquant: Llm quantization with learned rotations,'' arXiv preprint arXiv:2405.16406","author":"Liu Z.","year":"2024","unstructured":"Z. Liu, C. Zhao, I. Fedorov, B. Soran, D. Choudhary, R. Krishnamoorthi, V. Chandra, Y. Tian, and T. Blankevoort, ''Spinquant: Llm quantization with learned rotations,'' arXiv preprint arXiv:2405.16406, 2024."},{"key":"e_1_3_2_1_86_1","first-page":"100213","article-title":"Quarot: Outlier-free 4-bit inference in rotated llms","volume":"37","author":"Ashkboos S.","year":"2024","unstructured":"S. Ashkboos, A. Mohtashami, M. Croci, B. Li, P. Cameron, M. Jaggi, D. Alistarh, T. Hoefler, and J. Hensman, ''Quarot: Outlier-free 4-bit inference in rotated llms,'' Advances in Neural Information Processing Systems, vol. 37, pp. 100213-100240, 2024.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_87_1","volume-title":"PMLR","author":"Tseng A.","year":"2024","unstructured":"A. Tseng, J. Chee, Q. Sun, V. Kuleshov, and C. De Sa, ''Quip $# $: Even better llm quantization with hadamard incoherence and lattice codebooks,'' in International Conference on Machine Learning, pp. 48630-48656, PMLR, 2024."},{"key":"e_1_3_2_1_88_1","doi-asserted-by":"publisher","DOI":"10.1109\/JETCAS.2025.3558300"},{"key":"e_1_3_2_1_89_1","first-page":"1","volume-title":"Read: Reliability-enhanced accelerator dataflow optimization using critical input pattern reduction,'' in 2023 IEEE\/ACM International Conference on Computer Aided Design (ICCAD)","author":"Zhang Z.","year":"2023","unstructured":"Z. Zhang, R. Wei, M. Li, Y. Lin, R. Wang, and R. Huang, ''Read: Reliability-enhanced accelerator dataflow optimization using critical input pattern reduction,'' in 2023 IEEE\/ACM International Conference on Computer Aided Design (ICCAD), pp. 1-9, IEEE, 2023."},{"key":"e_1_3_2_1_90_1","first-page":"1","article-title":"Deep neural network reliability improvement scheme in 3d die-stacked memory based on fault analysis","author":"Kim J.-S.","year":"2019","unstructured":"J.-S. Kim and J.-S. Yang, ''Dris-3: Deep neural network reliability improvement scheme in 3d die-stacked memory based on fault analysis,'' in Proceedings of the 56th Annual Design Automation Conference 2019, pp. 1-6, 2019.","journal-title":"Proceedings of the 56th Annual Design Automation Conference"},{"key":"e_1_3_2_1_91_1","first-page":"112","volume-title":"Minimizing total area of low-voltage sram arrays through joint optimization of cell size, redundancy, and ecc,'' in 2010 IEEE International Conference on Computer Design","author":"Zhou S.-T.","year":"2010","unstructured":"S.-T. Zhou, S. Katariya, H. Ghasemi, S. Draper, and N. S. Kim, ''Minimizing total area of low-voltage sram arrays through joint optimization of cell size, redundancy, and ecc,'' in 2010 IEEE International Conference on Computer Design, pp. 112-117, IEEE, 2010."},{"key":"e_1_3_2_1_92_1","first-page":"194","volume-title":"Single-event effects on ultra-low power cmos circuits,'' in 2009 IEEE International Reliability Physics Symposium","author":"Casey M. C.","year":"2009","unstructured":"M. C. Casey, B. L. Bhuva, S. A. Nation, O. A. Amusan, T. D. Loveless, L. W. Massengill, D. McMorrow, and J. S. Melinger, ''Single-event effects on ultra-low power cmos circuits,'' in 2009 IEEE International Reliability Physics Symposium, pp. 194-198, IEEE, 2009."},{"key":"e_1_3_2_1_93_1","first-page":"830","volume-title":"Edgebert: Sentence-level energy optimizations for latency-aware multi-task nlp inference,'' in MICRO-54:  54th Annual IEEE\/ACM International Symposium on Microarchitecture","author":"Tambe T.","year":"2021","unstructured":"T. Tambe, C. Hooper, L. Pentecost, T. Jia, E.-Y. Yang, M. Donato, V. Sanh, P. Whatmough, A. M. Rush, D. Brooks, et al., ''Edgebert: Sentence-level energy optimizations for latency-aware multi-task nlp inference,'' in MICRO-54: 54th Annual IEEE\/ACM International Symposium on Microarchitecture, pp. 830-844, 2021."},{"key":"e_1_3_2_1_94_1","first-page":"97","volume-title":"One bit is (not) enough: An empirical study of the impact of single and multiple bit-flip errors,'' in 2017 47th Annual IEEE\/IFIP International Conference on Dependable Systems and Networks (DSN)","author":"Sangchoolie B.","year":"2017","unstructured":"B. Sangchoolie, K. Pattabiraman, and J. Karlsson, ''One bit is (not) enough: An empirical study of the impact of single and multiple bit-flip errors,'' in 2017 47th Annual IEEE\/IFIP International Conference on Dependable Systems and Networks (DSN), pp. 97-108, IEEE, 2017."},{"key":"e_1_3_2_1_95_1","first-page":"270","volume-title":"Fidelity: Efficient resilience analysis framework for deep learning accelerators,'' in 2020 53rd Annual IEEE\/ACM International Symposium on Microarchitecture (MICRO)","author":"He Y.","year":"2020","unstructured":"Y. He, P. Balaprakash, and Y. Li, ''Fidelity: Efficient resilience analysis framework for deep learning accelerators,'' in 2020 53rd Annual IEEE\/ACM International Symposium on Microarchitecture (MICRO), pp. 270-281, IEEE, 2020."},{"key":"e_1_3_2_1_96_1","article-title":"Silent data corruption in robot operating system: A case for end-to-end system-level fault analysis using autonomous uavs","author":"Hsiao Y. S.","year":"2023","unstructured":"Y. S. Hsiao, Z. Wan, T. Jia, R. Ghosal, A. Mahmoud, A. Raychowdhury, V. J. Reddi, et al., ''Silent data corruption in robot operating system: A case for end-to-end system-level fault analysis using autonomous uavs,'' IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2023.","journal-title":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems"},{"key":"e_1_3_2_1_97_1","first-page":"902","volume-title":"Demystifying the system vulnerability stack: Transient fault effects across the layers,'' in 2021 ACM\/IEEE 48th Annual International Symposium on Computer Architecture (ISCA)","author":"Papadimitriou G.","year":"2021","unstructured":"G. Papadimitriou and D. Gizopoulos, ''Demystifying the system vulnerability stack: Transient fault effects across the layers,'' in 2021 ACM\/IEEE 48th Annual International Symposium on Computer Architecture (ISCA), pp. 902-915, IEEE, 2021."},{"key":"e_1_3_2_1_98_1","doi-asserted-by":"publisher","DOI":"10.1002\/j.1538-7305.1950.tb00463.x"},{"key":"e_1_3_2_1_99_1","doi-asserted-by":"publisher","DOI":"10.1145\/3458336.3465297"},{"key":"e_1_3_2_1_100_1","first-page":"1184","article-title":"Hadamard matrices and their applications","author":"Hedayat A.","year":"1978","unstructured":"A. Hedayat and W. D. Wallis, ''Hadamard matrices and their applications,'' The annals of statistics, pp. 1184-1238, 1978.","journal-title":"The annals of statistics"},{"key":"e_1_3_2_1_101_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0377-0427(00)00393-9"},{"key":"e_1_3_2_1_102_1","volume-title":"Information theory","author":"Ash R. B.","year":"2012","unstructured":"R. B. Ash, Information theory. Courier Corporation, 2012."},{"key":"e_1_3_2_1_103_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2021.3069954"},{"key":"e_1_3_2_1_104_1","first-page":"1","volume-title":"Hbm (high bandwidth memory) dram technology and architecture,'' in 2017 IEEE International Memory Workshop (IMW)","author":"Jun H.","year":"2017","unstructured":"H. Jun, J. Cho, K. Lee, H.-Y. Son, K. Kim, H. Jin, and K. Kim, ''Hbm (high bandwidth memory) dram technology and architecture,'' in 2017 IEEE International Memory Workshop (IMW), pp. 1-4, IEEE, 2017."},{"key":"e_1_3_2_1_105_1","volume-title":"Scale-sim: Systolic cnn accelerator simulator,'' arXiv preprint arXiv:1811.02883","author":"Samajdar A.","year":"2018","unstructured":"A. Samajdar, Y. Zhu, P. Whatmough, M. Mattina, and T. Krishna, ''Scale-sim: Systolic cnn accelerator simulator,'' arXiv preprint arXiv:1811.02883, 2018."},{"key":"e_1_3_2_1_106_1","volume-title":"Decoupled weight decay regularization","author":"Loshchilov I.","year":"2019","unstructured":"I. Loshchilov and F. Hutter, ''Decoupled weight decay regularization,'' 2019."}],"event":{"name":"ASPLOS '26: 31st ACM International Conference on Architectural Support for Programming Languages and Operating Systems","location":"Pittsburgh PA USA","sponsor":["SIGOPS ACM Special Interest Group on Operating Systems","SIGPLAN ACM Special Interest Group on Programming Languages","SIGARCH ACM Special Interest Group on Computer Architecture","SIGBED ACM Special Interest Group on Embedded Systems"]},"container-title":["Proceedings of the 31st ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2"],"original-title":[],"deposited":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T13:57:19Z","timestamp":1773583039000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3779212.3790147"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,22]]},"references-count":106,"alternative-id":["10.1145\/3779212.3790147","10.1145\/3779212"],"URL":"https:\/\/doi.org\/10.1145\/3779212.3790147","relation":{},"subject":[],"published":{"date-parts":[[2026,3,22]]},"assertion":[{"value":"2026-03-22","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}