{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T11:56:40Z","timestamp":1773230200462,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":47,"publisher":"ACM","funder":[{"name":"NSF &#x28;National Science Foundation&#x29;","award":["NSF-PHY-2117997"],"award-info":[{"award-number":["NSF-PHY-2117997"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,2,22]]},"DOI":"10.1145\/3748173.3779202","type":"proceedings-article","created":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T21:17:35Z","timestamp":1770326255000},"page":"44-55","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["KANEL\u00c9: Kolmogorov\u2013Arnold Networks for Efficient LUT-based Evaluation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8250-870X","authenticated-orcid":false,"given":"Duc","family":"Hoang","sequence":"first","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, MA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0177-4855","authenticated-orcid":false,"given":"Aarush","family":"Gupta","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, Massachusetts, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8189-3741","authenticated-orcid":false,"given":"Philip C","family":"Harris","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, Massachusetts, USA"}]}],"member":"320","published-online":{"date-parts":[[2026,2,21]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","unstructured":"2020. Dry Bean. UCI Machine Learning Repository. DOI: https:\/\/doi.org\/10.24432\/C50S4B.","DOI":"10.24432\/C50S4B"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","unstructured":"Stefan Aeberhard and M. Forina. 1992. Wine. UCI Machine Learning Repository. DOI: https:\/\/doi.org\/10.24432\/C5PC7J.","DOI":"10.24432\/C5PC7J"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1108\/eb007637"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/icfpt59805.2023.00012"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/fpl64840.2024.00028"},{"key":"e_1_3_2_1_6_1","volume-title":"Constantinides","author":"Andronic Marta","year":"2025","unstructured":"Marta Andronic and George A. Constantinides. 2025. NeuraLUT-Assemble: Hardware-aware Assembling of Sub-Neural Networks for Efficient LUT Inference. arXiv:2504.00592 [cs.LG] https:\/\/arxiv.org\/abs\/2504.00592"},{"key":"e_1_3_2_1_7_1","volume-title":"Eugene John, Lizy K. John, Priscila M. V. Lima, and Felipe M. G. Fran\u00e7a.","author":"Bacellar Alan T. L.","year":"2025","unstructured":"Alan T. L. Bacellar, Zachary Susskind, Mauricio Breternitz Jr., Eugene John, Lizy K. John, Priscila M. V. Lima, and Felipe M. G. Fran\u00e7a. 2025. DifferentiableWeightless Neural Networks. arXiv:2410.11112 [cs.LG] https:\/\/arxiv.org\/abs\/2410.11112"},{"key":"e_1_3_2_1_8_1","volume-title":"Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks","author":"Banbury Colby","year":"2021","unstructured":"Colby Banbury, Vijay Janapa Reddi, Peter Torelli, Jeremy Holleman, Nat Jeffries, Csaba Kiraly, Pietro Montino, David Kanter, Sebastian Ahmed, Danilo Pau, et al. 2021. MLPerf Tiny Benchmark. Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks (2021)."},{"key":"e_1_3_2_1_9_1","volume-title":"Jack Natan Spolski, and Santiago Pourteau.","author":"Bodner Alexander Dylan","year":"2025","unstructured":"Alexander Dylan Bodner, Antonio Santiago Tepsich, Jack Natan Spolski, and Santiago Pourteau. 2025. Convolutional Kolmogorov-Arnold Networks. arXiv:2406.13155 [cs.CV] https:\/\/arxiv.org\/abs\/2406.13155"},{"key":"e_1_3_2_1_10_1","unstructured":"Hendrik Borras Giuseppe Di Guglielmo Javier Duarte Nicol\u00f2 Ghielmetti Ben Hawks Scott Hauck Shih-Chieh Hsu Ryan Kastner Jason Liang Andres Meza Jules Muhizi Tai Nguyen Rushil Roy Nhan Tran Yaman Umuroglu OliviaWeng Aidan Yokuda and Michaela Blott. 2022. Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark. arXiv:2206.11791 [cs.LG] https:\/\/arxiv.org\/abs\/2206.11791"},{"key":"e_1_3_2_1_11_1","volume-title":"CERNBox LHC Jets Dataset. https:\/\/cernbox.cern. ch\/index.php\/s\/jvFd5MoWhGs1l5v\/download [Accessed","author":"Collaboration CERN","year":"2025","unstructured":"CERN Collaboration. 2025. CERNBox LHC Jets Dataset. https:\/\/cernbox.cern. ch\/index.php\/s\/jvFd5MoWhGs1l5v\/download [Accessed: Sept 1, 2025]."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/LCSYS.2025.3578019"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2211477"},{"key":"e_1_3_2_1_14_1","unstructured":"Ivan Drokin. 2024. Kolmogorov-Arnold Convolutions: Design Principles and Empirical Studies. arXiv:2407.01092 [cs.CV] https:\/\/arxiv.org\/abs\/2407.01092"},{"key":"e_1_3_2_1_15_1","unstructured":"Farah Fahim Benjamin Hawks Christian Herwig James Hirschauer Sergo Jindariani Nhan Tran Luca P. Carloni Giuseppe Di Guglielmo Philip Harris Jeffrey Krupa Dylan Rankin Manuel Blanco Valentin Josiah Hester Yingyi Luo John Mamish Seda Orgrenci-Memik Thea Aarrestad Hamza Javed Vladimir Loncar Maurizio Pierini Adrian Alan Pol Sioni Summers Javier Duarte Scott Hauck Shih-Chieh Hsu Jennifer Ngadiuba Mia Liu Duc Hoang Edward Kreinar and Zhenbin Wu. 2021. hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices. arXiv:2103.05579 [cs.LG] https:\/\/arxiv.org\/abs\/2103.05579"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","unstructured":"Giuseppe Franco Alessandro Pappalardo and Nicholas J Fraser. 2025. Xilinx\/brevitas. doi:10.5281\/zenodo.3333552","DOI":"10.5281\/zenodo.3333552"},{"key":"e_1_3_2_1_17_1","volume-title":"TKAN: Temporal Kolmogorov-Arnold Networks. arXiv:2405.07344 [cs.LG] https:\/\/arxiv.org\/abs\/2405.07344","author":"Genet Remi","year":"2025","unstructured":"Remi Genet and Hugo Inzirillo. 2025. TKAN: Temporal Kolmogorov-Arnold Networks. arXiv:2405.07344 [cs.LG] https:\/\/arxiv.org\/abs\/2405.07344"},{"key":"e_1_3_2_1_18_1","unstructured":"Xiao Han Xinfeng Zhang Yiling Wu Zhenduo Zhang and Zhe Wu. 2025. Are KANs Effective for Multivariate Time Series Forecasting? arXiv:2408.11306 [cs.LG] https:\/\/arxiv.org\/abs\/2408.11306"},{"key":"e_1_3_2_1_19_1","unstructured":"Yuntian Hou Tianrui Ji Di Zhang and Angelos Stefanidis. 2025. Kolmogorov-Arnold Networks: A Critical Assessment of Claims Performance and Practical Viability. arXiv:2407.11075 [cs.LG] https:\/\/arxiv.org\/abs\/2407.11075"},{"key":"e_1_3_2_1_20_1","unstructured":"Abdullah Al Imran and Md Farhan Ishmam. 2024. FourierKAN outperforms MLP on Text Classification Head Fine-tuning. arXiv:2408.08803 [cs.CL] https:\/\/arxiv.org\/abs\/2408.08803"},{"key":"e_1_3_2_1_21_1","unstructured":"Tianrui Ji Yuntian Hou and Di Zhang. 2025. A Comprehensive Survey on Kolmogorov Arnold Networks (KAN). arXiv:2407.11075 [cs.LG] https:\/\/arxiv.org\/abs\/2407.11075"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3706628.3708877"},{"key":"e_1_3_2_1_23_1","volume-title":"Raul Steinmetz, Ricardo Bedin Grando, Ayano Yorozu, and Akihisa Ohya.","author":"Kich Victor Augusto","year":"2024","unstructured":"Victor Augusto Kich, Jair Augusto Bottega, Raul Steinmetz, Ricardo Bedin Grando, Ayano Yorozu, and Akihisa Ohya. 2024. Kolmogorov-Arnold Network for Online Reinforcement Learning. arXiv:2408.04841 [cs.LG] https:\/\/arxiv.org\/abs\/2408.04841"},{"key":"e_1_3_2_1_24_1","volume-title":"U-KAN Makes Strong Backbone for Medical Image Segmentation and Generation. arXiv preprint arXiv:2406.02918","author":"Li Chenxin","year":"2024","unstructured":"Chenxin Li, Xinyu Liu, Wuyang Li, Cheng Wang, Hengyu Liu, and Yixuan Yuan. 2024. U-KAN Makes Strong Backbone for Medical Image Segmentation and Generation. arXiv preprint arXiv:2406.02918 (2024)."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-025-01087-7"},{"key":"e_1_3_2_1_26_1","unstructured":"Ziming Liu Pingchuan Ma Yixuan Wang Wojciech Matusik and Max Tegmark. 2024. KAN 2.0: Kolmogorov-Arnold Networks Meet Science. arXiv:2408.10205 [cs.LG] https:\/\/arxiv.org\/abs\/2408.10205"},{"key":"e_1_3_2_1_27_1","volume-title":"KAN: Kolmogorov-Arnold Networks. arXiv:2404.19756 [cs.LG] https:\/\/arxiv.org\/abs\/2404.19756","author":"Liu Ziming","year":"2025","unstructured":"Ziming Liu, YixuanWang, Sachin Vaidya, Fabian Ruehle, James Halverson, Marin Solja?i?, Thomas Y. Hou, and Max Tegmark. 2025. KAN: Kolmogorov-Arnold Networks. arXiv:2404.19756 [cs.LG] https:\/\/arxiv.org\/abs\/2404.19756"},{"key":"e_1_3_2_1_28_1","unstructured":"Ilya Loshchilov and Frank Hutter. 2019. DecoupledWeight Decay Regularization. arXiv:1711.05101 [cs.LG] https:\/\/arxiv.org\/abs\/1711.05101"},{"key":"e_1_3_2_1_29_1","volume-title":"Leong","author":"Lou Binglei","year":"2024","unstructured":"Binglei Lou, Richard Rademacher, David Boland, and Philip H. W. Leong. 2024. PolyLUT-Add: FPGA-based LUT Inference with Wide Inputs. arXiv:2406.04910 [cs.LG] https:\/\/arxiv.org\/abs\/2406.04910"},{"key":"e_1_3_2_1_30_1","volume-title":"Accessed","year":"2025","unstructured":"Marmiton. n.d.. Cannel\u00e9s bordelais. https:\/\/www.marmiton.org\/recettes\/recette_ canneles-bordelais_11439.aspx. Accessed: Sept 23, 2025."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASAP54787.2022.00014"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1088\/2632-2153\/aba042"},{"key":"e_1_3_2_1_33_1","volume-title":"hls4ml lhc jets hlf (OpenML Dataset 42468). https:\/\/www.openml.org\/d\/42468 [Accessed","author":"Contributors ML","year":"2025","unstructured":"OpenML Contributors and LHC Jets HLF Curators. 2020. hls4ml lhc jets hlf (OpenML Dataset 42468). https:\/\/www.openml.org\/d\/42468 [Accessed: Sept 1, 2025]."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.5555\/1953048.2078195"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3743128"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3559009.3569680"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","unstructured":"Zachary Susskind Alan Bacellar Aman Arora Luis Villon Renan Mendanha Leandro Santiago Diego Dutra Priscila Lima Felipe Fran\u00e7a Igor Miranda Mauricio Breternitz and LIZY JOHN. 2022. Pruning Weightless Neural Networks. 37-42. doi:10.14428\/esann\/2022.ES2022-55","DOI":"10.14428\/esann\/2022.ES2022-55"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2012.6386109"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/CANDARW64572.2024.00026"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"crossref","unstructured":"Yaman Umuroglu Yash Akhauri Nicholas J. Fraser and Michaela Blott. 2020. LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput Applications. arXiv:2004.03021 [eess.SP] https:\/\/arxiv.org\/abs\/2004.03021","DOI":"10.1109\/FPL50879.2020.00055"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3020078.3021744"},{"key":"e_1_3_2_1_42_1","volume-title":"Constantinides","author":"Wang Erwei","year":"2019","unstructured":"Erwei Wang, James J. Davis, Peter Y. K. Cheung, and George A. Constantinides. 2019. LUTNet: Rethinking Inference in FPGA Soft Logic. arXiv:1904.00938 [cs.LG] https:\/\/arxiv.org\/abs\/1904.00938"},{"key":"e_1_3_2_1_43_1","volume-title":"Hou","author":"Wang Yixuan","year":"2025","unstructured":"Yixuan Wang, Jonathan W. Siegel, Ziming Liu, and Thomas Y. Hou. 2025. On the expressiveness and spectral bias of KANs. arXiv:2410.01803 [cs.LG] https:\/\/arxiv.org\/abs\/2410.01803"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2024.117518"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3706628.3708874"},{"key":"e_1_3_2_1_46_1","unstructured":"Runpeng Yu Weihao Yu and Xinchao Wang. 2024. KAN or MLP: A Fairer Comparison. arXiv:2407.16674 [cs.LG] https:\/\/arxiv.org\/abs\/2407.16674"},{"key":"e_1_3_2_1_47_1","unstructured":"Jusheng Zhang Yijia Fan Kaitong Cai and KezeWang. 2025. Kolmogorov-Arnold Fourier Networks. arXiv:2502.06018 [cs.LG] https:\/\/arxiv.org\/abs\/2502.06018"}],"event":{"name":"FPGA '26:The 2026 ACM\/SIGDA International Symposium on Field Programmable Gate Arrays","location":"Seaside CA USA","sponsor":["SIGDA ACM Special Interest Group on Design Automation"]},"container-title":["Proceedings of the 2026 ACM\/SIGDA International Symposium on Field Programmable Gate Arrays"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3748173.3779202","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T14:56:10Z","timestamp":1773154570000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3748173.3779202"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,21]]},"references-count":47,"alternative-id":["10.1145\/3748173.3779202","10.1145\/3748173"],"URL":"https:\/\/doi.org\/10.1145\/3748173.3779202","relation":{},"subject":[],"published":{"date-parts":[[2026,2,21]]},"assertion":[{"value":"2026-02-21","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}