{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T07:06:24Z","timestamp":1775199984946,"version":"3.50.1"},"reference-count":26,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T00:00:00Z","timestamp":1764979200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T00:00:00Z","timestamp":1764979200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,12,6]]},"DOI":"10.1109\/asru65441.2025.11434708","type":"proceedings-article","created":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T19:48:04Z","timestamp":1775159284000},"page":"1-6","source":"Crossref","is-referenced-by-count":0,"title":["KAN-AST: Kolmogorov-Arnold Network based Audio Spectrogram Transformer for Audio Classification"],"prefix":"10.1109","author":[{"given":"Phuong Tuan","family":"Dat","sequence":"first","affiliation":[{"name":"Institute for Infocomm Research (I2R) Agency for Science, Technology and Research (A*STAR),Singapore"}]},{"given":"Tran Huy","family":"Dat","sequence":"additional","affiliation":[{"name":"Institute for Infocomm Research (I2R) Agency for Science, Technology and Research (A*STAR),Singapore"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3318015"},{"issue":"5","key":"ref2","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/0893-6080(89)90020-8","article-title":"Multilayer feedforward networks are universal approximators","volume":"2","author":"Hornik","year":"1989","journal-title":"Neural Networks"},{"issue":"6","key":"ref3","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1037\/h0042519","article-title":"The perceptron: a probabilistic model for information storage and organization in the brain","volume":"65","author":"Rosenblatt","year":"1958","journal-title":"Psychological review"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1038\/323533a0","article-title":"Learning representations by back-propagating errors","volume":"323","author":"Rumelhart","year":"1986","journal-title":"Nature"},{"key":"ref5","article-title":"A survey on universal approximation theorems","author":"Augustine","year":"2024"},{"key":"ref6","article-title":"KAN: Kolmogorov-arnold networks","volume-title":"The Thirteenth International Conference on Learning Representations","author":"Liu"},{"key":"ref7","first-page":"369","article-title":"On the representation of continuous functions of several variables by superposition of continuous functions of one variable and addition","volume":"114","author":"Kolmogorov","year":"1957","journal-title":"Doklady Akademii Nauk SSSR"},{"key":"ref8","article-title":"Hyperkan: Kolmogorov-arnold networks make hyperspectral image classificators smarter","author":"Lobanov","year":"2024"},{"key":"ref9","article-title":"Deep state space recurrent neural networks for time series forecasting","author":"Inzirillo","year":"2024"},{"key":"ref10","article-title":"Kolmogorov-arnold networks are radial basis function networks","author":"Li","year":"2024"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2021-698"},{"key":"ref12","article-title":"An image is worth 16 x16 words: Transformers for image recognition at scale","author":"Dosovitskiy","year":"2021"},{"issue":"18-24","key":"ref13","first-page":"10347","article-title":"Training data-efficient image transformers amp; distillation through attention","volume-title":"Proceedings of the 38th International Conference on Machine Learning, ser. Proceedings of Machine Learning Research","volume":"139","author":"Touvron"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2017.7952261"},{"key":"ref15","article-title":"Acoustic scene classification in dcase 2020 challenge: generalization across devices and low complexity solutions","author":"Heittola","year":"2020"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2019-2680"},{"key":"ref17","article-title":"Adam: A method for stochastic optimization","volume":"abs\/1412.6980","author":"Kingma","year":"2014","journal-title":"CoRR"},{"key":"ref18","article-title":"Speech commands: A dataset for limited-vocabulary speech recognition","author":"Warden","year":"2018"},{"key":"ref19","article-title":"Learning from between-class examples for deep sound recognition","author":"Tokozume","year":"2018"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s10579-008-9076-6"},{"key":"ref21","article-title":"Ssast: Selfsupervised audio spectrogram transformer","author":"Gong","year":"2022"},{"key":"ref22","doi-asserted-by":"crossref","DOI":"10.1109\/TASLP.2020.3030497","article-title":"Panns: Large-scale pretrained audio neural networks for audio pattern recognition","author":"Kong","year":"2020"},{"key":"ref23","doi-asserted-by":"crossref","DOI":"10.21437\/Interspeech.2021-698","article-title":"Ast: Audio spectrogram transformer","author":"Gong","year":"2021"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"3292","DOI":"10.1109\/TASLP.2021.3120633","article-title":"Psla: Improving audio tagging with pretraining, sampling, labeling, and aggregation","volume":"29","author":"Gong","year":"2021","journal-title":"IEEE\/ACM Transactions on Audio, Speech, and Language Processing"},{"key":"ref25","article-title":"Eat: Self-supervised pre-training with efficient audio transformer","author":"Chen","year":"2024"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2015.7178964"}],"event":{"name":"2025 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","location":"Honolulu, HI, USA","start":{"date-parts":[[2025,12,6]]},"end":{"date-parts":[[2025,12,10]]}},"container-title":["2025 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11434577\/11433836\/11434708.pdf?arnumber=11434708","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T04:58:38Z","timestamp":1775192318000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11434708\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,6]]},"references-count":26,"URL":"https:\/\/doi.org\/10.1109\/asru65441.2025.11434708","relation":{},"subject":[],"published":{"date-parts":[[2025,12,6]]}}}