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CLaMP 3 is a unified framework developed to address challenges of cross-modal and cross-lingual generalization in music information retrieval.
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Improved deep metric learning with multi-class n-pair loss objective
Kihyuk Sohn. 2016 · 2016
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Audio set: An ontology and human-labeled dataset for audio events
Jort F. Gemmeke, Daniel P. W. Ellis, Dylan Freedman, Aren Jansen, Wade Lawrence, R. Channing Moore, Manoj Plakal, and Marvin Ritter. 2017 · 2017
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Accurate, large minibatch SGD: training imagenet in 1 hour
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Bag of tricks for efficient text classification
Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomás Mikolov. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Mixed precision training
Paulius Micikevicius, Sharan Narang, Jonah Alben, Gregory F. Diamos, Erich Elsen, David García, Boris Ginsburg, Michael Houston, Oleksii Kuchaiev, Ganesh Venkatesh, and Hao Wu. 2018 · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 2018 · 2018
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The mtg-jamendo dataset for automatic music tagging
Dmitry Bogdanov, Minz Won, Philip Tovstogan, Alastair Porter, and Xavier Serra. 2019 · 2019
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Learning to generate music with sentiment
Lucas Ferreira and Jim Whitehead. 2019 · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
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Unsupervised cross-lingual representation learning at scale
Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. 2020 · 2020
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Retrieval-augmented generation for knowledge-intensive NLP tasks
Patrick S. H. Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela. 2020 · 2020
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Midibert-piano: large-scale pre-training for symbolic music understanding
Yi-Hui Chou, I Chen, Chin-Jui Chang, Joann Ching, Yi-Hsuan Yang, et al. 2021 · 2021
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Musicbert: Symbolic music understanding with large-scale pre-training
Mingliang Zeng, Xu Tan, Rui Wang, Zeqian Ju, Tao Qin, and Tie-Yan Liu. 2021 · 2021
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Mulan: A joint embedding of music audio and natural language
Qingqing Huang, Aren Jansen, Joonseok Lee, Ravi Ganti, Judith Yue Li, and Daniel P. W. Ellis. 2022 · 2022
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Musiclm: Generating music from text
Andrea Agostinelli, Timo I Denk, Zalán Borsos, Jesse Engel, Mauro Verzetti, Antoine Caillon, Qingqing Huang, Aren Jansen, Adam Roberts, Marco Tagliasacchi, et al. 2023 · 2023
Large-scale contrastive language-audio pretraining with feature fusion and keyword-to-caption augmentation
Yusong Wu, Ke Chen, Tianyu Zhang, Yuchen Hui, Taylor Berg-Kirkpatrick, and Shlomo Dubnov. 2023b · 2023
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MARBLE: music audio representation benchmark for universal evaluation
Ruibin Yuan, Yinghao Ma, Yizhi Li, Ge Zhang, Xingran Chen, Hanzhi Yin, Le Zhuo, Yiqi Liu, Jiawen Huang, Zeyue Tian, Binyue Deng, Ningzhi Wang, Chenghua Lin, Emmanouil Benetos, Anton Ragni, Norbert Gyenge, Roger B. Dannenberg, Wenhu Chen, Gus Xia, Wei Xue, Si Liu, Shi Wang, Ruibo Liu, Yike Guo, and Jie Fu. 2023 · 2023
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Jisheng Bai, Haohe Liu, Mou Wang, Dongyuan Shi, Wenwu Wang, Mark D Plumbley, Woon-Seng Gan, and Jianfeng Chen. 2024 · 2024
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Musicldm: Enhancing novelty in text-to-music generation using beat-synchronous mixup strategies
Ke Chen, Yusong Wu, Haohe Liu, Marianna Nezhurina, Taylor Berg-Kirkpatrick, and Shlomo Dubnov. 2024 · 2024
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Seamlessm4t-massively multilingual & multimodal machine translation
Loïc Barrault, Yu-An Chung, Mariano Cora Meglioli, David Dale, Ning Dong, Paul-Ambroise Duquenne, Hady Elsahar, Hongyu Gong, Kevin Heffernan, John Hoffman, et al. 2023 · 2023
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Simple and controllable music generation
Jade Copet, Felix Kreuk, Itai Gat, Tal Remez, David Kant, Gabriel Synnaeve, Yossi Adi, and Alexandre Défossez. 2023 · 2023
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Lp-musiccaps: Llm-based pseudo music captioning
Seungheon Doh, Keunwoo Choi, Jongpil Lee, and Juhan Nam. 2023a · 2023
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Toward universal text-to-music retrieval
Seungheon Doh, Minz Won, Keunwoo Choi, and Juhan Nam. 2023b · 2023
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Imagebind one embedding space to bind them all
Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu, Mannat Singh, Kalyan Vasudev Alwala, Armand Joulin, and Ishan Misra. 2023 · 2023
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The song describer dataset: a corpus of audio captions for music-and-language evaluation
Ilaria Manco, Benno Weck, Seungheon Doh, Minz Won, Yixiao Zhang, Dmitry Bogdanov, Yusong Wu, Ke Chen, Philip Tovstogan, Emmanouil Benetos, et al. 2023 · 2023
Cited alongside, same era.
Clamp: Contrastive language-music pre-training for cross-modal symbolic music information retrieval
Shangda Wu, Dingyao Yu, Xu Tan, and Maosong Sun. 2023a · 2023
Cited alongside, same era.
Enriching music descriptions with A finetuned-llm and metadata for text-to-music retrieval
Seungheon Doh, Minhee Lee, Dasaem Jeong, and Juhan Nam. 2024 · 2024
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Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al. 2024 · 2024
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MERT: acoustic music understanding model with large-scale self-supervised training
Yizhi Li, Ruibin Yuan, Ge Zhang, Yinghao Ma, Xingran Chen, Hanzhi Yin, Chenghao Xiao, Chenghua Lin, Anton Ragni, Emmanouil Benetos, Norbert Gyenge, Roger B. Dannenberg, Ruibo Liu, Wenhu Chen, Gus Xia, Yemin Shi, Wenhao Huang, Zili Wang, Yike Guo, and Jie Fu. 2024 · 2024
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Midicaps–a large-scale midi dataset with text captions
Jan Melechovsky, Abhinaba Roy, and Dorien Herremans. 2024 · 2024
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Frechet music distance: A metric for generative symbolic music evaluation
Jan Retkowski, Jakub Stępniak, and Mateusz Modrzejewski. 2024 · 2024
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Clamp 2: Multimodal music information retrieval across 101 languages using large language models
Shangda Wu, Yashan Wang, Ruibin Yuan, Zhancheng Guo, Xu Tan, Ge Zhang, Monan Zhou, Jing Chen, Xuefeng Mu, Yuejie Gao, et al. 2024 · 2024
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An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, et al. 2024 · 2024
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Muq: Self-supervised music representation learning with mel residual vector quantization
Haina Zhu, Yizhi Zhou, Hangting Chen, Jianwei Yu, Ziyang Ma, Rongzhi Gu, Wei Tan, and Xie Chen. 2025 · 2025
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