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Open vocabulary models (e.g.
Zero-data learning of new tasks
Larochelle, H., Erhan, D., and Bengio, Y · 2008
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ImageNet: A Large-Scale Hierarchical Image Database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L · 2009
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Learning multiple layers of features from tiny images
Krizhevsky, A · 2009
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Adapting visual category models to new domains
Saenko, K., Kulis, B., Fritz, M., and Darrell, T · 2010
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A survey of hierarchical classification across different application domains
Silla, C. N. and Freitas, A. A · 2010
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Sun database: Large-scale scene recognition from abbey to zoo
Xiao, J., Hays, J., Ehinger, K. A., Oliva, A., and Torralba, A · 2010
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Hierarchical annotation of medical images
Dimitrovski, I., Kocev, D., Loskovska, S., and Džeroski, S · 2011
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Food-101 – mining discriminative components with random forests
Bossard, L., Guillaumin, M., and Van Gool, L · 2014
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Costa: Co-occurrence statistics for zero-shot classification
Mensink, T., Gavves, E., and Snoek, C. G · 2014
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Learning from massive noisy labeled data for image classification
Xiao, T., Xia, T., Yang, Y., Huang, C., and Wang, X · 2015
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Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop, 2015
Yu, F., Seff, A., Zhang, Y., Song, S., Funkhouser, T., and Xiao, J · 2015
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Remote sensing image scene classification: Benchmark and state of the art
Cheng, G., Han, J., and Lu, X · 2017
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Deep hashing network for unsupervised domain adaptation
Venkateswara, H., Eusebio, J., Chakraborty, S., and Panchanathan, S · 2017
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Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms, 2017
Xiao, H., Rasul, K., and Vollgraf, R · 2017
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Introducing eurosat: A novel dataset and deep learning benchmark for land use and land cover classification
Helber, P., Bischke, B., Dengel, A., and Borth, D · 2018
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Fruit recognition from images using deep learning
Mureşan, H. and Oltean, M · 2018
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Objectnet: A large-scale bias-controlled dataset for pushing the limits of object recognition models
Barbu, A., Mayo, D., Alverio, J., Luo, W., Wang, C., Gutfreund, D., Tenenbaum, J., and Katz, B · 2019
Earlier work this paper cites.
Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification
Helber, P., Bischke, B., Dengel, A., and Borth, D · 2019
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Parameter-efficient transfer learning for nlp
Houlsby, N., Giurgiu, A., Jastrzebski, S., Morrone, B., De Laroussilhe, Q., Gesmundo, A., Attariyan, M., and Gelly, S · 2019
Cited alongside, same era.
Zero-shot handwritten chinese character recognition with hierarchical decomposition embedding
Cao, Z., Lu, J., Cui, S., and Zhang, C · 2020
Cited alongside, same era.
An empirical study on large-scale multi-label text classification including few and zero-shot labels
Chalkidis, I., Fergadiotis, M., Kotitsas, S., Malakasiotis, P., Aletras, N., and Androutsopoulos, I · 2020
Cited alongside, same era.
Making pre-trained language models better few-shot learners
Gao, T., Fisch, A., and Chen, D · 2020
Fine-grained image captioning with clip reward
Cho, J., Yoon, S., Kale, A., Dernoncourt, F., Bui, T., and Bansal, M · 2022
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Don’t stop learning: Towards continual learning for the clip model, 2022
Ding, Y., Liu, L., Tian, C., Yang, J., and Ding, H · 2022
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Clip on wheels: Zero-shot object navigation as object localization and exploration
Gadre, S. Y., Wortsman, M., Ilharco, G., Schmidt, L., and Song, S · 2022
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Unsupervised prompt learning for vision-language models, 2022
Huang, T., Chu, J., and Wei, F · 2022
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Patching open-vocabulary models by interpolating weights
Ilharco, G., Wortsman, M., Gadre, S. Y., Song, S., Hajishirzi, H., Kornblith, S., Farhadi, A., and Schmidt, L · 2022
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Cited alongside, same era.
Large-scale zero-shot image classification from rich and diverse textual descriptions
Bujwid, S. and Sullivan, J · 2021
Cited alongside, same era.
Hsva: Hierarchical semantic-visual adaptation for zero-shot learning
Chen, S., Xie, G., Liu, Y., Peng, Q., Sun, B., Li, H., You, X., and Shao, L · 2021
Cited alongside, same era.
Clip-adapter: Better vision-language models with feature adapters
Gao, P., Geng, S., Zhang, R., Ma, T., Fang, R., Zhang, Y., Li, H., and Qiao, Y · 2021
Cited alongside, same era.
Scaling up visual and vision-language representation learning with noisy text supervision
Jia, C., Yang, Y., Xia, Y., Chen, Y.-T., Parekh, Z., Pham, H., Le, Q., Sung, Y.-H., Li, Z., and Duerig, T · 2021
Cited alongside, same era.
Liu, H., Zhang, D., Yin, B., and Zhu, X · 2021
Cited alongside, same era.
Revisiting the calibration of modern neural networks
Minderer, M., Djolonga, J., Romijnders, R., Hubis, F., Zhai, X., Houlsby, N., Tran, D., and Lucic, M · 2021
Cited alongside, same era.
Combined scaling for open-vocabulary image classification
Pham, H., Dai, Z., Ghiasi, G., Kawaguchi, K., Liu, H., Yu, A. W., Yu, J., Chen, Y.-T., Luong, M.-T., Wu, Y., et al · 2021
Cited alongside, same era.
Jia, M., Tang, L., Chen, B.-C., Cardie, C., Belongie, S., Hariharan, B., and Lim, S.-N · 2022
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Language models (mostly) know what they know, 2022
Kadavath, S., Conerly, T., Askell, A., Henighan, T., Drain, D., Perez, E., Schiefer, N., Dodds, Z. H., DasSarma, N., Tran-Johnson, E., Johnston, S., El-Showk, S., Jones, A., Elhage, N., Hume, T., Chen, A., Bai, Y., Bowman, S., Fort, S., Ganguli, D., Hernandez, D., Jacobson, J., Kernion, J., Kravec, S., Lovitt, L., Ndousse, K., Olsson, C., Ringer, S., Amodei, D., Brown, T., Clark, J., Joseph, N., Mann, B., McCandlish, S., Olah, C., and Kaplan, J · 2022
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Toward zero-shot and zero-resource multilingual question answering
Kuo, C.-C. and Chen, K.-Y · 2022
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What does a platypus look like? generating customized prompts for zero-shot image classification, 2022
Pratt, S., Liu, R., and Farhadi, A · 2022
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Rethinking the openness of clip, 2022
Ren, S., Li, L., Ren, X., Zhao, G., and Sun, X · 2022
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Is a caption worth a thousand images? a controlled study for representation learning, 2022
Santurkar, S., Dubois, Y., Taori, R., Liang, P., and Hashimoto, T · 2022
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K-lite: Learning transferable visual models with external knowledge, 2022
Shen, S., Li, C., Hu, X., Xie, Y., Yang, J., Zhang, P., Rohrbach, A., Gan, Z., Wang, L., Yuan, L., Liu, C., Keutzer, K., Darrell, T., and Gao, J · 2022
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Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time
Wortsman, M., Ilharco, G., Gadre, S. Y., Roelofs, R., Gontijo-Lopes, R., Morcos, A. S., Namkoong, H., Farhadi, A., Carmon, Y., Kornblith, S., et al · 2022
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Exploring hierarchical graph representation for large-scale zero-shot image classification
Yi, K., Shen, X., Gou, Y., and Elhoseiny, M · 2022
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Multimodal knowledge alignment with reinforcement learning, 2022
Yu, Y., Chung, J., Yun, H., Hessel, J., Park, J., Lu, X., Ammanabrolu, P., Zellers, R., Bras, R. L., Kim, G., and Choi, Y · 2022
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Socratic models: Composing zero-shot multimodal reasoning with language
Zeng, A., Attarian, M., Ichter, B., Choromanski, K., Wong, A., Welker, S., Tombari, F., Purohit, A., Ryoo, M., Sindhwani, V., Lee, J., Vanhoucke, V., and Florence, P · 2022
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Lit: Zero-shot transfer with locked-image text tuning
Zhai, X., Wang, X., Mustafa, B., Steiner, A., Keysers, D., Kolesnikov, A., and Beyer, L · 2022
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