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The widespread adoption of large language models (LLMs) has raised concerns regarding data privacy.
ROUGE: A package for automatic evaluation of summaries
Lin, C.-Y · 2004
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Distributed representations of sentences and documents, 2014
Le, Q. V. and Mikolov, T · 2014
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Skip-thought vectors, 2015
Kiros, R., Zhu, Y., Salakhutdinov, R., Zemel, R. S., Torralba, A., Urtasun, R., and Fidler, S · 2015
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Pointer sentinel mixture models, 2016
Merity, S., Xiong, C., Bradbury, J., and Socher, R · 2016
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Squad: 100,000+ questions for machine comprehension of text, 2016
Rajpurkar, P., Zhang, J., Lopyrev, K., and Liang, P · 2016
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Privacy-preserving deep learning: Revisited and enhanced
Phong, L. T., Aono, Y., Hayashi, T., Wang, L., and Moriai, S · 2017
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Membership inference attacks against machine learning models, 2017
Shokri, R., Stronati, M., Song, C., and Shmatikov, V · 2017
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Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., and Polosukhin, I · 2017
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Deep leakage from gradients, 2019b
Zhu, L., Liu, Z., and Han, S · 2017
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Language models are unsupervised multitask learners
Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., and Sutskever, I · 2019
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Sentence-bert: Sentence embeddings using siamese bert-networks, 2019
Reimers, N. and Gurevych, I · 2019
Cited alongside, same era.
Privacy risks of general-purpose language models
Pan, X., Zhang, M., Ji, S., and Yang, M · 2020
Cited alongside, same era.
Information leakage in embedding models, 2020
Song, C. and Raghunathan, A · 2020
Cited alongside, same era.
Visbert: Hidden-state visualizations for transformers, 2020
van Aken, B., Winter, B., Löser, A., and Gers, F. A · 2020
Cited alongside, same era.
idlg: Improved deep leakage from gradients, 2020
Zhao, B., Mopuri, K. R., and Bilen, H · 2020
Cited alongside, same era.
Transformer feed-forward layers are key-value memories, 2021
Geva, M., Schuster, R., Berant, J., and Levy, O · 2021
Cited alongside, same era.
Slora: Federated parameter efficient fine-tuning of language models, 2023
Babakniya, S., Elkordy, A. R., Ezzeldin, Y. H., Liu, Q., Song, K.-B., El-Khamy, M., and Avestimehr, S · 2023
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Federated large language model: A position paper, 2023
Chen, C., Feng, X., Zhou, J., Yin, J., and Zheng, X · 2023
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Decepticons: Corrupted transformers breach privacy in federated learning for language models
Fowl, L. H., Geiping, J., Reich, S., Wen, Y., Czaja, W., Goldblum, M., and Goldstein, T · 2023
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Towards sentence level inference attack against pre-trained language models
Gu, K., Kabir, E., Ramsurrun, N., Vosoughi, S., and Mehnaz, S · 2023
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Sentence embedding leaks more information than you expect: Generative embedding inversion attack to recover the whole sentence
Li, H., Xu, M., and Song, Y · 2023
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LAMP: Extracting text from gradients with language model priors
Balunovic, M., Dimitrov, D. I., Jovanović, N., and Vechev, M · 2022
Cited alongside, same era.
Improving language models by retrieving from trillions of tokens, 2022
Borgeaud, S., Mensch, A., Hoffmann, J., Cai, T., Rutherford, E., Millican, K., van den Driessche, G., Lespiau, J.-B., Damoc, B., Clark, A., de Las Casas, D., Guy, A., Menick, J., Ring, R., Hennigan, T., Huang, S., Maggiore, L., Jones, C., Cassirer, A., Brock, A., Paganini, M., Irving, G., Vinyals, O., Osindero, S., Simonyan, K., Rae, J. W., Elsen, E., and Sifre, L · 2022
Cited alongside, same era.
Glm: General language model pretraining with autoregressive blank infilling
Du, Z., Qian, Y., Liu, X., Ding, M., Qiu, J., Yang, Z., and Tang, J · 2022
Cited alongside, same era.
Privacy-preserving face recognition in the frequency domain
Wang, Y., Liu, J., Luo, M., Yang, L., and Wang, L · 2022
Cited alongside, same era.
Text embeddings reveal (almost) as much as text, 2023a
Morris, J. X., Kuleshov, V., Shmatikov, V., and Rush, A. M
Cited in the paper.
Language model inversion, 2023b
Morris, J. X., Zhao, W., Chiu, J. T., Shmatikov, V., and Rush, A. M
Cited in the paper.
Privacy-preserving face recognition using random frequency components
Mi, Y., Huang, Y., Ji, J.-B., Zhao, M., Wu, J., Xu, X., Ding, S., and Zhou, S · 2023
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A comprehensive overview of large language models, 2023
Naveed, H., Khan, A. U., Qiu, S., Saqib, M., Anwar, S., Usman, M., Akhtar, N., Barnes, N., and Mian, A · 2023
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Llama 2: Open foundation and fine-tuned chat models, 2023
Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bashlykov, N., Batra, S., Bhargava, P., Bhosale, S., Bikel, D., Blecher, L., Ferrer, C. C., Chen, M., Cucurull, G., Esiobu, D., Fernandes, J., Fu, J., Fu, W., Fuller, B., Gao, C., Goswami, V., Goyal, N., Hartshorn, A., Hosseini, S., Hou, R., Inan, H., Kardas, M., Kerkez, V., Khabsa, M., Kloumann, I., Korenev, A., Koura, P. S., Lachaux, M.-A., Lavril, T., Lee, J., Liskovich, D., Lu, Y., Mao, Y., Martinet, X., Mihaylov, T., Mishra, P., Molybog, I., Nie, Y., Poulton, A., Reizenstein, J., Rungta, R., Saladi, K., Schelten, A., Silva, R., Smith, E. M., Subramanian, R., Tan, X. E., Tang, B., Taylor, R., Williams, A., Kuan, J. X., Xu, P., Yan, Z., Zarov, I., Zhang, Y., Fan, A., Kambadur, M., Narang, S., Rodriguez, A., Stojnic, R., Edunov, S., and Scialom, T · 2023
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Fingpt: Open-source financial large language models, 2023
Yang, H., Liu, X.-Y., and Wang, C. D · 2023
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React: Synergizing reasoning and acting in language models, 2023
Yao, S., Zhao, J., Yu, D., Du, N., Shafran, I., Narasimhan, K., and Cao, Y · 2023
Later among the works it cites.