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Despite the impressive capabilities of large language models (LLMs) across diverse applications, they still suffer from trustworthiness issues, such as hallucinations and misalignments.
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This email could save your life: Introducing the task of email subject line generation
Zhang, R. and Tetreault, J · 2019
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Language models are few-shot learners, 2020
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Dense passage retrieval for open-domain question answering
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Retrieval-augmented generation for knowledge-intensive nlp tasks
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Nan, L., Radev, D., Zhang, R., Rau, A., Sivaprasad, A., Hsieh, C., Tang, X., Vyas, A., Verma, N., Krishna, P., et al · 2020
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Approximate nearest neighbor negative contrastive learning for dense text retrieval
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Learn then test: Calibrating predictive algorithms to achieve risk control
Angelopoulos, A. N., Bates, S., Candès, E. J., Jordan, M. I., and Lei, L · 2021
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Learning to retrieve prompts for in-context learning
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Conformal time-series forecasting
Stankeviciute, K., M Alaa, A., and van der Schaar, M · 2021
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Finetuned language models are zero-shot learners
Wei, J., Bosma, M., Zhao, V. Y., Guu, K., Yu, A. W., Lester, B., Du, N., Dai, A. M., and Le, Q. V · 2021
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Han, C., Wang, Z., Zhao, H., and Ji, H · 2023
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Kang, M., Lin, Z., Sun, J., Xiao, C., and Li, B · 2023
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Compressing context to enhance inference efficiency of large language models
Li, Y., Dong, B., Lin, C., and Guerin, F · 2023
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Trustworthy llms: a survey and guideline for evaluating large language models’ alignment, 2023
Liu, Y., Yao, Y., Ton, J.-F., Zhang, X., Guo, R., Cheng, H., Klochkov, Y., Taufiq, M. F., and Li, H · 2023
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Luo, Z., Xu, C., Zhao, P., Geng, X., Tao, C., Ma, J., Lin, Q., and Jiang, D · 2023
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Quach, V., Fisch, A., Schuster, T., Yala, A., Sohn, J. H., Jaakkola, T. S., and Barzilay, R · 2023
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Llama: Open and efficient foundation language models
Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.-A., Lacroix, T., Rozière, B., Goyal, N., Hambro, E., Azhar, F., et al · 2023
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Transformers learn in-context by gradient descent
Von Oswald, J., Niklasson, E., Randazzo, E., Sacramento, J., Mordvintsev, A., Zhmoginov, A., and Vladymyrov, M · 2023
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Hummer: Towards limited competitive preference dataset
Jiang, L., Wu, Y., Xiong, J., Ruan, J., Ding, Y., Guo, Q., Wen, Z., Zhou, J., and Deng, X · 2024
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Mm-llms: Recent advances in multimodal large language models
Zhang, D., Yu, Y., Li, C., Dong, J., Su, D., Chu, C., and Yu, D · 2024
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