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The rise of large language models (LLMs) has revolutionized the way that we interact with artificial intelligence systems through natural language.
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Diverse expected gradient active learning for relative attributes
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Active learning for speech recognition: the power of gradients
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Simple and scalable predictive uncertainty estimation using deep ensembles
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Active discriminative text representation learning
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Cost-effective active learning for hierarchical multi-label classification
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Hotpotqa: A dataset for diverse, explainable multi-hop question answering
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Asking clarifying questions in open-domain information-seeking conversations
Aliannejadi, M., Zamani, H., Crestani, F., and Croft, W. B. (2019) · 2019
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Practical, efficient, and customizable active learning for named entity recognition in the digital humanities
Erdmann, A., Wrisley, D. J., Brown, C., Cohen-Bodénès, S., Elsner, M., Feng, Y., Joseph, B., Joyeux-Prunel, B., and de Marneffe, M.-C. (2019) · 2019
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Language models are few-shot learners
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020) · 2020
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IIRC: A dataset of incomplete information reading comprehension questions
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Constructing A multi-hop QA dataset for comprehensive evaluation of reasoning steps
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Retrieval-augmented generation for knowledge-intensive NLP tasks
Lewis, P. S. H., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Küttler, H., Lewis, M., Yih, W., Rocktäschel, T., Riedel, S., and Kiela, D. (2020) · 2020
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Chain-of-thought prompting elicits reasoning in large language models
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Ask me anything: A simple strategy for prompting language models
Arora, S., Narayan, A., Chen, M. F., Orr, L. J., Guha, N., Bhatia, K., Chami, I., and Ré, C. (2023) · 2023
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Huang, L., Yu, W., Ma, W., Zhong, W., Feng, Z., Wang, H., Chen, Q., Peng, W., Feng, X., Qin, B., et al. (2023) · 2023
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Atlas: Few-shot learning with retrieval augmented language models
Izacard, G., Lewis, P. S. H., Lomeli, M., Hosseini, L., Petroni, F., Schick, T., Dwivedi-Yu, J., Joulin, A., Riedel, S., and Grave, E. (2023) · 2023
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Active retrieval augmented generation
Jiang, Z., Xu, F. F., Gao, L., Sun, Z., Liu, Q., Dwivedi-Yu, J., Yang, Y., Callan, J., and Neubig, G. (2023) · 2023
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Generating clarifying questions for information retrieval
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The pile: An 800gb dataset of diverse text for language modeling
Gao, L., Biderman, S., Black, S., Golding, L., Hoppe, T., Foster, C., Phang, J., He, H., Thite, A., Nabeshima, N., Presser, S., and Leahy, C. (2021) · 2021
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Did aristotle use a laptop? A question answering benchmark withimplicit reasoning strategies
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Zhang, M. and Plank, B. (2021) · 2021
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Qmsum: A new benchmark for query-based multi-domain meeting summarization
Zhong, M., Yin, D., Yu, T., Zaidi, A., Mutuma, M., Jha, R., Awadallah, A. H., Celikyilmaz, A., Liu, Y., Qiu, X., and Radev, D. R. (2021) · 2021
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Scaling instruction-finetuned language models
Chung, H. W., Hou, L., Longpre, S., Zoph, B., Tay, Y., Fedus, W., Li, E., Wang, X., Dehghani, M., Brahma, S., et al. (2022) · 2022
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Guiding large language models via directional stimulus prompting
Li, Z., Peng, B., He, P., Galley, M., Gao, J., and Yan, X. (2023) · 2023
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G-eval: NLG evaluation using gpt-4 with better human alignment
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Active learning principles for in-context learning with large language models
Margatina, K., Schick, T., Aletras, N., and Dwivedi-Yu, J. (2023) · 2023
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Augmented language models: a survey
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OpenAI (2023) · 2023
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Natural language instruction-following with task-related language development and translation
Pang, J.-C., Yang, X., Yang, S.-H., Chen, X.-H., and Yu, Y. (2023) · 2023
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Measuring and narrowing the compositionality gap in language models
Press, O., Zhang, M., Min, S., Schmidt, L., Smith, N. A., and Lewis, M. (2023) · 2023
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Enhancing retrieval-augmented large language models with iterative retrieval-generation synergy
Shao, Z., Gong, Y., Shen, Y., Huang, M., Duan, N., and Chen, W. (2023) · 2023
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Llama 2: Open foundation and fine-tuned chat models
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Language model self-improvement by reinforcement learning contemplation
Pang, J., Wang, P., Li, K., Chen, X., Xu, J., Zhang, Z., and Yu, Y. (2024) · 2024
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