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The reasoning capabilities of the recent LLMs enable them to execute external function calls to overcome their inherent limitations, such as knowledge cutoffs, poor arithmetic skills, or lack of access to private data.
Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Yang, Z., Qi, P., Zhang, S., Bengio, Y., Cohen, W. W., Salakhutdinov, R., and Manning, C. D · 2018
Earlier work this paper cites.
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
Earlier work this paper cites.
Break it down: A question understanding benchmark
Wolfson, T., Geva, M., Gupta, A., Gardner, M., Goldberg, Y., Deutch, D., and Berant, J · 2020
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Program synthesis with large language models, 2021
Austin, J., Odena, A., Nye, M., Bosma, M., Michalewski, H., Dohan, D., Jiang, E., Cai, C., Terry, M., Le, Q., and Sutton, C · 2021
Earlier work this paper cites.
Evaluating large language models trained on code
Chen, M., Tworek, J., Jun, H., Yuan, Q., de Oliveira Pinto, H. P., Kaplan, J., Edwards, H., Burda, Y., Joseph, N., Brockman, G., Ray, A., Puri, R., Krueger, G., Petrov, M., Khlaaf, H., Sastry, G., Mishkin, P., Chan, B., Gray, S., Ryder, N., Pavlov, M., Power, A., Kaiser, L., Bavarian, M., Winter, C., Tillet, P., Such, F. P., Cummings, D., Plappert, M., Chantzis, F., Barnes, E., Herbert-Voss, A., Guss, W. H., Nichol, A., Paino, A., Tezak, N., Tang, J., Babuschkin, I., Balaji, S., Jain, S., Saunders, W., Hesse, C., Carr, A. N., Leike, J., Achiam, J., Misra, V., Morikawa, E., Radford, A., Knight, M., Brundage, M., Murati, M., Mayer, K., Welinder, P., McGrew, B., Amodei, D., McCandlish, S., Sutskever, I., and Zaremba, W · 2021
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The power of scale for parameter-efficient prompt tuning, 2021
Lester, B., Al-Rfou, R., and Constant, N · 2021
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GPTQ: Accurate post-training compression for generative pretrained transformers
Frantar, E., Ashkboos, S., Hoefler, T., and Alistarh, D · 2022
Earlier work this paper cites.
Pal: Program-aided language models
Gao, L., Madaan, A., Zhou, S., Alon, U., Liu, P., Yang, Y., Callan, J., and Neubig, G · 2022
Earlier work this paper cites.
LoRA: Low-rank adaptation of large language models
Hu, E. J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W · 2022
Earlier work this paper cites.
A fast post-training pruning framework for transformers, 2022
Kwon, W., Kim, S., Mahoney, M. W., Hassoun, J., Keutzer, K., and Gholami, A · 2022
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LlamaIndex, 11 2022
Liu, J · 2022
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Is a question decomposition unit all we need?
Patel, P., Mishra, S., Parmar, M., and Baral, C · 2022
Earlier work this paper cites.
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Wei, J., Wang, X., Schuurmans, D., Bosma, M., Xia, F., Chi, E., Le, Q. V., Zhou, D., et al · 2022
Earlier work this paper cites.
Language models as inductive reasoners, 2022
Yang, Z., Dong, L., Du, X., Cheng, H., Cambria, E., Liu, X., Gao, J., and Wei, F · 2022
Earlier work this paper cites.
React: Synergizing reasoning and acting in language models
Yao, S., Zhao, J., Yu, D., Du, N., Shafran, I., Narasimhan, K., and Cao, Y · 2022
Earlier work this paper cites.
Orca: A distributed serving system for { \{ Transformer-Based } \} generative models
Yu, G.-I., Jeong, J. S., Kim, G.-W., Kim, S., and Chun, B.-G · 2022
Earlier work this paper cites.
Graph of thoughts: Solving elaborate problems with large language models, 2023
Besta, M., Blach, N., Kubicek, A., Gerstenberger, R., Gianinazzi, L., Gajda, J., Lehmann, T., Podstawski, M., Niewiadomski, H., Nyczyk, P., and Hoefler, T · 2023
Cited alongside, same era.
Spqr: A sparse-quantized representation for near-lossless llm weight compression, 2023
Dettmers, T., Svirschevski, R., Egiazarian, V., Kuznedelev, D., Frantar, E., Ashkboos, S., Borzunov, A., Hoefler, T., and Alistarh, D · 2023
Cited alongside, same era.
Sparsegpt: Massive language models can be accurately pruned in one-shot, 2023
Frantar, E. and Alistarh, D · 2023
Cited alongside, same era.
Reasoning with language model is planning with world model, 2023
Hao, S., Gu, Y., Ma, H., Hong, J. J., Wang, Z., Wang, D. Z., and Hu, Z · 2023
Cited alongside, same era.
Intro to large language models, 2023
Karpathy, A · 2023
Cited alongside, same era.
Decomposed prompting: A modular approach for solving complex tasks
New models and developer products announced at devday, 2023
OpenAI · 2023
Closest in time.
Memgpt: Towards llms as operating systems, 2023
Packer, C., Fang, V., Patil, S. G., Lin, K., Wooders, S., and Gonzalez, J. E · 2023
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Gorilla: Large language model connected with massive apis, 2023
Patil, S. G., Zhang, T., Wang, X., and Gonzalez, J. E · 2023
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Measuring and narrowing the compositionality gap in language models, 2023
Press, O., Zhang, M., Min, S., Schmidt, L., Smith, N. A., and Lewis, M · 2023
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Toolllm: Facilitating large language models to master 16000+ real-world apis
Qin, Y., Liang, S., Ye, Y., Zhu, K., Yan, L., Lu, Y., Lin, Y., Cong, X., Tang, X., Qian, B., et al · 2023
Closest in time.
Toolformer: Language models can teach themselves to use tools
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Khot, T., Trivedi, H., Finlayson, M., Fu, Y., Richardson, K., Clark, P., and Sabharwal, A · 2023
Cited alongside, same era.
Squeezellm: Dense-and-sparse quantization, 2023
Kim, S., Hooper, C., Gholami, A., Dong, Z., Li, X., Shen, S., Mahoney, M. W., and Keutzer, K · 2023
Cited alongside, same era.
Large language models are zero-shot reasoners, 2023
Kojima, T., Gu, S. S., Reid, M., Matsuo, Y., and Iwasawa, Y · 2023
Cited alongside, same era.
Efficient memory management for large language model serving with pagedattention
Kwon, W., Li, Z., Zhuang, S., Sheng, Y., Zheng, L., Yu, C. H., Gonzalez, J. E., Zhang, H., and Stoica, I · 2023
Cited alongside, same era.
Fast inference from transformers via speculative decoding, 2023
Leviathan, Y., Kalman, M., and Matias, Y · 2023
Cited alongside, same era.
Taskmatrix.ai: Completing tasks by connecting foundation models with millions of apis, 2023
Liang, Y., Wu, C., Song, T., Wu, W., Xia, Y., Liu, Y., Ou, Y., Lu, S., Ji, L., Mao, S., Wang, Y., Shou, L., Gong, M., and Duan, N · 2023
Cited alongside, same era.
Awq: Activation-aware weight quantization for llm compression and acceleration, 2023
Lin, J., Tang, J., Tang, H., Yang, S., Dang, X., Gan, C., and Han, S · 2023
Cited alongside, same era.
Schick, T., Dwivedi-Yu, J., Dessì, R., Raileanu, R., Lomeli, M., Zettlemoyer, L., Cancedda, N., and Scialom, T · 2023
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Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face, 2023
Shen, Y., Song, K., Tan, X., Li, D., Lu, W., and Zhuang, Y · 2023
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Reflexion: Language agents with verbal reinforcement learning, 2023
Shinn, N., Cassano, F., Berman, E., Gopinath, A., Narasimhan, K., and Yao, S · 2023
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Restgpt: Connecting large language models with real-world restful apis, 2023
Song, Y., Xiong, W., Zhu, D., Wu, W., Qian, H., Song, M., Huang, H., Li, C., Wang, K., Yao, R., Tian, Y., and Li, S · 2023
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Cognitive architectures for language agents, 2023
Sumers, T. R., Yao, S., Narasimhan, K., and Griffiths, T. L · 2023
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Vipergpt: Visual inference via python execution for reasoning, 2023
Surís, D., Menon, S., and Vondrick, C · 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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Rewoo: Decoupling reasoning from observations for efficient augmented language models, 2023
Xu, B., Peng, Z., Lei, B., Mukherjee, S., Liu, Y., and Xu, D · 2023
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Ifqa: A dataset for open-domain question answering under counterfactual presuppositions, 2023
Yu, W., Jiang, M., Clark, P., and Sabharwal, A · 2023
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Take a step back: Evoking reasoning via abstraction in large language models, 2023
Zheng, H. S., Mishra, S., Chen, X., Cheng, H.-T., Chi, E. H., Le, Q. V., and Zhou, D · 2023
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Speculative decoding with big little decoder, 2024
Kim, S., Mangalam, K., Moon, S., Malik, J., Mahoney, M. W., Gholami, A., and Keutzer, K · 2024
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