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Open-sourced Large Language Models (LLMs) have achieved great success in various NLP tasks, however, they are still far inferior to API-based models when acting as agents.
Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Yang, Z., Qi, P., Zhang, S., Bengio, Y., Cohen, W., Salakhutdinov, R., and Manning, C. D · 2018
Earlier work this paper cites.
Alfworld: Aligning text and embodied environments for interactive learning
Shridhar, M., Yuan, X., Côté, M.-A., Bisk, Y., Trischler, A., and Hausknecht, M · 2020
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 · 2021
Earlier work this paper cites.
Generated knowledge prompting for commonsense reasoning
Liu, J., Liu, A., Lu, X., Welleck, S., West, P., Bras, R. L., Choi, Y., and Hajishirzi, H · 2021
Earlier work this paper cites.
Multitask prompted training enables zero-shot task generalization
Sanh, V., Webson, A., Raffel, C., Bach, S. H., Sutawika, L., Alyafeai, Z., Chaffin, A., Stiegler, A., Scao, T. L., Raja, A., et al · 2021
Earlier work this paper cites.
Scaling instruction-finetuned language models
Chung, H. W., Hou, L., Longpre, S., Zoph, B., Tay, Y., Fedus, W., Li, Y., Wang, X., Dehghani, M., Brahma, S., et al · 2022
Earlier work this paper cites.
Unnatural instructions: Tuning language models with (almost) no human labor
Honovich, O., Scialom, T., Levy, O., and Schick, T · 2022
Earlier work this paper cites.
Hint: Hypernetwork instruction tuning for efficient zero-shot generalisation
Ivison, H., Bhagia, A., Wang, Y., Hajishirzi, H., and Peters, M · 2022
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Openai: Introducing chatgpt, 2022
OpenAI · 2022
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Scienceworld: Is your agent smarter than a 5th grader?
Wang, R., Jansen, P., Côté, M.-A., and Ammanabrolu, P · 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
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Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality, March 2023
Chiang, W.-L., Li, Z., Lin, Z., Sheng, Y., Wu, Z., Zhang, H., Zheng, L., Zhuang, S., Zhuang, Y., Gonzalez, J. E., Stoica, I., and Xing, E. P · 2023
Earlier work this paper cites.
Mind2web: Towards a generalist agent for the web
Deng, X., Gu, Y., Zheng, B., Chen, S., Stevens, S., Wang, B., Sun, H., and Su, Y · 2023
Earlier work this paper cites.
Qlora: Efficient finetuning of quantized llms
Dettmers, T., Pagnoni, A., Holtzman, A., and Zettlemoyer, L · 2023
Earlier work this paper cites.
Specializing smaller language models towards multi-step reasoning
Fu, Y., Peng, H., Ou, L., Sabharwal, A., and Khot, T · 2023
Earlier work this paper cites.
glaive-function-calling-v2, 2023
GlaiveAI · 2023
Cited alongside, same era.
ToRA: A tool-integrated reasoning agent for mathematical problem solving
Gou, Z., Shao, Z., Gong, Y., Yang, Y., Huang, M., Duan, N., Chen, W., et al · 2023
Cited alongside, same era.
Gunasekar, S., Zhang, Y., Aneja, J., Mendes, C. C. T., Del Giorno, A., Gopi, S., Javaheripi, M., Kauffmann, P., de Rosa, G., Saarikivi, O., et al · 2023
Cited alongside, same era.
MetaGPT: Meta programming for multi-agent collaborative framework
Hong, S., Zheng, X., Chen, J., Cheng, Y., Wang, J., Zhang, C., Wang, Z., Yau, S. K. S., Lin, Z., Zhou, L., et al · 2023
Cited alongside, same era.
Inner monologue: Embodied reasoning through planning with language models
Huang, W., Xia, F., Xiao, T., Chan, H., Liang, J., Florence, P., Zeng, A., Tompson, J., Mordatch, I., Chebotar, Y., et al · 2023
Gorilla: Large language model connected with massive apis
Patil, S. G., Zhang, T., Wang, X., and Gonzalez, J. E · 2023
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Making language models better tool learners with execution feedback
Qiao, S., Gui, H., Chen, H., and Zhang, N · 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
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Reflexion: Language agents with verbal reinforcement learning
Shinn, N., Cassano, F., Gopinath, A., Narasimhan, K. R., and Yao, S · 2023
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Llm-planner: Few-shot grounded planning for embodied agents with large language models
Song, C. H., Wu, J., Washington, C., Sadler, B. M., Chao, W.-L., and Su, Y · 2023
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Cited alongside, same era.
Survey of hallucination in natural language generation
Ji, Z., Lee, N., Frieske, R., Yu, T., Su, D., Xu, Y., Ishii, E., Bang, Y. J., Madotto, A., and Fung, P · 2023
Cited alongside, same era.
Language models can solve computer tasks, 2023
Kim, G., Baldi, P., and McAleer, S · 2023
Cited alongside, same era.
Multi-step jailbreaking privacy attacks on chatgpt
Li, H., Guo, D., Fan, W., Xu, M., and Song, Y · 2023
Cited alongside, same era.
Encouraging divergent thinking in large language models through multi-agent debate, 2023
Liang, T., He, Z., Jiao, W., Wang, X., Wang, Y., Wang, R., Yang, Y., Tu, Z., and Shi, S · 2023
Cited alongside, same era.
The flan collection: Designing data and methods for effective instruction tuning
Longpre, S., Hou, L., Vu, T., Webson, A., Chung, H. W., Tay, Y., Zhou, D., Le, Q. V., Zoph, B., Wei, J., et al · 2023
Cited alongside, same era.
Full parameter fine-tuning for large language models with limited resources
Lv, K., Yang, Y., Liu, T., Gao, Q., Guo, Q., and Qiu, X · 2023
Cited alongside, same era.
Mao, S., Zhang, N., Wang, X., Wang, M., Yao, Y., Jiang, Y., Xie, P., Huang, F., and Chen, H · 2023
Cited alongside, same era.
Later among the works it cites.
Cognitive architectures for language agents
Sumers, T. R., Yao, S., Narasimhan, K., and Griffiths, T. L · 2023
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Multi-agent collaboration: Harnessing the power of intelligent llm agents
Talebirad, Y. and Nadiri, A · 2023
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Llama 2: Open foundation and fine-tuned chat models
Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bashlykov, N., Batra, S., Bhargava, P., Bhosale, S., et al · 2023
Later among the works it cites.
AutoGen: Enabling next-gen llm applications via multi-agent conversation framework
Wu, Q., Bansal, G., Zhang, J., Wu, Y., Zhang, S., Zhu, E., Li, B., Jiang, L., Zhang, X., and Wang, C · 2023
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The rise and potential of large language model based agents: A survey
Xi, Z., Chen, W., Guo, X., He, W., Ding, Y., Hong, B., Zhang, M., Wang, J., Jin, S., Zhou, E., et al · 2023
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Rewoo: Decoupling reasoning from observations for efficient augmented language models
Xu, B., Peng, Z., Lei, B., Mukherjee, S., Liu, Y., and Xu, D · 2023
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GPT-4 is too smart to be safe: Stealthy chat with llms via cipher
Yuan, Y., Jiao, W., Wang, W., Huang, J.-t., He, P., Shi, S., and Tu, Z · 2023
Later among the works it cites.
AgentTuning: Enabling generalized agent abilities for llms
Zeng, A., Liu, M., Lu, R., Wang, B., Liu, X., Dong, Y., and Tang, J · 2023
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Webarena: A realistic web environment for building autonomous agents
Zhou, S., Xu, F. F., Zhu, H., Zhou, X., Lo, R., Sridhar, A., Cheng, X., Bisk, Y., Fried, D., Alon, U., et al · 2023
Later among the works it cites.
Jiang, A. Q., Sablayrolles, A., Roux, A., Mensch, A., Savary, B., Bamford, C., Chaplot, D. S., Casas, D. d. l., Hanna, E. B., Bressand, F., et al · 2024
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