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The rapid progress of foundation models has led to the prosperity of autonomous agents, which leverage the universal capabilities of foundation models to conduct reasoning, decision-making, and environmental interaction.
Artificial life meets entertainment: lifelike autonomous agents
Maes, P · 1995
Earlier work this paper cites.
Item-based collaborative filtering recommendation algorithms
Sarwar, B., Karypis, G., Konstan, J., and Riedl, J · 2001
Earlier work this paper cites.
The probabilistic relevance framework: Bm25 and beyond
Robertson, S., Zaragoza, H., et al · 2009
Earlier work this paper cites.
On evaluation of embodied navigation agents
Anderson, P., Chang, A., Chaplot, D. S., Dosovitskiy, A., Gupta, S., Koltun, V., Kosecka, J., Malik, J., Mottaghi, R., Savva, M., et al · 2018
Earlier work this paper cites.
Fast greedy map inference for determinantal point process to improve recommendation diversity
Chen, L., Zhang, G., and Zhou, E · 2018
Earlier work this paper cites.
Virtualhome: Simulating household activities via programs
Puig, X., Ra, K., Boben, M., Li, J., Wang, T., Fidler, S., and Torralba, A · 2018
Earlier work this paper cites.
Reinforcement learning: An introduction
Sutton, R. S. and Barto, A. G · 2018
Earlier work this paper cites.
Babyai: A platform to study the sample efficiency of grounded language learning, 2019
Chevalier-Boisvert, M., Bahdanau, D., Lahlou, S., Willems, L., Saharia, C., Nguyen, T. H., and Bengio, Y · 2019
Earlier work this paper cites.
Gibson env v2: Embodied simulation environments for interactive navigation
Xia, F., Li, C., Chen, K., Shen, W. B., Martın-Martın, R., Hirose, N., Zamir, A. R., Fei-Fei, L., and Savarese, S · 2019
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.
Interactive gibson benchmark: A benchmark for interactive navigation in cluttered environments
Xia, F., Shen, W. B., Li, C., Kasimbeg, P., Tchapmi, M. E., Toshev, A., Martín-Martín, R., and Savarese, S · 2020
Earlier work this paper cites.
Pyserini: A Python toolkit for reproducible information retrieval research with sparse and dense representations
Lin, J., Ma, X., Lin, S.-C., Yang, J.-H., Pradeep, R., and Nogueira, R · 2021
Earlier work this paper cites.
Agent: A benchmark for core psychological reasoning
Shu, T., Bhandwaldar, A., Gan, C., Smith, K., Liu, S., Gutfreund, D., Spelke, E., Tenenbaum, J., and Ullman, T · 2021
Earlier work this paper cites.
Habitat 2.0: Training home assistants to rearrange their habitat
Szot, A., Clegg, A., Undersander, E., Wijmans, E., Zhao, Y., Turner, J., Maestre, N., Mukadam, M., Chaplot, D. S., Maksymets, O., et al · 2021
Earlier work this paper cites.
Androidenv: A reinforcement learning platform for android
Toyama, D., Hamel, P., Gergely, A., Comanici, G., Glaese, A., Ahmed, Z., Jackson, T., Mourad, S., and Precup, D · 2021
Earlier work this paper cites.
Do as i can and not as i say: Grounding language in robotic affordances
Ahn, M., Brohan, A., Brown, N., Chebotar, Y., Cortes, O., David, B., Finn, C., Fu, C., Gopalakrishnan, K., Hausman, K., Herzog, A., Ho, D., Hsu, J., Ibarz, J., Ichter, B., Irpan, A., Jang, E., Ruano, R. J., Jeffrey, K., Jesmonth, S., Joshi, N., Julian, R., Kalashnikov, D., Kuang, Y., Lee, K.-H., Levine, S., Lu, Y., Luu, L., Parada, C., Pastor, P., Quiambao, J., Rao, K., Rettinghouse, J., Reyes, D., Sermanet, P., Sievers, N., Tan, C., Toshev, A., Vanhoucke, V., Xia, F., Xiao, T., Xu, P., Xu, S., Yan, M., and Zeng, A · 2022
Earlier work this paper cites.
Constitutional ai: Harmlessness from ai feedback
Bai, Y., Kadavath, S., Kundu, S., Askell, A., Kernion, J., Jones, A., Chen, A., Goldie, A., Mirhoseini, A., McKinnon, C., et al · 2022
Earlier work this paper cites.
Minedojo: Building open-ended embodied agents with internet-scale knowledge
Fan, L., Wang, G., Jiang, Y., Mandlekar, A., Yang, Y., Zhu, H., Tang, A., Huang, D.-A., Zhu, Y., and Anandkumar, A · 2022
Earlier work this paper cites.
Rfuniverse: A physics-based action-centric interactive environment for everyday household tasks
Fu, H., Xu, W., Xue, H., Yang, H., Ye, R., Huang, Y., Xue, Z., Wang, Y., and Lu, C · 2022
Earlier work this paper cites.
A path towards autonomous machine intelligence version 0.9. 2, 2022-06-27
LeCun, Y · 2022
Earlier work this paper cites.
Memory-assisted prompt editing to improve GPT-3 after deployment
Madaan, A., Tandon, N., Clark, P., and Yang, Y · 2022
Earlier work this paper cites.
Training language models to follow instructions with human feedback
Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., et al · 2022
Cited alongside, same era.
Avlen: Audio-visual-language embodied navigation in 3d environments
Paul, S., Roy-Chowdhury, A., and Cherian, A · 2022
Cited alongside, same era.
Task ambiguity in humans and language models
Tamkin, A., Handa, K., Shrestha, A., and Goodman, N · 2022
Cited alongside, same era.
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
Cited alongside, same era.
Least-to-most prompting enables complex reasoning in large language models
Zhou, D., Schärli, N., Hou, L., Wei, J., Scales, N., Wang, X., Schuurmans, D., Cui, C., Bousquet, O., Le, Q., et al · 2022
Cited alongside, same era.
Communicative agents for software development, 2023
Qian, C., Cong, X., Liu, W., Yang, C., Chen, W., Su, Y., Dang, Y., Li, J., Xu, J., Li, D., Liu, Z., and Sun, M · 2023
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Toolllm: Facilitating large language models to master 16000+ real-world apis, 2023
Qin, Y., Liang, S., Ye, Y., Zhu, K., Yan, L., Lu, Y., Lin, Y., Cong, X., Tang, X., Qian, B., Zhao, S., Tian, R., Xie, R., Zhou, J., Gerstein, M., Li, D., Liu, Z., and Sun, M · 2023
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Identifying the risks of lm agents with an lm-emulated sandbox
Ruan, Y., Dong, H., Wang, A., Pitis, S., Zhou, Y., Ba, J., Dubois, Y., Maddison, C. J., and Hashimoto, T · 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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Cognitive architectures for language agents
Sumers, T. R., Yao, S., Narasimhan, K., and Griffiths, T. L · 2023
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Weak-to-strong generalization: Eliciting strong capabilities with weak supervision
Burns, C., Izmailov, P., Kirchner, J. H., Baker, B., Gao, L., Aschenbrenner, L., Chen, Y., Ecoffet, A., Joglekar, M., Leike, J., et al · 2023
Cited alongside, same era.
Batch prompting: Efficient inference with large language model APIs
Cheng, Z., Kasai, J., and Yu, T · 2023
Cited alongside, same era.
Mind2web: Towards a generalist agent for the web, 2023
Deng, X., Gu, Y., Zheng, B., Chen, S., Stevens, S., Wang, B., Sun, H., and Su, Y · 2023
Cited alongside, same era.
Reasoning with language model is planning with world model
Hao, S., Gu, Y., Ma, H., Hong, J. J., Wang, Z., Wang, D. Z., and Hu, Z · 2023
Cited alongside, same era.
Language models, agent models, and world models: The law for machine reasoning and planning
Hu, Z. and Shu, T · 2023
Cited alongside, same era.
Ai alignment: A comprehensive survey
Ji, J., Qiu, T., Chen, B., Zhang, B., Lou, H., Wang, K., Duan, Y., He, Z., Zhou, J., Zhang, Z., et al · 2023
Cited alongside, same era.
Evaluating language-model agents on realistic autonomous tasks
Kinniment, M., Sato, L. J. K., Du, H., Goodrich, B., Hasin, M., Chan, L., Miles, L. H., Lin, T. R., Wijk, H., Burget, J., et al · 2023
Cited alongside, same era.
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Gemini: a family of highly capable multimodal models
Team, G., Anil, R., Borgeaud, S., Wu, Y., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., et al · 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
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Smartplay: A benchmark for llms as intelligent agents
Wu, Y., Tang, X., Mitchell, T. M., and Li, Y · 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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Lemur: Harmonizing natural language and code for language agents
Xu, Y., Su, H., Xing, C., Mi, B., Liu, Q., Shi, W., Hui, B., Zhou, F., Liu, Y., Xie, T., et al · 2023
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Failures pave the way: Enhancing large language models through tuning-free rule accumulation
Yang, Z., Li, P., and Liu, Y · 2023
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Expel: Llm agents are experiential learners
Zhao, A., Huang, D., Xu, Q., Lin, M., Liu, Y.-J., and Huang, G · 2023
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Zhu, X., Chen, Y., Tian, H., Tao, C., Su, W., Yang, C., Huang, G., Li, B., Lu, L., Wang, X., et al · 2023
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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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Agentboard: An analytical evaluation board of multi-turn llm agents
Ma, C., Zhang, J., Zhu, Z., Yang, C., Yang, Y., Jin, Y., Lan, Z., Kong, L., and He, J · 2024
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Autoact: Automatic agent learning from scratch via self-planning
Qiao, S., Zhang, N., Fang, R., Luo, Y., Zhou, W., Jiang, Y. E., Lv, C., and Chen, H · 2024
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Executable code actions elicit better llm agents
Wang, X., Chen, Y., Yuan, L., Zhang, Y., Li, Y., Peng, H., and Ji, H · 2024
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R-judge: Benchmarking safety risk awareness for llm agents
Yuan, T., He, Z., Dong, L., Wang, Y., Zhao, R., Xia, T., Xu, L., Zhou, B., Li, F., Zhang, Z., et al · 2024
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Gpt-4v(ision) is a generalist web agent, if grounded
Zheng, B., Gou, B., Kil, J., Sun, H., and Su, Y · 2024
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Hazard challenge: Embodied decision making in dynamically changing environments
Zhou, Q., Chen, S., Wang, Y., Xu, H., Du, W., Zhang, H., Du, Y., Tenenbaum, J. B., and Gan, C · 2024
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