Self-Evolving GPT: A Lifelong Autonomous Experiential Learner
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Jinglong Gao, Xiao Ding, Yiming Cui, Jianbai Zhao, Hepeng Wang, Ting Liu, Bing Qin. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2024.
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Most existing approaches construct an experience pool or memory bank and focus on improving the retrieval of useful past information.
“Most existing approaches construct an experience pool or memory bank and focus on improving the retrieval of useful past information (Zhao et al., 2024; Gao et al., 2024; Xu et al., 2025b).”
From 3DLLM-Mem: Long-Term Spatial-Temporal Memory for Embodied 3D Large Language Model (2025) · cites this paper as Gao et al., 2024
Section 3.1 describes an experience memory, and Section 3.3 describes retrieving similar tasks from it, so the paper is an example of an approach that stores and retrieves past experience. It does not establish that most existing approaches do this or that improving retrieval is their main focus; its own framework also emphasizes experience transfer and induction. The supplied passages have no page numbers. (LLM, conf=0.84)
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Cited by
Sorted by citations
3DLLM-Mem: Long-Term Spatial-Temporal Memory for Embodied 3D Large Language Model
Hu, W., Hong, Y., Wang, Y., Gao, L., Wei, Z., Yao, X., Peng, N., Bitton, Y., Szpektor, I., & Chang, K.-W. (2025) · Advances in Neural Information Processing Systems 38 · doi:10.52202/085713-2278 · Cited by 2 · see citing works
- Authors
- Gao, J., Ding, X., Cui, Y., Zhao, J., Wang, H., Liu, T., & Qin, B.
- Affiliations
- Harbin Institute of Technology (CN)
- IFlyTek (China) (CN)
- Venue
- Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Published
- 2024
- Pages
- 6385-6432
- ISSN
- 0736-587X (ISSN-L)
- OpenAlex
- W4402671825
- Cited by
- 5
- References
- 0
- Citations by year
- 2025: 5
- FWCI
- 1.21
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Proceedings of the conference - Association for Computational Linguistics. Meeting (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion, cc-by)
- arXiv (Cornell University) (cc-by)
- Funders
- National Natural Science Foundation of China (U22B2059, 62176079)
- Natural Science Foundation of Heilongjiang Province (YQ2022F005)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Keywords
- lifelong learning, self-directed learning, experiential learning, large language models, self-improving AI
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