{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T23:10:08Z","timestamp":1751411408184,"version":"3.41.0"},"publisher-location":"Singapore","reference-count":35,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819666010","type":"print"},{"value":"9789819665990","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-981-96-6599-0_23","type":"book-chapter","created":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T22:35:00Z","timestamp":1751409300000},"page":"332-346","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Novel Visual-Enhanced Dual Stream Long-Term Decision Framework for\u00a0Large Language Model Agents"],"prefix":"10.1007","author":[{"given":"Xingjin","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiahao","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiahui","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Linjing","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,7,2]]},"reference":[{"key":"23_CR1","unstructured":"Ahn, M., et\u00a0al.: Do as I can, not as I say: grounding language in robotic affordances. arXiv preprint arXiv:2204.01691 (2022)"},{"key":"23_CR2","first-page":"23716","volume":"35","author":"JB Alayrac","year":"2022","unstructured":"Alayrac, J.B., et al.: Flamingo: a visual language model for few-shot learning. Adv. Neural. Inf. Process. Syst. 35, 23716\u201323736 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"23_CR3","doi-asserted-by":"publisher","first-page":"1446","DOI":"10.1016\/j.neuropsychologia.2010.12.006","volume":"49","author":"C Bundesen","year":"2011","unstructured":"Bundesen, C., Habekost, T., Kyllingsb\u00e6k, S.: A neural theory of visual attention and short-term memory (NTVA). Neuropsychologia 49, 1446\u20131457 (2011). https:\/\/doi.org\/10.1016\/j.neuropsychologia.2010.12.006","journal-title":"Neuropsychologia"},{"key":"23_CR4","doi-asserted-by":"publisher","first-page":"9315","DOI":"10.1523\/JNEUROSCI.1097-11.2011","volume":"31","author":"NB Carlisle","year":"2011","unstructured":"Carlisle, N.B., Arita, J.T., Pardo, D., Woodman, G.: Attentional templates in visual working memory. J. Neurosci. 31, 9315\u20139322 (2011). https:\/\/doi.org\/10.1523\/JNEUROSCI.1097-11.2011","journal-title":"J. Neurosci."},{"key":"23_CR5","unstructured":"Chen, J., Lin, B., Xu, R., Chai, Z., Liang, X., Wong, K.Y.K.: MapGPT: Map-guided prompting for unified vision-and-language navigation. arXiv preprint arXiv:2401.07314 (2024)"},{"key":"23_CR6","unstructured":"Chen, M., et\u00a0al.: Evaluating large language models trained on code. arXiv preprint arXiv:2107.03374 (2021)"},{"key":"23_CR7","doi-asserted-by":"crossref","unstructured":"Chen, Z., et\u00a0al.: InternVL: scaling up vision foundation models and aligning for generic visual-linguistic tasks. arXiv preprint arXiv:2312.14238 (2023)","DOI":"10.1109\/CVPR52733.2024.02283"},{"key":"23_CR8","doi-asserted-by":"publisher","unstructured":"He, J., et al.: Deep reinforcement learning with a combinatorial action space for predicting popular Reddit threads. In: Su, J., Duh, K., Carreras, X. (eds.) Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pp. 1838\u20131848. Association for Computational Linguistics, Austin, Texas, November 2016. https:\/\/doi.org\/10.18653\/v1\/D16-1189","DOI":"10.18653\/v1\/D16-1189"},{"key":"23_CR9","unstructured":"Huang, S., et\u00a0al.: Language is not all you need: Aligning perception with language models. In: Advances in Neural Information Processing Systems, vol. 36 (2024)"},{"key":"23_CR10","unstructured":"Lin, B.Y., et al.: Swiftsage: a generative agent with fast and slow thinking for complex interactive tasks. arXiv preprint arXiv:2305.17390 (2023)"},{"key":"23_CR11","unstructured":"Liu, H., Li, C., Wu, Q., Lee, Y.J.: Visual instruction tuning. arXiv preprint arXiv:2304.08485 (2023)"},{"key":"23_CR12","unstructured":"Liu, Z., Zhang, Y., Li, P., Liu, Y., Yang, D.: Dynamic LLM-agent network: an LLM-agent collaboration framework with agent team optimization. arXiv preprint arXiv:2310.02170 (2023)"},{"key":"23_CR13","unstructured":"Achiam, J., Adler, S., Agarwal, S., et\u00a0al.: OpenAI, Gpt-4 Technical report (2023)"},{"key":"23_CR14","doi-asserted-by":"crossref","unstructured":"Park, J.S., O\u2019Brien, J., Cai, C.J., Morris, M.R., Liang, P., Bernstein, M.S.: Generative agents: interactive simulacra of human behavior. In: Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology, pp. 1\u201322 (2023)","DOI":"10.1145\/3586183.3606763"},{"key":"23_CR15","unstructured":"Qin, Y., et\u00a0al.: Tool learning with foundation models. arXiv preprint arXiv:2304.08354 (2023)"},{"key":"23_CR16","unstructured":"Schick, T., et al.: ToolFormer: Language models can teach themselves to use tools. arXiv preprint arXiv:2302.04761 (2023)"},{"key":"23_CR17","unstructured":"Shen, Y., Song, K., Tan, X., Li, D., Lu, W., Zhuang, Y.: HuggingGPT: Solving AI tasks with ChatGPT and its friends in HuggingFace. arXiv preprint arXiv:2303.17580 (2023)"},{"key":"23_CR18","unstructured":"Shinn, N., Cassano, F., Gopinath, A., Narasimhan, K.R., Yao, S.: Reflexion: Language agents with verbal reinforcement learning. In: Thirty-seventh Conference on Neural Information Processing Systems (2023)"},{"key":"23_CR19","unstructured":"Shridhar, M., Yuan, X., Cote, M.A., Bisk, Y., Trischler, A., Hausknecht, M.: ALFWorld: aligning text and embodied environments for interactive learning. In: International Conference on Learning Representations (2020)"},{"key":"23_CR20","unstructured":"Significant Gravitas: AutoGPT. https:\/\/github.com\/Significant-Gravitas\/AutoGPT"},{"key":"23_CR21","doi-asserted-by":"crossref","unstructured":"Sur\u00eds, D., Menon, S., Vondrick, C.: ViperGPT: visual inference via python execution for reasoning. arXiv preprint arXiv:2303.08128 (2023)","DOI":"10.1109\/ICCV51070.2023.01092"},{"key":"23_CR22","unstructured":"Team, G., Anil, R., Borgeaud, S., Wu, Y., et\u00a0al.: Gemini: A family of highly capable multimodal models (2023)"},{"key":"23_CR23","unstructured":"Team, X.: Xagent: an autonomous agent for complex task solving (2023)"},{"key":"23_CR24","unstructured":"Touvron, H., et\u00a0al.: LLaMA 2: Open foundation and fine-tuned chat models. arXiv preprint arXiv:2307.09288 (2023)"},{"key":"23_CR25","unstructured":"Wang, L., et\u00a0al.: A survey on large language model based autonomous agents. arXiv preprint arXiv:2308.11432 (2023)"},{"key":"23_CR26","doi-asserted-by":"crossref","unstructured":"Wang, R., Jansen, P., C\u00f4t\u00e9, M.A., Ammanabrolu, P.: Scienceworld: Is your agent smarter than a 5th grader? arXiv preprint arXiv:2203.07540 (2022)","DOI":"10.18653\/v1\/2022.emnlp-main.775"},{"key":"23_CR27","doi-asserted-by":"publisher","unstructured":"Wang, X., Li, L., Zeng, D.: LDM$$^2$$: a large decision model imitating human cognition with dynamic memory enhancement. In: Bouamor, H., Pino, J., Bali, K. (eds.) Findings of the Association for Computational Linguistics: EMNLP 2023, pp. 4660\u20134681. Association for Computational Linguistics, Singapore, December 2023. https:\/\/doi.org\/10.18653\/v1\/2023.findings-emnlp.309","DOI":"10.18653\/v1\/2023.findings-emnlp.309"},{"key":"23_CR28","unstructured":"Wei, J., et al.: Chain of thought prompting elicits reasoning in large language models. arXiv preprint arXiv:2201.11903 (2022)"},{"key":"23_CR29","unstructured":"Wu, C., Yin, S., Qi, W., Wang, X., Tang, Z., Duan, N.: Visual ChatGPT: Talking, drawing and editing with visual foundation models. arXiv preprint arXiv:2303.04671 (2023)"},{"key":"23_CR30","unstructured":"Wu, Q., et al.: Autogen: enabling next-gen LLM applications via multi-agent conversation framework. arXiv preprint arXiv:2308.08155 (2023)"},{"key":"23_CR31","unstructured":"Yang, Z., et al.: Mm-react: Prompting ChatGPT for multimodal reasoning and action. arXiv preprint arXiv:2303.11381 (2023)"},{"key":"23_CR32","unstructured":"Yao, S., Chen, H., Yang, J., Narasimhan, K.R.: Webshop: towards scalable real-world web interaction with grounded language agents. In: Oh, A.H., Agarwal, A., Belgrave, D., Cho, K. (eds.) Advances in Neural Information Processing Systems (2022). https:\/\/openreview.net\/forum?id=R9KnuFlvnU"},{"key":"23_CR33","unstructured":"Yao, S., et al.: Tree of thoughts: Deliberate problem solving with large language models. arXiv preprint arXiv:2305.10601 (2023)"},{"key":"23_CR34","unstructured":"Yao, S., et al.: React: Synergizing reasoning and acting in language models. In: The Eleventh International Conference on Learning Representations (2022)"},{"key":"23_CR35","unstructured":"Zhou, D., et al.: Least-to-most prompting enables complex reasoning in large language models. arXiv preprint arXiv:2205.10625 (2022)"}],"container-title":["Lecture Notes in Computer Science","Neural Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-6599-0_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T22:35:09Z","timestamp":1751409309000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-6599-0_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819666010","9789819665990"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-6599-0_23","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"2 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICONIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Information Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Auckland","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"New Zealand","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconip2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/iconip2024.org","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}