Personal Large Language Model Agents: A Case Study on Tailored Travel Planning (2024.emnlp-industry)
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Harmanpreet Singh, Nikhil Verma, Yixiao Wang, Manasa Bharadwaj, Homa Fashandi, Kevin Ferreira, Chul Lee
| Challenge: | Large Language Models (LLMs) are becoming more autonomous and capable of handling real-world tasks through their access to tools, various planning strategies, and memory, referred to as LLM agents. |
| Approach: | They introduce a personalized version of TravelPlanner and establish baselines for personal LLM agents by comparing generic and personal plans. |
| Outcome: | The proposed model encapsulates user-related information, preferences, and personal concepts and provides baselines for personal LLM agents. |
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