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license: cc-by-4.0 |
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# TravelBench Dataset |
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TravelBench is a benchmark crafted for evaluating language agents in tool-use and complex planning within multiple constraints. (See our [paper]() for more details.) |
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## Introduction |
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In TravelBench, for a given query, language agents are expected to formulate a comprehensive plan that includes transportation, daily meals, attractions, and accommodation for each day. |
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TravelBench comprises 1,225 queries in total. The number of days and hard constraints are designed to test agents' abilities across both the breadth and depth of complex planning. |
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## Split |
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<b>Train Set</b>: 5 queries with corresponding human-annotated plans for group, resulting in a total of 45 query-plan pairs. This set provides the human annotated plans as demonstrations for in-context learning. |
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<b>Validation Set</b>: 20 queries from each group, amounting to 180 queries in total. There is no human annotated plan in this set. |
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<b>Test Set</b>: 1,000 randomly distributed queries. To avoid data contamination, we only provide the level, days, and natural language query fields. |
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## Record Layout |
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- "org": The city from where the journey begins. |
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- "dest": The destination city. |
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- "days": The number of days planned for the trip. |
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- "visiting_city_number": The total number of cities included in the itinerary. |
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- "date": The specific date when the travel is scheduled. |
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- "people_numbe": The total number of people involved in the travel. |
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- "local_constraint": The local hard constraint, including house rule, cuisine, room type and transportation. |
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- "query": A natural language description or request related to the travel plan. |
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- "level": The difficulty level, which is determined by the number of hard constraints. |
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- "annotated_plan": A detailed travel plan annotated by a human, ensuring compliance with all common sense requirements and specific hard constraints. |
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## Citation |
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If our paper or related resources prove valuable to your research, we kindly ask for citation. Please feel free to contact us with any inquiries. |
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```bib |
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@article{Xie2024TravelBench, |
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title={}, |
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author={}, |
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journal={}, |
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year={2024} |
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} |
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``` |
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