| | --- |
| | license: cc-by-4.0 |
| | configs: |
| | - config_name: train |
| | data_files: |
| | - split: train |
| | path: "train.csv" |
| | - config_name: validation |
| | data_files: |
| | - split: validation |
| | path: "validation.csv" |
| | - config_name: test |
| | data_files: |
| | - split: test |
| | path: "test.csv" |
| | --- |
| | |
| | # TravelPlanner Dataset |
| |
|
| | TravelPlanner is a benchmark crafted for evaluating language agents in tool-use and complex planning within multiple constraints. (See our [paper](https://arxiv.org/pdf/2402.01622.pdf) for more details.) |
| |
|
| | ## Introduction |
| |
|
| | In TravelPlanner, for a given query, language agents are expected to formulate a comprehensive plan that includes transportation, daily meals, attractions, and accommodation for each day. |
| |
|
| | TravelPlanner 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. |
| |
|
| | ## Split |
| |
|
| | <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. |
| |
|
| | <b>Validation Set</b>: 20 queries from each group, amounting to 180 queries in total. There is no human annotated plan in this set. |
| |
|
| | <b>Test Set</b>: 1,000 randomly distributed queries. To avoid data contamination, we only provide the level, days, and natural language query fields. |
| |
|
| | ## Record Layout |
| |
|
| | - "org": The city from where the journey begins. |
| | - "dest": The destination city. |
| | - "days": The number of days planned for the trip. |
| | - "visiting_city_number": The total number of cities included in the itinerary. |
| | - "date": The specific date when the travel is scheduled. |
| | - "people_numbe": The total number of people involved in the travel. |
| | - "local_constraint": The local hard constraint, including house rule, cuisine, room type and transportation. |
| | - "query": A natural language description or request related to the travel plan. |
| | - "level": The difficulty level, which is determined by the number of hard constraints. |
| | - "annotated_plan": A detailed travel plan annotated by a human, ensuring compliance with all common sense requirements and specific hard constraints. |
| | - "reference_information": Reference information for "sole-planning" mode. |
| |
|
| | ## Citation |
| |
|
| | 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. |
| |
|
| | ```bib |
| | @article{Xie2024TravelPlanner, |
| | author = {Jian Xie, Kai Zhang, Jiangjie Chen, Tinghui Zhu, Renze Lou, Yuandong Tian, Yanghua Xiao, Yu Su}, |
| | title = {TravelPlanner: A Benchmark for Real-World Planning with Language Agents}, |
| | journal = {arXiv preprint arXiv: 2402.01622}, |
| | year = {2024} |
| | } |
| | ``` |
| |
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