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README.md
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license: cc-by-4.0
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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](https://arxiv.org/abs/2311.12983) for more details.)
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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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<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 plan as demonstrations for in-context learning.
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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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- "org": The city from where the journey begins.
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- "dest": The destination city.
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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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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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license: cc-by-4.0
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---
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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](https://arxiv.org/abs/2311.12983) 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 plan as demonstrations for in-context learning.
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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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- "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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