Update content.py

content.py

@@ -1,16 +1,16 @@
 TITLE = """<h1 align="center" id="space-title">TravelPlanner Leaderboard</h1>"""
 
 INTRODUCTION_TEXT = """
-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.)
+TravelPlanner 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.)
 
 ## Data
-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.
+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.
 For constraints, from the perspective of real world applications, we design three types of them: Environment Constraint, Commonsense Constraint, and Hard Constraint.
-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.
+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.
 
-TravelBench data can be found in [this dataset](https://huggingface.co/datasets/osunlp/TravelBench). 
+TravelPlanner data can be found in [this dataset](https://huggingface.co/datasets/osunlp/TravelPlanner). 
 
-## Submission Guidelines for TravelBench
+## Submission Guidelines for TravelPlanner
 Participants are invited to submit results for both validation and testing phases. The submissions will be evaluated based on several metrics: delivery rate, commonsense constraint pass rate (micro/macro), hard constraint pass rate (micro/macro), and the final pass rate.
 
 ### Format of Submission:
@@ -39,9 +39,9 @@ Format: Use "Name, City" to specify the chosen restaurant and its location. If a
 Description: Information about attractions visited.
 Format: List attractions as "Name, City". If visiting multiple attractions, separate them with a semicolon ";". If no attraction is planned, use "-".
 
-Please refer to [this](https://huggingface.co/datasets/osunlp/TravelBench/resolve/main/example_submission.jsonl?download=true) for example submission file. 
+Please refer to [this](https://huggingface.co/datasets/osunlp/TravelPlanner/resolve/main/example_submission.jsonl?download=true) for example submission file. 
 
-Submission made by our team are labelled "TravelBench Team". Each submission will be automatically evaluated and scored based on the predefined metrics. You can then obtain the scores and download the detailed constraint pass rates after the evaluation.
+Submission made by our team are labelled "TravelPlanner Team". Each submission will be automatically evaluated and scored based on the predefined metrics. You can then obtain the scores and download the detailed constraint pass rates after the evaluation.
 
 ## Show Your Results on Leaderborad
 If you are interested in showing your results on our leaderboard, we invite you to reach out to us. Please send an email to [us](mailto:[email protected]) including the following details: evaluation mode, fondation model, tool-use strategy, planning strategy, organization, and your paper link (if available), along with your submission files.