Summary of Webcanvas: Benchmarking Web Agents in Online Environments, by Yichen Pan et al.
WebCanvas: Benchmarking Web Agents in Online Environments
by Yichen Pan, Dehan Kong, Sida Zhou, Cheng Cui, Yifei Leng, Bing Jiang, Hangyu Liu, Yanyi Shang, Shuyan Zhou, Tongshuang Wu, Zhengyang Wu
First submitted to arxiv on: 18 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces WebCanvas, an innovative online evaluation framework for web agents that effectively addresses the dynamic nature of web interactions. The framework contains three main components: a novel evaluation metric that captures critical intermediate actions or states necessary for task completions, a benchmark dataset called Mind2Web-Live, and lightweight annotation tools and testing pipelines. Building on WebCanvas, the authors open-source an agent framework with extensible modules for reasoning, providing a foundation for the community to conduct online inference and evaluations. The paper also analyzes performance discrepancies across various websites, domains, and experimental environments. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper is about how to make web agents better at understanding the internet. Right now, most tests only look at the static parts of websites, but real-life interactions involve lots of changes and updates. To solve this problem, the authors created a new way to test and evaluate web agents called WebCanvas. It includes three main parts: a special metric that looks at important steps in completing tasks, a dataset with many examples (542 tasks with 2439 states), and tools for annotating and testing. The paper also shares results from using this framework, showing how different agents perform on various websites. |
Keywords
* Artificial intelligence * Inference
