WebForge: Breaking the Realism-Reproducibility-Scalability Trilemma in Browser Agent Benchmark explores WebForge is an automated framework and benchmark for creating reproducible, realistic, and scalable browser agent environments without human annotation.. Commercial viability score: 8/10 in Browser Agents.
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Peng Yuan
Tencent BAC, Tsinghua University
Yuyang Yin
Tencent BAC
Yuxuan Cai
Tencent BAC
Zheng Wei
Tencent BAC
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Analysis model: GPT-4o · Last scored: 4/14/2026
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WebForge addresses a fundamental challenge in browser agent benchmarking by eliminating the need for costly manual curation and balancing realism and reproducibility.
Package WebForge as a SaaS platform offering continuous updates to benchmark datasets and interactive tools for performance analysis.
Could replace existing benchmarking methods that rely on static datasets and require manual updates, thus streamlining the evaluation process for web agents.
The market includes companies focused on browser automation, scraping, and testing, who would benefit from realistic, reproducible benchmarks.
Develop a subscription-based service that provides up-to-date and realistic browser agent benchmarks for companies developing or testing web automation tools.
The approach utilizes a four-agent pipeline to produce web environments that mimic real-world noise and complexity, enabling scalable and reproducible benchmarking beyond simple static tasks.
Evaluated with 934 tasks across 7 domains; demonstrated ability to control complexity along multiple dimensions and offered significant improvements over existing benchmarks.
Potential challenges include ensuring the benchmarks remain up to date with actual web environments and maintaining broad applicability across various types of browser agents.