Papers with WebArena benchmark
Navigating the Infinite Dynamic Web Space: Effective In-Context Exploration via Cognitive Multi-Agent Collaboration (2026.eacl-long)
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Guozhao Mo, Yanjiang Liu, Yafei Shi, Jiawei Chen, Yang Li, Yaojie Lu, Hongyu Lin, Ben He, Le Sun, Bo Zheng, Xianpei Han
| Challenge: | Existing methods for dynamic web navigation rely on greedy strategies or value estimation, struggle to achieve effective backtracking and are heavily dependent on proprietary models. |
| Approach: | They propose a cognitive multi-agent collaboration framework that enhances cyberspace exploration capability through In-Context Exploration. |
| Outcome: | The proposed framework surpasses the proprietary model Claude-3.5 Sonnet on the WebArena benchmark. |
Branch-and-Browse: Efficient and Controllable Web Exploration with Tree-Structured Reasoning and Action Memory (2026.acl-long)
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| Challenge: | Existing methods for embodied reasoning are coarse-grained and expensive . branch-and-browse framework enables fine-grounded, memory-guided, and efficient multi-branch reasoning. |
| Approach: | They propose a framework that unifies structured reasoning-acting, contextual memory, and efficient execution. |
| Outcome: | The proposed framework achieves task success rate of 35.8% and reduces execution time by up to 40.4% relative to state-of-the-art methods. |