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cs.AI2026
SCOPE: Evolving Symbolic World for Planning in Open-Ended Environments
Yundaichuan Zhan, Minghe Gao, Zhongqi Yue +7
Recent works have explored integrating Vision-Language Models (VLMs) with classical planners that rely on symbolic representations of planning problems to generate long-horizon pla…
cs.AI2026
Learning to Adapt: Self-Improving Web Agent via Cognitive-Aware Exploration
Weile Chen, Bingchen Miao, Qifan Yu +6
Recent advances in Multimodal Large Language Models (MLLMs) have led to promising progress in web agents. However, existing web agents often rely on handcrafted execution pipelines…