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cs.LG2026
GUI-HARVEST: Self-Improving GUI Agents through Evidence-Driven Harness Evolution
Geyi Yang, Zikun Qu, Xiang Li +4
The executable harness surrounding a GUI model determines how observations are assembled, actions are executed, and verification, recovery, and termination are controlled. Compared…
cs.LG2026
From Preference to Reciprocity: Decentralized Matching with Empirically Grounded LLM-agent Based Modeling
Wangxuan Fan, Xiaoyu Nie, Zhoutian Shi +5
Bipartite matching is a fundamental problem in game theory and market design. Classical approaches such as Gale--Shapley assume complete preferences and centralized computation, wh…