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Shao-Xuan Li

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#artificial intelligence Preprint Oct 2026

AutoSFT: An Agentic System for Automated Data Research in Supervised Fine-Tuning

Language model agents increasingly automate post-training, but when given the full training stack they converge on supervised fine-tuning and spend most effort revising training data. Existing systems give the agent one kind of control, selecting rows from a fixed pool or calling a generator, whereas a human data engin...

Bing-Xiang He, Peng Sun, Shi-Hao Peng et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Can AI Agents Learn Their Way to the Top? Evaluating Heuristic Learning in a Long-Running Game Agent Competition

Adversarial games have driven advances from heuristic search to reinforcement learning, yet learning and adapting strategies from limited samples remain challenging. AI agents offer an alternative by turning game experience into revisions of executable policies. Building on heuristic learning (HL), we formalize Adversa...

Kai-Sen Yang, Qing-Le Liu, Ke-Jin Wang et al. · 0 citations

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