Author

Qing-Le Liu

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Preprint Oct 2026

World Models'Last Exam in Physics

Video world models can produce visually convincing yet physically inconsistent sequences, raising concerns about their reliability for prediction and planning in embodied AI systems. Existing evaluations often rely on model-based judgments or reference videos, while direct physical tests largely focus on mechanics. We...

Ming-Ju Gao, Qing-Le Liu, Yu-Zhao 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

#artificial intelligence Preprint Sep 2026

When Context Misleads: In-context Learning with Jurisdiction in Large Language Models

J-ICL is proposed, a post-training framework that incorporates context validation into the training objective and improves ICLEval and reality accuracy by an average of 5.84 percentage points and reality accuracy by 9.20 points over the corresponding base models.

Pei-Lin Li, Qing-Le Liu, Jun-Yang Feng et al. · 0 citations