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Qionghao Huang

2 accepted papers

2026

Test-Time Reinforcement Learning for Flow Matching

ICML 2026poster

Flow-matching has emerged as a leading framework for high-fidelity text-to-image generation. However, its alignment with human preferences through RL is often hindered by substantial computational overhead. In this paper, we introduce Flow-TTRL, the first test-time reinforcement learning framework t…

Cited by 0SourceScholar
2025

ML-GOOD: Towards Multi-Label Graph Out-Of-Distribution Detection

AAAI 2025technical

The out-of-distribution (OOD) detection on graph-structured data is crucial for deploying graph neural networks securely in open-world scenarios. However, existing methods have overlooked the prevalent scenario of multi-label classification in real-world applications. In this work, we investigate th…