Qi Ma
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The paper proposes QT-PUF, a novel quantum tunneling leakage-based Physical Unclonable Function (PUF) designed for ultralow-power, implantable IoMT devices, achieving high reliability and minimal power consumption.
The paper proposes a novel four-stage simulation framework that uses GPS-derived seasonal spatial priors and LLMs to generate demographically accurate, synthetic tourist mobility schedules for urban planning.
This paper proposes a post-training framework called Retrieval-Augmented Reinforcement Fine-Tuning (RA-RFT) to teach language models to reason by analogy.
Papers
Learning to Reason by Analogy via Retrieval-Augmented Reinforcement Fine-Tuning
Zilin Xiao, Qi Ma, Chun-cheng Jason Chen, Xintao Chen +3 more
This paper proposes a post-training framework called Retrieval-Augmented Reinforcement Fine-Tuning (RA-RFT) to teach language models to reason by analogy.