Tao Chen
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PragLocker is a novel prompt protection scheme that secures valuable LLM agent prompts against theft and reuse by other proprietary models by making them non-portable.
VITAL introduces a novel latent-space reasoning framework for medical MLLMs, utilizing visual-semantic dual supervision to enhance reasoning capabilities and provide crucial interpretability without sacrificing efficiency.
The paper proposes Skill-RM, a unified framework that treats reward modeling as an agentic task to consistently integrate diverse evaluation criteria, achieving superior performance over traditional methods.
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.