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VaLiDRec, a generative recommendation framework based on variable-length, LLM-aligned semantic identifiers, demonstrates that LLM-native variable-length semantic identifiers provide a more expressive and efficient paradigm for generative recommendation.
ODYSSE is presented, a Reinforced Fine-Tuning (RFT) framework for personalized agentic reasoning designed to address long action horizons and strong cross-step dependencies in personalized agentic reasoning, and an episodic batch sampler that groups actions from the same episode into unified training batches, facilitat...
The Fusion of Layer-wise Exits for Sequential Recommendation (FLEXRec), a discriminative framework that enhances compact LLMs while retaining scalable full-corpus ranking and achieves state-of-the-art accuracy among competing methods while remaining highly efficient.
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