Yunchen Pu
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This paper proposes Learning to Allocate (L2A), an end-to-end framework for resource-adaptive inference in Large Language Models (LLMs) using budget-conditioned and input-aware gating networks.
This paper introduces Bifocal dLLMs (R2LM), a new paradigm for discrete diffusion language models that combines causal and bidirectional attention for improved throughput and generation quality.
This paper proposes Diffusion-GR2, a method to convert an autoregressive reasoning re-ranker into a block-diffusion re-ranker while maintaining accuracy and increasing speed.
Papers
Diffusion-GR2: Diffusion Generative Reasoning Re-ranker
Zhuoxuan Zhang, Kangqi Ni, Yuhang Chen, Mingfu Liang +11 more
This paper proposes Diffusion-GR2, a method to convert an autoregressive reasoning re-ranker into a block-diffusion re-ranker while maintaining accuracy and increasing speed.