In modern sequential Monte Carlo (SMC) applications, such as diffusion model samplers, propagating a particle is expensive, so only a few particles can be afforded. In this regime, each resampling step decides which regions of the state space survive, so a better resampling scheme is worth extra computation. However, c...
This work introduces Mahalanobis-Ensemble Decoding (ME-Decoding), a novel Large Language Model (LLM) decoding framework that frames candidate token selection as ensemble pruning and devise an efficient greedy selection algorithm with near-linear complexity in the candidate size under early stopping, while establishing...
Dun-Yao Xue, Cheng-Shuo Du, Zheng-Bo Wang et al.· 0 citations
Quantile AlignTree Flow Matching (QAT-FM), an efficient structured coupling strategy that constructs a hierarchical coupling between a Gaussian prior and the target data distribution via a quantile-aligned tree structure, is proposed, enabling scalable training for large-scale high-dimensional generative tasks.
Jun-Yi Lin, Meng-Yu Li, Jing-Xuan Hu et al.· 0 citations
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