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Heng-Chang Lu

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#artificial intelligence Preprint Jul 2026

BFMT: Enhancing Search Capabilities of Tree Sampler via Bootstrap Flow-Map Tree

Bootstrap Flow-Map-Tree (a.k.a BFMT), a computationally efficient sampling framework that enables full tree-path construction from any tree depth using a single function evaluation, drastically reducing computational overhead while providing critical foresight for sequential sampling.

Bing-Lin Ji, Anindya Sarkar, Heng-Chang Lu et al. · 1 citation
#artificial intelligence Preprint Jul 2026

Sampling Meets Interaction: Sequentially-Controlled Multi-Particle Flow-Maps for Efficient Inference-time Search

It is proved that the resulting sampling framework yields a multi-particle interaction-aware Feynman-Kac corrector that progressively steers the multi-particle system toward a KL-tilted target distribution, facilitating global exploration and preventing mode collapse.

Bing-Lin Ji, Anindya Sarkar, Heng-Chang Lu et al. · 0 citations

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