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December 8, 2025PLoS Computational BiologyOpen Access

ARTreeFormer: A faster attention-based autoregressive model for phylogenetic inference

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TXTianyu Xie

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Overview

Novel autoregressive model enhances phylogenetic inference speed using attention mechanisms, suggesting improved data handling.

Key Points

  • To develop an efficient autoregressive model for phylogenetic inference that overcomes limitations of existing methods.
  • Proposes ARTreeFormer, an improved model utilizing fixed-point iteration and attention mechanisms.
  • Implements vectorized computation for faster performance on CUDA devices.
  • Evaluates efficiency on a benchmark of real data phylogenetic inference problems.
  • Demonstrates significant improvements in computation speed for phylogenetic inference.
  • Maintains high approximation performance compared to previous methods.

Cite This Study

Tianyu Xie (2025) studied this question.

synapsesocial.com/papers/693624dd4fa91c937236d1echttps://doi.org/10.1371/journal.pcbi.1013768
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