---
id: 20260708-T0-18
title: "稀疏残差路由：用更少计算量实现更准确的天气预报"
title_en: "Sparse Residual Routing: Fewer Tokens, Better Weather Forecasts"
url: https://ai.daily.yangsir.net/daily/20260708-T0-18
issue_date: 2026-07-08
publish_date: 2026-07-07T04:00:00.000Z
category: research
source_name: "arXiv cs.LG (ML)"
source_url: https://arxiv.org/abs/2607.02829
---

# 稀疏残差路由：用更少计算量实现更准确的天气预报

新研究提出稀疏残差路由（Sparse Residual Routing），改进基于ViT的天气预报模型。传统模型对所有空间token进行统一计算，而该方法利用大气网格点间的相似性，减少冗余计算，用更少token实现更优预测。论文发布于arXiv。

## English Version

**Sparse Residual Routing: Fewer Tokens, Better Weather Forecasts**

A new paper introduces Sparse Residual Routing to improve ViT-based weather forecasting models. Traditional models compute uniformly across all spatial tokens, while this method leverages similarity among atmospheric grid points to reduce redundant computation, achieving better forecasts with fewer tokens. Paper on arXiv.

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**来源**：[arXiv cs.LG (ML)](https://arxiv.org/abs/2607.02829)

**详情页**：https://ai.daily.yangsir.net/daily/20260708-T0-18

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