---
id: 20260923-T0-18
title: "通用多模态基础模型：一次部署，支持新增模态和多种任务"
title_en: "Generalized Multimodal Foundation Model Handles New Modalities and Tasks After Deployment"
url: https://ai.daily.yangsir.net/daily/20260923-T0-18
issue_date: 2026-09-23
publish_date: 2026-09-22T04:00:00.000Z
category: research
source_name: "arXiv cs.LG (ML)"
source_url: https://arxiv.org/abs/2609.22107
---

# 通用多模态基础模型：一次部署，支持新增模态和多种任务

现有大多数多模态融合模型在部署后只能处理预设模态（如视觉、文本、音频）和单一任务，难以快速适配新场景。一篇新论文提出“通用多模态基础模型”，目标是在部署后仍能支持新增模态和多种任务。该方向若成熟，可减少为每个新模态或新任务重新训练模型的成本，对需要快速接入新数据类型的应用团队有实际意义。目前仍属研究阶段，尚未看到开源实现或产品化信息。

## English Version

**Generalized Multimodal Foundation Model Handles New Modalities and Tasks After Deployment**

Most existing multimodal fusion models handle only predefined modalities (vision, text, audio) and a single task once deployed, making adaptation slow. A new paper proposes a "generalized multimodal foundation model" that aims to support new modalities and multiple tasks after deployment. If matured, this could cut the cost of retraining for each new modality or task, benefiting teams that need to quickly integrate new data types. The work remains at the research stage with no open-source release or productization announced.

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**来源**：[arXiv cs.LG (ML)](https://arxiv.org/abs/2609.22107)

**详情页**：https://ai.daily.yangsir.net/daily/20260923-T0-18

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