Ai2：Molmo 2开放发布催生MIT鲑鱼追踪研究
Ai2 发文介绍，MIT 2025 届毕业生 Kai Van Brunt 在 MIT BeeryLab 基于开放视觉语言模型 Molmo 2 开发出 Molmo2Fish，用于在水下声纳视频中追踪鲑鱼，并可根据自然语言指令修正追踪预测。文章称，Molmo 2 能直接处理整段视频并输出目标轨迹；Van Brunt 在鲑鱼视频上微调后，Molmo2Fish 在未接受纠正前表现与专用鱼类追踪系统大致相当，但结果因河流而异。实验显示，语言引导修正在指令清晰时有效，但模型较难改进自身最强的预测；Molmo2Fish 仍是尚未部署的研究项目。
该案例展示了开放模型、代码与训练数据的发布如何让研究者把通用的视频-语言能力迁移到生态监测等专门领域。
How Molmo 2’s open release helped an MIT researcher rethink fish tracking
October 13, 2026
Ai2
When we released Molmo 2, our open vision-language model for images and video, we made the model, code, and training data openly available so researchers could inspect how it was built and customize it for their own work. Molmo 2 can follow a particular figure or object as it moves through a video, identify something described in language – such as “the second car to cross the finish line” – and reason about events over time. Making the model and the resources behind it open gives researchers a starting point for applying those capabilities to new problems.
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