新闻
Ai2 at COLM 2026: Open research, from models to agents for science
Ai2 · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Ai2 presented research on hybrid language models combining attention and recurrence, achieving 49% training token efficiency gains, plus released Olmo-core 3 for mixture-of-experts training.
- 为何重要
- ML engineers building efficient language models or training infrastructure should track these architectural innovations and open-source tooling releases.
- 注意
- Efficiency gains shown on MMLU benchmark; real-world performance across diverse tasks and deployment scenarios remains to be validated by the community.
- agent
- language model
- olmo
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