AIFIRST ToMoE: converting dense LLMs to Mixture-of-Experts via dynamic structural pruning
The brief
ToMoE is a research paper proposing a method to convert existing dense large language models into Mixture-of-Experts architectures through dynamic structural pruning, without full retraining from scratch.
Key points
- The approach routes inputs to identified parameter subsets that behave as specialized experts.
- If reproduced broadly, the technique could lower the cost of obtaining MoE efficiency gains from already-trained dense models.
Sources
- redditreddit.com