Dynamic Proxy-Mixing: Transferring Replay Controllers from Small to Large Models for Continual Instruction Tuning
arXiv:2606.00400v1 Announce Type: new Abstract: Continual instruction tuning updates a language model through a sequence of new domains, yet each update can progressively erode previously learned capabilities and alignment behavior. Replay is the standard mitigation, but fixed replay ratios are inherently limited because the optimal mixture varies with the current domain, the training stage, and the evolving vulnerability of prior behaviors. We propose PROX-YMIX, a framework that learns a dynamic replay controller on a small proxy model and transfers the frozen controller to a larger target. T
The continuous improvement and application of large language models necessitate robust methods for ongoing learning without catastrophic forgetting, driving innovation in instruction tuning techniques.
This development addresses a critical limitation in AI's ability to continually learn and adapt, which is fundamental for creating more dynamic and contextually aware autonomous systems.
The ability to efficiently transfer replay controllers from smaller to larger models for continual instruction tuning changes the paradigm for how LLMs can be updated and maintained, making ongoing learning more scalable and less resource-intensive.
- · AI developers
- · Cloud providers
- · Edge AI applications
- · Companies using LLMs for specialized tasks
- · Model retraining services relying on full re-training
- · Less efficient continual learning techniques
Language models become more adaptable and retain learned capabilities better over time, accelerating their deployment in dynamic environments.
The cost and computational resources required for maintaining and updating large AI models are reduced, potentially democratizing access to advanced AI capabilities.
More robust continual learning could lead to the proliferation of highly specialized and continuously evolving AI agents that are integrated into a wider array of daily operations.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.LG