SEAL Paper: Models That Continuously Learn Post-Deployment
mdancho84 · x · 2026-07-09
This post introduces a new paper, SEAL: Self-Adapting Language Models (arXiv:2506.10943), which proposes that language models can continuously learn after deployment without requiring retraining.
The author highlights that this method allows models to learn from new data in real-time, rectify degraded knowledge, and maintain persistent memory across different sessions.
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