Unpacking LLM Bottlenecks and Continuous Learning Approaches

LLMs face core bottlenecks like continuous learning, sparse rewards, and long contexts, all rooted in the plasticity-stability dilemma that causes catastrophic forgetting. To address this, researchers have developed five major technical approaches, including external memory, to help models learn new information without forgetting the old.

2026-08-09 ~ 2026-08-10 · 2 related posts

• Continual Learning in LLMs: Five Approaches to Beating Catastrophic Forgetting — 机器之心 · 2026-08-09
• Decoding LLM Bottlenecks: Why Continual Learning is the Ultimate Challenge — 青稞AI · 2026-08-10