Can LLMs Learn New Concepts Incrementally without Forgetting?

Understand

Large Language Models (LLMs) have achieved remarkable success across various tasks, yet their ability to learn incrementally without forgetting remains underexplored.

• Incremental learning (IL) is crucial as it enables models to acquire new knowledge while retaining previously learned information, akin to human learning.
• Existing benchmarks for IL are insufficient due to data leakage issues and the overqualification of LLMs.
• To address these challenges, we introduce Concept-1K, a novel dataset comprising 1,023 recently emerged concepts across diverse domains.