3 papers
cs.CL2024
In-context Continual Learning Assisted by an External Continual Learner
Saleh Momeni, Sahisnu Mazumder, Zixuan Ke +1
Existing continual learning (CL) methods mainly rely on fine-tuning or adapting large language models (LLMs). They still suffer from catastrophic forgetting (CF). Little work has b…
cs.CL2024
Continual Learning Using Only Large Language Model Prompting
Jiabao Qiu, Zixuan Ke, Bing Liu
We introduce CLOB, a novel continual learning (CL) paradigm wherein a large language model (LLM) is regarded as a black box. Learning is done incrementally via only verbal promptin…
cs.LG2024
Open-World Continual Learning: Unifying Novelty Detection and Continual Learning
Gyuhak Kim, Changnan Xiao, Tatsuya Konishi +2
As AI agents are increasingly used in the real open world with unknowns or novelties, they need the ability to (1) recognize objects that (a) they have learned before and (b) detec…