Continual learning empowers models to adapt autonomously to the ever-changing
environment or data streams without forgetting old knowledge. Prompt-based approaches …

Inspired by the Lottery Ticket Hypothesis (LTH), which highlights the existence of efficient
subnetworks within larger, dense networks, a high-performing Winning Subnetwork (WSN) …

The foremost challenge in continual learning is devising strategies to alleviate catastrophic
forgetting, thereby preserving a model's memory of prior knowledge while learning new …