Continual learning of large language models: A comprehensive survey
The recent success of large language models (LLMs) trained on static, pre-collected,
general datasets has sparked numerous research directions and applications. One such …
general datasets has sparked numerous research directions and applications. One such …
Recent advances of foundation language models-based continual learning: a survey
Recently, foundation language models (LMs) have marked significant achievements in the
domains of natural language processing (NLP) and computer vision (CV). Unlike traditional …
domains of natural language processing (NLP) and computer vision (CV). Unlike traditional …
Adaptive Rank, Reduced Forgetting: Knowledge Retention in Continual Learning Vision-Language Models with Dynamic Rank-Selective LoRA
We investigate whether the pre-trained knowledge of vision-language models (VLMs), such
as CLIP, can be retained or even enhanced during continual learning (CL) while absorbing …
as CLIP, can be retained or even enhanced during continual learning (CL) while absorbing …
Recent Advances of Multimodal Continual Learning: A Comprehensive Survey
Continual learning (CL) aims to empower machine learning models to learn continually from
new data, while building upon previously acquired knowledge without forgetting. As …
new data, while building upon previously acquired knowledge without forgetting. As …
Less is More: Efficient Model Merging with Binary Task Switch
B Qi, F Li, Z Wang, J Gao, D Li, P Ye, B Zhou - arXiv preprint arXiv …, 2024 - arxiv.org
As an effective approach to equip models with multi-task capabilities without additional
training, model merging has garnered significant attention. However, existing methods face …
training, model merging has garnered significant attention. However, existing methods face …
One VLM to Keep it Learning: Generation and Balancing for Data-free Continual Visual Question Answering
Vision-Language Models (VLMs) have shown significant promise in Visual Question
Answering (VQA) tasks by leveraging web-scale multimodal datasets. However, these …
Answering (VQA) tasks by leveraging web-scale multimodal datasets. However, these …
Mining your own secrets: Diffusion classifier scores for continual personalization of text-to-image diffusion models
Personalized text-to-image diffusion models have grown popular for their ability to efficiently
acquire a new concept from user-defined text descriptions and a few images. However, in …
acquire a new concept from user-defined text descriptions and a few images. However, in …
THE CASE FOR COGNITIVE-DISSONANCE AWARE CONTINUAL UPDATE OF KNOWLEDGE IN LLMS
IN PRAISE - openreview.net
Despite remarkable capabilities, large language models (LLMs) struggle to continually
update their knowledge without catastrophic forgetting. In contrast, humans effortlessly …
update their knowledge without catastrophic forgetting. In contrast, humans effortlessly …