Add to ORKGContinual learning (CL) is an emerging learning paradigm that aims to emulate the human capability of learning and accumulating knowledge continually without forgetting the previously learned knowledge and also transferring the knowledge to new tasks to learn them better. This survey presents a comprehensive review of the recent progress of CL in the NLP field. It covers (1) all CL settings with a taxonomy of existing techniques. Besides dealing with forgetting, it also focuses on (2) knowledge transfer, which is of particular importance to NLP. Both (1) and (2) are not mentioned in the existing survey. Finally, a list of future directions is also discussed
Lifelong learning a.k.a Continual Learning is an advanced machine learning paradigm in which a syste...
Continual Learning (CL) is the process of learning new things on top of what has already been learne...
Continual learning is a Machine Learning paradigm that studies the problem of learning from a potent...
Continual learning (CL) aims to enable information systems to learn from a continuous data stream ac...
Continual learning (CL) is a setting in which a model learns from a stream of incoming data while av...
Recent work on large language models relies on the intuition that most natural language processing t...
In real scenarios, a multilingual model trained to solve NLP tasks on a set of languages can be requ...
Large Language Models (LMs) are known to encode world knowledge in their parameters as they pretrain...
Learning continuously during all model lifetime is fundamental to deploy machine learning solutions ...
The ability of a model to learn continually can be empirically assessed in different continual learn...
Continual Learning (CL) allows artificial neural networks to learn a sequence of tasks without catas...
Continual learning (CL) incrementally learns a sequence of tasks while solving the catastrophic for...
Part 1: Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT)International audienceArt...
Continual learning (CL) learns a sequence of tasks incrementally. There are two popular CL settings,...
In Continual Learning (CL), a neural network is trained on a stream of data whose distribution chang...
Lifelong learning a.k.a Continual Learning is an advanced machine learning paradigm in which a syste...
Continual Learning (CL) is the process of learning new things on top of what has already been learne...
Continual learning is a Machine Learning paradigm that studies the problem of learning from a potent...
Continual learning (CL) aims to enable information systems to learn from a continuous data stream ac...
Continual learning (CL) is a setting in which a model learns from a stream of incoming data while av...
Recent work on large language models relies on the intuition that most natural language processing t...
In real scenarios, a multilingual model trained to solve NLP tasks on a set of languages can be requ...
Large Language Models (LMs) are known to encode world knowledge in their parameters as they pretrain...
Learning continuously during all model lifetime is fundamental to deploy machine learning solutions ...
The ability of a model to learn continually can be empirically assessed in different continual learn...
Continual Learning (CL) allows artificial neural networks to learn a sequence of tasks without catas...
Continual learning (CL) incrementally learns a sequence of tasks while solving the catastrophic for...
Part 1: Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT)International audienceArt...
Continual learning (CL) learns a sequence of tasks incrementally. There are two popular CL settings,...
In Continual Learning (CL), a neural network is trained on a stream of data whose distribution chang...
Lifelong learning a.k.a Continual Learning is an advanced machine learning paradigm in which a syste...
Continual Learning (CL) is the process of learning new things on top of what has already been learne...
Continual learning is a Machine Learning paradigm that studies the problem of learning from a potent...