Jun 27, 2024 · We study the pros and cons of updating a language model when new data comes from new languages – the case of continual learning under language shift. Starting ...

Jun 30, 2024 · Continual lifelong learning in natural language processing: A survey. In D ... Dbpedia abstracts: A large-scale, open, multilingual nlp training corpus.

7 days ago · Natural Language Processing (NLP), for example, often exploits Transfer Learning ... The studies of Continual Pre-Training in NLP are however limited in terms of ...

Jun 24, 2024 · Continual Learning. LLMs will be designed to learn continually, adapting to new tasks and domains without forgetting previous knowledge. This will involve ...

Jun 11, 2024 · The study investigates efficient continual pre-training methods, focusing on learning ... What are the latest NLP methods for generating natural language text?

Jun 10, 2024 · Conventional machine learning approaches for natural language processing (NLP) mainly rely on the availability of large-scale sets of task-specific examples.

Jun 9, 2024 · This survey presents a comprehensive review and analysis of the recent progress of CL in NLP, which has significant differences from CL in computer vision and ...

1 day ago · Continual learning focuses on enabling models to learn continuously from new data without forgetting previous knowledge. This approach is crucial for creating ...

Jun 10, 2024 · Continual learning requires the model to learn multi- ple tasks sequentially. In continual learning, the model should possess the ability to maintain its ...

Jun 10, 2024 · Continual Learning: Building models that can learn continuously from new data without forgetting previous knowledge, mimicking human learning processes.