zzz47zzz/codebase-for-incremental-learning-with-llm
[ACL2024] A Codebase for Incremental Learning with Large Language Models; Official released code for "Learn or Recall? Revisiting Incremental Learning with Pre-trained Language Models (ACL 2024)", "Incremental Sequence Labeling: A Tale of Two Shifts (ACL 2024 Findings)", and "Concept-1K: A Novel Benchmark for Instance Incremental Learning (arxiv)"
This project helps researchers and practitioners in natural language processing to develop and test models that can learn new information over time without forgetting what they've already learned. It takes various text datasets (like text for classification, intent, or named entity recognition) and implements incremental learning techniques using large language models. The output is a more adaptable and robust language model that performs well on new tasks while retaining knowledge from old ones, ideal for AI/ML researchers, data scientists, and language model developers.
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Use this if you are developing or evaluating large language models that need to continuously learn from new data streams without suffering from 'catastrophic forgetting' on previously learned tasks.
Not ideal if you are looking for a pre-trained, ready-to-use application, as this is a research codebase requiring technical expertise to set up and run experiments.
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Feb 01, 2025
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