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20212024
most citedAchieving Forgetting Prevention and Knowledge Transfer in Continual Learning

44 citations · 47 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.CL2024

Probing Language Models for Pre-training Data Detection

Zhenhua Liu, Tong Zhu, Chuanyuan Tan +3

Large Language Models (LLMs) have shown their impressive capabilities, while also raising concerns about the data contamination problems due to privacy issues and leakage of benchm…

cs.CL2024

Modeling Low-Resource Health Coaching Dialogues via Neuro-Symbolic Goal Summarization and Text-Units-Text Generation

Yue Zhou, Barbara Di Eugenio, Brian Ziebart +3

Health coaching helps patients achieve personalized and lifestyle-related goals, effectively managing chronic conditions and alleviating mental health issues. It is particularly be…

cs.CL2023

Analyzing and Reducing the Performance Gap in Cross-Lingual Transfer with Fine-tuning Slow and Fast

Yiduo Guo, Yaobo Liang, Dongyan Zhao +2

Existing research has shown that a multilingual pre-trained language model fine-tuned with one (source) language also performs well on downstream tasks for non-source languages, ev…

cs.CL20231 cited

Adapting a Language Model While Preserving its General Knowledge

Zixuan Ke, Yijia Shao, Haowei Lin +3

Domain-adaptive pre-training (or DA-training for short), also known as post-training, aims to train a pre-trained general-purpose language model (LM) using an unlabeled corpus of a…

cs.CL202144 cited

Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning

Zixuan Ke, Bing Liu, Nianzu Ma +2

Continual learning (CL) learns a sequence of tasks incrementally with the goal of achieving two main objectives: overcoming catastrophic forgetting (CF) and encouraging knowledge t…