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cs.CL2025
Breaking Thought Patterns: A Multi-Dimensional Reasoning Framework for LLMs
Xintong Tang, Meiru Zhang, Shang Xiao +5
Large language models (LLMs) are often constrained by rigid reasoning processes, limiting their ability to generate creative and diverse responses. To address this, a novel framewo…
cs.CL2024
SEEKR: Selective Attention-Guided Knowledge Retention for Continual Learning of Large Language Models
Jinghan He, Haiyun Guo, Kuan Zhu +3
Continual learning (CL) is crucial for language models to dynamically adapt to the evolving real-world demands. To mitigate the catastrophic forgetting problem in CL, data replay h…