3 papers
cs.AI2026
eMoT: evolving Memory-of-Thought via Symbolic Anchoring and Memory Corrosion
Xiang Li, Jiwei Wei, Ke Liu +5
While Large Language Models (LLMs) achieve impressive performance on multi-step reasoning tasks, their reliability is persistently hindered by critical limitations such as unconstr…
cs.LG2026
Learning Dynamic Representations via An Optimally-Weighted Maximum Mean Discrepancy Optimization Framework for Continual Learning
KaiHui Huang, RunQing Wu, JinHui Sheng +4
Continual learning has emerged as a pivotal area of research, primarily due to its advantageous characteristic that allows models to persistently acquire and retain information. Ho…
cs.LG2025
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model
Runqing Wu, Fei Ye, Qihe Liu +3
Continual Learning seeks to develop a model capable of incrementally assimilating new information while retaining prior knowledge. However, current research predominantly addresses…