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20242026
most citedTopology-aware Embedding Memory for Continual Learning on Expanding Networks

16 citations · 24 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.LG2025★ 1 cited

Improving Large Language Models with Concept-Aware Fine-Tuning

Michael K. Chen, Xikun Zhang, Jiaxing Huang +1

Large language models (LLMs) have become the cornerstone of modern AI. However, the existing paradigm of next-token prediction fundamentally limits their ability to form coherent,…

cs.LG2025★ 2 cited

A Survey of Direct Preference Optimization

Shunyu Liu, Wenkai Fang, Zetian Hu +9

Large Language Models (LLMs) have demonstrated unprecedented generative capabilities, yet their alignment with human values remains critical for ensuring helpful and harmless deplo…

cs.LG2024

Learning System Dynamics without Forgetting

Xikun Zhang, Dongjin Song, Yushan Jiang +2

Observation-based trajectory prediction for systems with unknown dynamics is essential in fields such as physics and biology. Most existing approaches are limited to learning withi…

cs.LG2024★ 5 cited

Continual Learning on Graphs: Challenges, Solutions, and Opportunities

Xikun Zhang, Dongjin Song, Dacheng Tao

Continual learning on graph data has recently attracted paramount attention for its aim to resolve the catastrophic forgetting problem on existing tasks while adapting the sequenti…

cs.LG2024★ 16 cited

Topology-aware Embedding Memory for Continual Learning on Expanding Networks

Xikun Zhang, Dongjin Song, Yixin Chen +1

Memory replay based techniques have shown great success for continual learning with incrementally accumulated Euclidean data. Directly applying them to continually expanding networ…