12 citations · 18 across the 3 of their papers we have counts for
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cs.LG2025
Skrull: Towards Efficient Long Context Fine-tuning through Dynamic Data Scheduling
Hongtao Xu, Wenting Shen, Yuanxin Wei +6
Long-context supervised fine-tuning (Long-SFT) plays a vital role in enhancing the performance of large language models (LLMs) on long-context tasks. To smoothly adapt LLMs to long…
cs.LG2024★ 6 cited
A Comprehensive Survey of Dynamic Graph Neural Networks: Models, Frameworks, Benchmarks, Experiments and Challenges
ZhengZhao Feng, Rui Wang, TianXing Wang +3
Dynamic Graph Neural Networks (GNNs) combine temporal information with GNNs to capture structural, temporal, and contextual relationships in dynamic graphs simultaneously, leading…