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cs.LG2026
Hybrid-LoRA: Bridging Full Fine-Tuning and Low-Rank Adaptation for Post-Training
Chengqian Zhang, Wei Zhu, Kyumin Lee
Post-training has become essential for adapting large language models (LLMs) to complex downstream behaviors, including instruction following, preference alignment, and multi-step…
cs.LG2025
Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning
Zhengyu Hu, Yichuan Li, Zhengyu Chen +4
Textual Attributed Graphs (TAGs) are crucial for modeling complex real-world systems, yet leveraging large language models (LLMs) for TAGs presents unique challenges due to the gap…