7 citations · 11 across the 19 of their papers we have counts for
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cs.CL2025
Fast Thinking for Large Language Models
Haoyu Zheng, Zhuonan Wang, Yuqian Yuan +7
Reasoning-oriented Large Language Models (LLMs) often rely on generating explicit tokens step by step, and their effectiveness typically hinges on large-scale supervised fine-tunin…
cs.CL2025
Graft: Integrating the Domain Knowledge via Efficient Parameter Synergy for MLLMs
Yang Dai, Jianxiang An, Tianwei Lin +6
Multimodal Large Language Models (MLLMs) have achieved success across various domains. However, their applicability tends to degrade when confronted with different types of data in…
cs.CL2025
MoA: Heterogeneous Mixture of Adapters for Parameter-Efficient Fine-Tuning of Large Language Models
Jie Cao, Tianwei Lin, Bo Yuan +7
Recent studies integrate Low-Rank Adaptation (LoRA) and Mixture-of-Experts (MoE) to further enhance the performance of parameter-efficient fine-tuning (PEFT) methods in Large Langu…