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cs.CL2025
GuiLoMo: Allocating Expert Number and Rank for LoRA-MoE via Bilevel Optimization with GuidedSelection Vectors
Hengyuan Zhang, Xinrong Chen, Yingmin Qiu +7
Parameter-efficient fine-tuning (PEFT) methods, particularly Low-Rank Adaptation (LoRA), offer an efficient way to adapt large language models with reduced computational costs. How…
cs.CL2025
Domaino1s: Guiding LLM Reasoning for Explainable Answers in High-Stakes Domains
Xu Chu, Zhijie Tan, Hanlin Xue +3
Large Language Models (LLMs) are widely applied to downstream domains. However, current LLMs for high-stakes domain tasks, such as financial investment and legal QA, typically gene…
cs.CL2025
CLEAR-KGQA: Clarification-Enhanced Ambiguity Resolution for Knowledge Graph Question Answering
Liqiang Wen, Guanming Xiong, Tong Mo +3
This study addresses the challenge of ambiguity in knowledge graph question answering (KGQA). While recent KGQA systems have made significant progress, particularly with the integr…