2 papers
cs.LG2026
AutoRAGTuner: A Declarative Framework for Automatic Optimization of RAG Pipelines
Xintan Zeng, Yongchao Liu, Yice Luo +1
Retrieval-Augmented Generation (RAG) enhances LLMs, but performance is highly sensitive to complex architecture designs and hyper-parameter configurations, which currently rely on…
cs.LG2025
Scaling Graph Chain-of-Thought Reasoning: A Multi-Agent Framework with Efficient LLM Serving
Chengying Huan, Ziheng Meng, Yongchao Liu +11
Graph Chain-of-Thought (Graph-CoT) enables large language models (LLMs) to perform step-by-step reasoning over graph-structured knowledge, but existing pipelines suffer from low ac…