747 citations · 751 across the 6 of their papers we have counts for
7 papers
J-Miner: Recovering the Decision Logic of Fine-Tuned LLM Classifiers as Compact Rules
Yunfan Gao, Xinyi Huang, Tao Sheng +3
Task-fine-tuned large language model (LLM) classifiers acquire task-specific decision knowledge, but this knowledge remains implicit in distributed internal computations, making th…
DS2SC-Agent: A Multi-Agent Automated Pipeline for Rapid Chiplet Model Generation
Yiwei Wu, Yifan Wu, Yunhao Xiong +6
Constructing behavioral-level chiplet models (e.g., SystemC) is crucial for early-stage heterogeneous architecture exploration. Traditional manual modeling is notoriously time-cons…
Synergizing RAG and Reasoning: A Systematic Review
Yunfan Gao, Yun Xiong, Yijie Zhong +3
Recent breakthroughs in large language models (LLMs), particularly in reasoning capabilities, have propelled Retrieval-Augmented Generation (RAG) to unprecedented levels. By synerg…
U-NIAH: Unified RAG and LLM Evaluation for Long Context Needle-In-A-Haystack
Yunfan Gao, Yun Xiong, Wenlong Wu +3
Recent advancements in Large Language Models (LLMs) have expanded their context windows to unprecedented lengths, sparking debates about the necessity of Retrieval-Augmented Genera…
Preference-Guided Refactored Tuning for Retrieval Augmented Code Generation
Xinyu Gao, Yun Xiong, Deze Wang +4
Retrieval-augmented code generation utilizes Large Language Models as the generator and significantly expands their code generation capabilities by providing relevant code, documen…
Modular RAG: Transforming RAG Systems into LEGO-like Reconfigurable Frameworks
Yunfan Gao, Yun Xiong, Meng Wang +1
Retrieval-augmented Generation (RAG) has markedly enhanced the capabilities of Large Language Models (LLMs) in tackling knowledge-intensive tasks. The increasing demands of applica…
Retrieval-Augmented Generation for Large Language Models: A Survey
Yunfan Gao, Yun Xiong, Xinyu Gao +7
Large Language Models (LLMs) showcase impressive capabilities but encounter challenges like hallucination, outdated knowledge, and non-transparent, untraceable reasoning processes.…