activity
20232026
most citedRetrieval-Augmented Generation for Large Language Models: A Survey

747 citations · 756 across the 10 of their papers we have counts for

collaborators

11 papers

cs.LG2026

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…

cs.CV2026

Hierarchical Textual Knowledge for Enhanced Image Clustering

Yijie Zhong, Yunfan Gao, Weipeng Jiang +1

Image clustering aims to group images in an unsupervised fashion. Traditional methods focus on knowledge from visual space, making it difficult to distinguish between visually simi…

cs.CL2026★ 1 cited

HingeMem: Boundary Guided Long-Term Memory with Query Adaptive Retrieval for Scalable Dialogues

Yijie Zhong, Yunfan Gao, Haofen Wang

Long-term memory is critical for dialogue systems that support continuous, sustainable, and personalized interactions. However, existing methods rely on continuous summarization or…

cs.AI2026

Embodied Science: Closing the Discovery Loop with Agentic Embodied AI

Xiang Zhuang, Chenyi Zhou, Kehua Feng +10

Artificial intelligence has demonstrated remarkable capability in predicting scientific properties, yet scientific discovery remains an inherently physical, long-horizon pursuit go…

cs.AI2025

CitySeeker: How Do VLMS Explore Embodied Urban Navigation With Implicit Human Needs?

Siqi Wang, Chao Liang, Yunfan Gao +5

Vision-Language Models (VLMs) have made significant progress in explicit instruction-based navigation; however, their ability to interpret implicit human needs (e.g., "I am thirsty…

cs.IR2025★ 4 cited

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…

cs.IR2025

StePO-Rec: Towards Personalized Outfit Styling Assistant via Knowledge-Guided Multi-Step Reasoning

Yuxi Bi, Yunfan Gao, Haofen Wang

Advancements in Generative AI offers new opportunities for FashionAI, surpassing traditional recommendation systems that often lack transparency and struggle to integrate expert kn…

cs.CL2025

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…

cs.AI2024★ 4 cited

Decoding Urban Industrial Complexity: Enhancing Knowledge-Driven Insights via IndustryScopeGPT

Siqi Wang, Chao Liang, Yunfan Gao +3

Industrial parks are critical to urban economic growth. Yet, their development often encounters challenges stemming from imbalances between industrial requirements and urban servic…

cs.CL2024

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…

cs.CL2023★ 747 cited

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.…