747 citations · 821 across the 11 of their papers we have counts for
12 papers
CriticGen: Generation-Aware Evaluation as Actionable Feedback
Huifang Du, Zecheng Zuo, Sen Wang +3
Current evaluation methods for large language models are coarse-grained and decoupled from generation, producing generic explanations that fail to provide actionable feedback for m…
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…
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…
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…
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…
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…
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…
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…
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.…
Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System
Yunfan Gao, Tao Sheng, Youlin Xiang +3
Large language models (LLMs) have demonstrated their significant potential to be applied for addressing various application tasks. However, traditional recommender systems continue…
ReCo: A Dataset for Residential Community Layout Planning
Xi Chen, Yun Xiong, Siqi Wang +4
Layout planning is centrally important in the field of architecture and urban design. Among the various basic units carrying urban functions, residential community plays a vital pa…