5 papers
Retrieval-augmented Prompt Learning for Pre-trained Foundation Models
Xiang Chen, Yixin Ou, Quan Feng +8
The pre-trained foundation models (PFMs) have become essential for facilitating large-scale multimodal learning. Researchers have effectively employed the ``pre-train, prompt, and…
AutoMind: Adaptive Knowledgeable Agent for Automated Data Science
Yixin Ou, Yujie Luo, Jingsheng Zheng +9
Large Language Model (LLM) agents have shown great potential in addressing real-world data science problems. LLM-driven data science agents promise to automate the entire machine l…
How Do LLMs Acquire New Knowledge? A Knowledge Circuits Perspective on Continual Pre-Training
Yixin Ou, Yunzhi Yao, Ningyu Zhang +5
Despite exceptional capabilities in knowledge-intensive tasks, Large Language Models (LLMs) face a critical gap in understanding how they internalize new knowledge, particularly ho…
KnowAgent: Knowledge-Augmented Planning for LLM-Based Agents
Yuqi Zhu, Shuofei Qiao, Yixin Ou +7
Large Language Models (LLMs) have demonstrated great potential in complex reasoning tasks, yet they fall short when tackling more sophisticated challenges, especially when interact…
LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities
Yuqi Zhu, Xiaohan Wang, Jing Chen +6
This paper presents an exhaustive quantitative and qualitative evaluation of Large Language Models (LLMs) for Knowledge Graph (KG) construction and reasoning. We engage in experime…