activity
20222025
most citedLLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities

37 citations · 80 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CL2025

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…

cs.CL2025

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…

cs.LG2025

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…

cs.CL2024★ 4 cited

Symbolic Learning Enables Self-Evolving Agents

Wangchunshu Zhou, Yixin Ou, Shengwei Ding +9

The AI community has been exploring a pathway to artificial general intelligence (AGI) by developing "language agents", which are complex large language models (LLMs) pipelines inv…

cs.CL2024★ 4 cited

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…

cs.CL2024★ 1 cited

EasyInstruct: An Easy-to-use Instruction Processing Framework for Large Language Models

Yixin Ou, Ningyu Zhang, Honghao Gui +9

In recent years, instruction tuning has gained increasing attention and emerged as a crucial technique to enhance the capabilities of Large Language Models (LLMs). To construct hig…

cs.CL2023★ 10 cited

OceanGPT: A Large Language Model for Ocean Science Tasks

Zhen Bi, Ningyu Zhang, Yida Xue +4

Ocean science, which delves into the oceans that are reservoirs of life and biodiversity, is of great significance given that oceans cover over 70% of our planet's surface. Recentl…

cs.CL2023★ 7 cited

Layout and Task Aware Instruction Prompt for Zero-shot Document Image Question Answering

Wenjin Wang, Yunhao Li, Yixin Ou +1

Layout-aware pre-trained models has achieved significant progress on document image question answering. They introduce extra learnable modules into existing language models to capt…

cs.CL2023★ 37 cited

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…

cs.CL2023★ 5 cited

A Concept Knowledge Graph for User Next Intent Prediction at Alipay

Yacheng He, Qianghuai Jia, Lin Yuan +3

This paper illustrates the technologies of user next intent prediction with a concept knowledge graph. The system has been deployed on the Web at Alipay, serving more than 100 mill…

cs.CL2022★ 12 cited

Reasoning with Language Model Prompting: A Survey

Shuofei Qiao, Yixin Ou, Ningyu Zhang +6

Reasoning, as an essential ability for complex problem-solving, can provide back-end support for various real-world applications, such as medical diagnosis, negotiation, etc. This…