13 citations · 31 across the 17 of their papers we have counts for
8 papers · 1 filter
Software World Models: From Consequence Prediction to Decision Value
Tongli Su, Yuntong Hu, Liang Zhao +3
A coding agent may safely modify one repository while silently breaking downstream services, libraries, or datastores that depend on it. Exhaustively running integration tests afte…
Multimodal Representation Learning Conditioned on Semantic Relations
Yang Qiao, Yuntong Hu, Bowen Zhu +2
Multimodal representation learning has been largely driven by contrastive models such as CLIP, which learn a shared embedding space by aligning paired image-text samples. While eff…
Network Tomography with Path-Centric Graph Neural Network
Yuntong Hu, Junxiang Wang, Liang Zhao
Network tomography is a crucial problem in network monitoring, where the observable path performance metric values are used to infer the unobserved ones, making it essential for ta…
Transferable Unsupervised Outlier Detection Framework for Human Semantic Trajectories
Zheng Zhang, Hossein Amiri, Dazhou Yu +3
Semantic trajectories, which enrich spatial-temporal data with textual information such as trip purposes or location activities, are key for identifying outlier behaviors critical…
GraphNarrator: Generating Textual Explanations for Graph Neural Networks
Bo Pan, Zhen Xiong, Guanchen Wu +3
Graph representation learning has garnered significant attention due to its broad applications in various domains, such as recommendation systems and social network analysis. Despi…
TAGA: Text-Attributed Graph Self-Supervised Learning by Synergizing Graph and Text Mutual Transformations
Zheng Zhang, Yuntong Hu, Bo Pan +2
Text-Attributed Graphs (TAGs) enhance graph structures with natural language descriptions, enabling detailed representation of data and their relationships across a broad spectrum…
GRAG: Graph Retrieval-Augmented Generation
Yuntong Hu, Zhihan Lei, Zheng Zhang +3
Naive Retrieval-Augmented Generation (RAG) focuses on individual documents during retrieval and, as a result, falls short in handling networked documents which are very popular in…
Beyond Text: A Deep Dive into Large Language Models' Ability on Understanding Graph Data
Yuntong Hu, Zheng Zhang, Liang Zhao
Large language models (LLMs) have achieved impressive performance on many natural language processing tasks. However, their capabilities on graph-structured data remain relatively…