21 citations · 21 across the 6 of their papers we have counts for
6 papers
Meta-Reflection: A Feedback-Free Reflection Learning Framework
Yaoke Wang, Yun Zhu, Xintong Bao +7
Despite the remarkable capabilities of large language models (LLMs) in natural language understanding and reasoning, they often display undesirable behaviors, such as generating ha…
GraphCLIP: Enhancing Transferability in Graph Foundation Models for Text-Attributed Graphs
Yun Zhu, Haizhou Shi, Xiaotang Wang +5
Recently, research on Text-Attributed Graphs (TAGs) has gained significant attention due to the prevalence of free-text node features in real-world applications and the advancement…
Bridging Local Details and Global Context in Text-Attributed Graphs
Yaoke Wang, Yun Zhu, Wenqiao Zhang +3
Representation learning on text-attributed graphs (TAGs) is vital for real-world applications, as they combine semantic textual and contextual structural information. Research in t…
LASER: Tuning-Free LLM-Driven Attention Control for Efficient Text-conditioned Image-to-Animation
Haoyu Zheng, Wenqiao Zhang, Yaoke Wang +7
Revolutionary advancements in text-to-image models have unlocked new dimensions for sophisticated content creation, such as text-conditioned image editing, enabling the modificatio…
Efficient Tuning and Inference for Large Language Models on Textual Graphs
Yun Zhu, Yaoke Wang, Haizhou Shi +1
Rich textual and topological information of textual graphs need to be modeled in real-world applications such as webpages, e-commerce, and academic articles. Practitioners have bee…
GraphControl: Adding Conditional Control to Universal Graph Pre-trained Models for Graph Domain Transfer Learning
Yun Zhu, Yaoke Wang, Haizhou Shi +3
Graph-structured data is ubiquitous in the world which models complex relationships between objects, enabling various Web applications. Daily influxes of unlabeled graph data on th…