Search Results for author: Xuanwen Huang

Found 7 papers, 3 papers with code

An Expert is Worth One Token: Synergizing Multiple Expert LLMs as Generalist via Expert Token Routing

1 code implementation25 Mar 2024 Ziwei Chai, Guoyin Wang, Jing Su, Tianjie Zhang, Xuanwen Huang, Xuwu Wang, Jingjing Xu, Jianbo Yuan, Hongxia Yang, Fei Wu, Yang Yang

We present Expert-Token-Routing, a unified generalist framework that facilitates seamless integration of multiple expert LLMs.

Can GNN be Good Adapter for LLMs?

2 code implementations20 Feb 2024 Xuanwen Huang, Kaiqiao Han, Yang Yang, Dezheng Bao, Quanjin Tao, Ziwei Chai, Qi Zhu

In terms of efficiency, the GNN adapter introduces only a few trainable parameters and can be trained with low computation costs.

Node Classification Recommendation Systems +2

One Graph Model for Cross-domain Dynamic Link Prediction

no code implementations3 Feb 2024 Xuanwen Huang, Wei Chow, Yang Wang, Ziwei Chai, Chunping Wang, Lei Chen, Yang Yang

Extensive experiments on eight untrained graphs demonstrate that DyExpert achieves state-of-the-art performance in cross-domain link prediction.

Dynamic Link Prediction

GraphLLM: Boosting Graph Reasoning Ability of Large Language Model

1 code implementation9 Oct 2023 Ziwei Chai, Tianjie Zhang, Liang Wu, Kaiqiao Han, Xiaohai Hu, Xuanwen Huang, Yang Yang

This synergy equips LLMs with the ability to proficiently interpret and reason on graph data, harnessing the superior expressive power of graph learning models.

Graph Learning Language Modelling +1

How to Generate Popular Post Headlines on Social Media?

no code implementations18 Sep 2023 Zhouxiang Fang, Min Yu, Zhendong Fu, Boning Zhang, Xuanwen Huang, Xiaoqi Tang, Yang Yang

Observation results demonstrate that trends and personal styles are widespread in headlines on social medias and have significant contribution to posts's popularity.

Headline Generation

DGraph: A Large-Scale Financial Dataset for Graph Anomaly Detection

no code implementations30 Jun 2022 Xuanwen Huang, Yang Yang, Yang Wang, Chunping Wang, Zhisheng Zhang, Jiarong Xu, Lei Chen, Michalis Vazirgiannis

Since GAD emphasizes the application and the rarity of anomalous samples, enriching the varieties of its datasets is fundamental work.

Graph Anomaly Detection

Adaptive Hierarchical Graph Reasoning with Semantic Coherence for Video-and-Language Inference

no code implementations ICCV 2021 Juncheng Li, Siliang Tang, Linchao Zhu, Haochen Shi, Xuanwen Huang, Fei Wu, Yi Yang, Yueting Zhuang

Secondly, we introduce semantic coherence learning to explicitly encourage the semantic coherence of the adaptive hierarchical graph network from three hierarchies.

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