Qihang Zhao

Orcid: 0000-0002-7693-2870

According to our database1, Qihang Zhao authored at least 20 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Joint learning of structural and textual information on propagation network by graph attention networks for rumor detection.
Appl. Intell., February, 2024

SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks.
Trans. Mach. Learn. Res., 2024

dnaGrinder: a lightweight and high-capacity genomic foundation model.
CoRR, 2024

Redefining Information Retrieval of Structured Database via Large Language Models.
CoRR, 2024

Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence.
CoRR, 2024

Highly Accurate Disease Diagnosis and Highly Reproducible Biomarker Identification with PathFormer.
CoRR, 2024

2023
Towards popularity prediction of information cascades via degree distribution and deep neural networks.
J. Informetrics, August, 2023

Universal Normalization Enhanced Graph Representation Learning for Gene Network Prediction.
CoRR, 2023

RWKV: Reinventing RNNs for the Transformer Era.
CoRR, 2023

Both Efficiency and Effectiveness! A Large Scale Pre-ranking Framework in Search System.
CoRR, 2023

SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks.
CoRR, 2023

Uni-Match: A Semantic Unified Model for Query-Product Retrieval.
Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

2022
Utilizing citation network structure to predict paper citation counts: A Deep learning approach.
J. Informetrics, 2022

Predicting information diffusion via deep temporal convolutional networks.
Inf. Syst., 2022

AECasN: An information cascade predictor by learning the structural representation of the whole cascade network with autoencoder.
Expert Syst. Appl., 2022

TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural Networks.
CoRR, 2022

RESETBERT4Rec: A Pre-training Model Integrating Time And User Historical Behavior for Sequential Recommendation.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

2021
Prediction of information cascades via content and structure proximity preserved graph level embedding.
Inf. Sci., 2021

2020
On modeling and predicting popularity dynamics via integrating generative model and rich features.
Knowl. Based Syst., 2020

Utilizing Citation Network Structure to Predict Citation Counts: A Deep Learning Approach.
CoRR, 2020


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