Siteng Huang

Orcid: 0000-0002-9735-1186

According to our database1, Siteng Huang authored at least 14 papers between 2019 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
Cobra: Extending Mamba to Multi-Modal Large Language Model for Efficient Inference.
CoRR, 2024

Prompt-Based Distribution Alignment for Unsupervised Domain Adaptation.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Learning Disentangled Identifiers for Action-Customized Text-to-Image Generation.
CoRR, 2023

Check, Locate, Rectify: A Training-Free Layout Calibration System for Text-to-Image Generation.
CoRR, 2023

VGDiffZero: Text-to-image Diffusion Models Can Be Zero-shot Visual Grounders.
CoRR, 2023

Troika: Multi-Path Cross-Modal Traction for Compositional Zero-Shot Learning.
CoRR, 2023

Reference-Limited Compositional Zero-Shot Learning.
Proceedings of the 2023 ACM International Conference on Multimedia Retrieval, 2023

VoP: Text-Video Co-Operative Prompt Tuning for Cross-Modal Retrieval.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Domain Generalized Few-Shot Image Classification via Meta Regularization Network.
Proceedings of the IEEE International Conference on Acoustics, 2022

Tree Structure-Aware Few-Shot Image Classification via Hierarchical Aggregation.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
HINFShot: A Challenge Dataset for Few-Shot Node Classification in Heterogeneous Information Network.
Proceedings of the ICMR '21: International Conference on Multimedia Retrieval, 2021

Pareto Self-Supervised Training for Few-Shot Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Attributes-Guided and Pure-Visual Attention Alignment for Few-Shot Recognition.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019
DSANet: Dual Self-Attention Network for Multivariate Time Series Forecasting.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019


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