Yi-Feng Wu

According to our database1, Yi-Feng Wu authored at least 13 papers between 2018 and 2025.

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

2025
Ovis2.5 Technical Report.
CoRR, August, 2025

LPO: Towards Accurate GUI Agent Interaction via Location Preference Optimization.
CoRR, June, 2025

VoiceTalk: A No-Code Approach for Creating Voice-Controlled Smart Home Applications.
IEEE Open J. Comput. Soc., 2025

2024
Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

TAI++: Text as Image for Multi-Label Image Classification by Co-Learning Transferable Prompt.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

2023
Overview of Geriatric Trauma in an Urban Trauma Center in Eastern China: Implications from Computational Intelligence for Localized Trauma-Specific Frailty Index System Design.
Int. J. Comput. Intell. Syst., December, 2023

2021
Semi-Supervised Multi-Modal Clustering and Classification with Incomplete Modalities.
IEEE Trans. Knowl. Data Eng., 2021

2020
A semi-supervised attention model for identifying authentic sneakers.
Big Data Min. Anal., 2020

2019
Deep Robust Unsupervised Multi-Modal Network.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Deep Multi-modal Learning with Cascade Consensus.
Proceedings of the PRICAI 2018: Trends in Artificial Intelligence, 2018

Multi-network User Identification via Graph-Aware Embedding.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Complex Object Classification: A Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

DMTMV: A Unified Learning Framework for Deep Multi-task Multi-view Learning.
Proceedings of the 2018 IEEE International Conference on Big Knowledge, 2018


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