Gongwei Chen

Orcid: 0000-0002-0634-6075

According to our database1, Gongwei Chen authored at least 16 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
Optimus-1: Hybrid Multimodal Memory Empowered Agents Excel in Long-Horizon Tasks.
CoRR, 2024

Token-level Correlation-guided Compression for Efficient Multimodal Document Understanding.
CoRR, 2024

MoME: Mixture of Multimodal Experts for Generalist Multimodal Large Language Models.
CoRR, 2024

Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL.
CoRR, 2024

Enhancing the Emotional Generation Capability of Large Language Models via Emotional Chain-of-Thought.
CoRR, 2024

2023
Composite Object Relation Modeling for Few-Shot Scene Recognition.
IEEE Trans. Image Process., 2023

LION : Empowering Multimodal Large Language Model with Dual-Level Visual Knowledge.
CoRR, 2023

2022
An Accurate and Efficient Large-Scale Regression Method Through Best Friend Clustering.
IEEE Trans. Parallel Distributed Syst., 2022

Amorphous Region Context Modeling for Scene Recognition.
IEEE Trans. Multim., 2022

2021
See More for Scene: Pairwise Consistency Learning for Scene Classification.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Learning Scene Attribute for Scene Recognition.
IEEE Trans. Multim., 2020

Image Representations With Spatial Object-to-Object Relations for RGB-D Scene Recognition.
IEEE Trans. Image Process., 2020

Scene Recognition With Prototype-Agnostic Scene Layout.
IEEE Trans. Image Process., 2020

2019
Deep Patch Representations with Shared Codebook for Scene Classification.
ACM Trans. Multim. Comput. Commun. Appl., 2019

MUCH: Mutual Coupling Enhancement of Scene Recognition and Dense Captioning.
Proceedings of the 27th ACM International Conference on Multimedia, 2019

Scene Recognition with Comprehensive Regions Graph Modeling.
Proceedings of the Image and Graphics - 10th International Conference, 2019


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