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zehanwang01 committed Oct 30, 2023
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10 changes: 9 additions & 1 deletion _pages/includes/pub.md
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- Large Language Model for 3D: **Chat-3D**
- 3D Visual Grounding: **3DRP-Net (EMNLP 2023)**, **Weakly supervised 3DVG (ICCV 2023)**

<div class='paper-box'><div class='paper-box-image'><div><div class="badge">Arxiv 2023</div><img src='images/Ex-MCR.png' alt="sym" width="100%"></div></div>
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- [Extending Multi-modal Contrastive Representations](https://arxiv.org/abs/2310.08884) **Zehan Wang**, Ziang Zhang, Luping Liu, Yang Zhao, Haifeng Huang, Tao Jin, Zhou Zhao **Arxiv, 2023**
- Learn unified multimodal contrastive representations for more than three modalities in a paired-data free and training-efficient way.
- **Academic / Industry Impact**: Our code and pre-trained models are released at [![](https://img.shields.io/github/stars/MCR-PEFT/Ex-MCR?style=social&label=Code+Stars)](https://github.com/MCR-PEFT/Ex-MCR), which provides state-of-the-art unified 3D-image-text-audio representations.
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<div class='paper-box'><div class='paper-box-image'><div><div class="badge">NeurIPS 2023</div><img src='images/C-MCR.png' alt="sym" width="100%"></div></div>
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- [Connecting Multi-modal Contrastive Representations](https://arxiv.org/abs/2305.14381) **Zehan Wang**, Yang Zhao, Xize Cheng, Haifeng Huang, Jiageng Liu, Li Tang, Linjun Li, Yongqi Wang, Aoxiong Yin, Ziang Zhang, Zhou Zhao **NeurIPS 2023**
- Paired-data free and training-efficient multi-modal constrastive representations learning method.
- **Academic / Industry Impact**: Our work is reported by [PaperWeekly](https://mp.weixin.qq.com/s/n4RUkRTQsCHg0O-qWDzD9g). Our code and pre-trained models are released at [![](https://img.shields.io/github/stars/MCR-PEFT/C-MCR?style=social&label=Code+Stars)](https://github.com/MCR-PEFT/C-MCR), which provides state-of-the-art audio-visual and 3D-language representations.

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# 💻 Internships & Projects
- August. 2023: Research Intern: Tencent TEG.
- Hosted by Hongfa Wang, Wei Liu.
<br />Hosted by Hongfa Wang, Wei Liu.
<br />Working on HunYuan Text-to-Video, Text-to-Audio Project.
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