no code implementations • ICLR 2019 • Zeyuan Chen, Shaoliang Nie, Tianfu Wu, Christopher G. Healey
Face completion is a challenging task with the difficulty level increasing significantly with respect to high resolution, the complexity of "holes" and the controllable attributes of filled-in fragments.
1 code implementation • 17 Mar 2024 • Guohao Sun, Can Qin, Jiamian Wang, Zeyuan Chen, ran Xu, Zhiqiang Tao
Recent advancements in the vision-language model have shown notable generalization in vision-language tasks after visual instruction tuning.
Ranked #38 on Visual Question Answering on MM-Vet
no code implementations • 11 Mar 2024 • Haiyang Xu, Yu Lei, Zeyuan Chen, Xiang Zhang, Yue Zhao, Yilin Wang, Zhuowen Tu
We present Bayesian Diffusion Models (BDM), a prediction algorithm that performs effective Bayesian inference by tightly coupling the top-down (prior) information with the bottom-up (data-driven) procedure via joint diffusion processes.
no code implementations • 18 Feb 2024 • Kun Ma, Cong Xu, Zeyuan Chen, Wei zhang
However, achieving both model transparency and recommendation performance simultaneously is challenging, especially for models that take the entire sequence of items as input without screening.
no code implementations • 3 Nov 2023 • Boyang Zhang, Xinyue Shen, Wai Man Si, Zeyang Sha, Zeyuan Chen, Ahmed Salem, Yun Shen, Michael Backes, Yang Zhang
Moderating offensive, hateful, and toxic language has always been an important but challenging topic in the domain of safe use in NLP.
no code implementations • 25 Oct 2023 • Yilin Wang, Zeyuan Chen, Liangjun Zhong, Zheng Ding, Zhizhou Sha, Zhuowen Tu
In this paper, we introduce a novel generative model, Diffusion Layout Transformers without Autoencoder (Dolfin), which significantly improves the modeling capability with reduced complexity compared to existing methods.
1 code implementation • 19 Aug 2023 • WenBo Hu, Yifan Xu, Yi Li, Weiyue Li, Zeyuan Chen, Zhuowen Tu
BLIVA demonstrates significant capability in decoding real-world images, irrespective of text presence.
2 code implementations • 11 Aug 2023 • Zhiwei Liu, Weiran Yao, JianGuo Zhang, Le Xue, Shelby Heinecke, Rithesh Murthy, Yihao Feng, Zeyuan Chen, Juan Carlos Niebles, Devansh Arpit, ran Xu, Phil Mui, Huan Wang, Caiming Xiong, Silvio Savarese
The massive successes of large language models (LLMs) encourage the emerging exploration of LLM-augmented Autonomous Agents (LAAs).
1 code implementation • 10 Aug 2023 • Zeyuan Chen, Wei Chen, Jia Xu, Zhongyi Liu, Wei zhang
Drawing inspiration from this, we devise a novel Behavior Augmented Relevance Learning model for Alipay Search (BARL-ASe) that leverages neighbor queries of target item and neighbor items of target query to complement target query-item semantic matching.
1 code implementation • 7 Aug 2023 • Xinyue Shen, Zeyuan Chen, Michael Backes, Yun Shen, Yang Zhang
The misuse of large language models (LLMs) has garnered significant attention from the general public and LLM vendors.
1 code implementation • 4 Aug 2023 • Weiran Yao, Shelby Heinecke, Juan Carlos Niebles, Zhiwei Liu, Yihao Feng, Le Xue, Rithesh Murthy, Zeyuan Chen, JianGuo Zhang, Devansh Arpit, ran Xu, Phil Mui, Huan Wang, Caiming Xiong, Silvio Savarese
This demonstrates that using policy gradient optimization to improve language agents, for which we believe our work is one of the first, seems promising and can be applied to optimize other models in the agent architecture to enhance agent performances over time.
no code implementations • 18 Jul 2023 • Rithesh Murthy, Shelby Heinecke, Juan Carlos Niebles, Zhiwei Liu, Le Xue, Weiran Yao, Yihao Feng, Zeyuan Chen, Akash Gokul, Devansh Arpit, ran Xu, Phil Mui, Huan Wang, Caiming Xiong, Silvio Savarese
In this paper, we propose an enhanced approach for Rapid Exploration and eXploitation for AI Agents called REX.
no code implementations • 18 Apr 2023 • Xinyue Shen, Zeyuan Chen, Michael Backes, Yang Zhang
In this paper, we perform the first large-scale measurement of ChatGPT's reliability in the generic QA scenario with a carefully curated set of 5, 695 questions across ten datasets and eight domains.
2 code implementations • 26 Mar 2023 • Xinlei He, Xinyue Shen, Zeyuan Chen, Michael Backes, Yang Zhang
Extensive evaluations on public datasets with curated texts generated by various powerful LLMs such as ChatGPT-turbo and Claude demonstrate the effectiveness of different detection methods.
1 code implementation • ICCV 2023 • Can Qin, Ning Yu, Chen Xing, Shu Zhang, Zeyuan Chen, Stefano Ermon, Yun Fu, Caiming Xiong, ran Xu
Empirical results show that GlueNet can be trained efficiently and enables various capabilities beyond previous state-of-the-art models: 1) multilingual language models such as XLM-Roberta can be aligned with existing T2I models, allowing for the generation of high-quality images from captions beyond English; 2) GlueNet can align multi-modal encoders such as AudioCLIP with the Stable Diffusion model, enabling sound-to-image generation; 3) it can also upgrade the current text encoder of the latent diffusion model for challenging case generation.
1 code implementation • 16 Mar 2023 • Shu Zhang, Xinyi Yang, Yihao Feng, Can Qin, Chia-Chih Chen, Ning Yu, Zeyuan Chen, Huan Wang, Silvio Savarese, Stefano Ermon, Caiming Xiong, ran Xu
Incorporating human feedback has been shown to be crucial to align text generated by large language models to human preferences.
1 code implementation • ICCV 2023 • Xiang Zhang, Zeyuan Chen, Fangyin Wei, Zhuowen Tu
Performing holistic 3D scene understanding from a single-view observation, involving generating instance shapes and 3D scene segmentation, is a long-standing challenge.
1 code implementation • 19 Dec 2022 • Ning Yu, Chia-Chih Chen, Zeyuan Chen, Rui Meng, Gang Wu, Paul Josel, Juan Carlos Niebles, Caiming Xiong, ran Xu
Graphic layout designs play an essential role in visual communication.
1 code implementation • 6 Dec 2022 • Yutong Dai, Zeyuan Chen, Junnan Li, Shelby Heinecke, Lichao Sun, ran Xu
We propose FedNH, a novel method that improves the local models' performance for both personalization and generalization by combining the uniformity and semantics of class prototypes.
no code implementations • 4 Nov 2022 • Yuefan Wu, Zeyuan Chen, Shaowei Liu, Zhongzheng Ren, Shenlong Wang
Recovering the skeletal shape of an animal from a monocular video is a longstanding challenge.
1 code implementation • CVPR 2022 • Zeyuan Chen, Yinbo Chen, Jingwen Liu, Xingqian Xu, Vidit Goel, Zhangyang Wang, Humphrey Shi, Xiaolong Wang
The learned implicit neural representation can be decoded to videos of arbitrary spatial resolution and frame rate.
Space-time Video Super-resolution Video Frame Interpolation +1
1 code implementation • 27 Apr 2022 • Zeyuan Chen, He Wang, Xiangyu Zhu, Haiyan Wu, Congcong Gu, Shumeng Liu, Jinchao Huang, Wei zhang
The proposed solution of our team WSDM_Coggle_ is selected as the second place submission.
no code implementations • 8 Dec 2021 • Luyu Yang, Mingfei Gao, Zeyuan Chen, ran Xu, Abhinav Shrivastava, Chetan Ramaiah
In the context of online privacy, many methods propose complex privacy and security preserving measures to protect sensitive data.
2 code implementations • SpaNLP (ACL) 2022 • Mingfei Gao, Zeyuan Chen, Nikhil Naik, Kazuma Hashimoto, Caiming Xiong, ran Xu
We propose a novel framework to conduct field extraction from forms with unlabeled data.
1 code implementation • 8 Oct 2021 • Le Xue, Mingfei Gao, Zeyuan Chen, Caiming Xiong, ran Xu
We propose a novel framework to evaluate the robustness of transformer-based form field extraction methods via form attacks.
no code implementations • 25 Sep 2021 • Zeyuan Chen, Jiangchao Yao, Feng Wang, Kunyang Jia, Bo Han, Wei zhang, Hongxia Yang
With the hardware development of mobile devices, it is possible to build the recommendation models on the mobile side to utilize the fine-grained features and the real-time feedbacks.
1 code implementation • 24 Sep 2021 • Zeyuan Chen, Wei zhang, Junchi Yan, Gang Wang, Jianyong Wang
Sequential Recommendation aims to recommend items that a target user will interact with in the near future based on the historically interacted items.
1 code implementation • 1 Aug 2021 • Zeyuan Chen, Yifan Jiang, Dong Liu, Zhangyang Wang
We present \underline{C}oordinated \underline{E}nhancement for \underline{R}eal-world \underline{L}ow-light Noisy Images (CERL), that seamlessly integrates light enhancement and noise suppression parts into a unified and physics-grounded optimization framework.
1 code implementation • CVPR 2021 • Zeyuan Chen, Yangchao Wang, Yang Yang, Dong Liu
Deep learning-based methods have achieved remarkable performance for image dehazing.
no code implementations • 5 Mar 2021 • Wei zhang, Zeyuan Chen, Chao Dong, Wen Wang, Hongyuan Zha, Jianyong Wang
However, they encounter two main limitations: (1) Correlations between answers in the same question are often overlooked.
no code implementations • 25 Sep 2019 • Zeyuan Chen, Shaoliang Nie, Tianfu Wu, Christopher G. Healey
The proposed frequency-oriented attentive module (FOAM) encourages GANs to attend to only finer details in the coarse-to-fine progressive training, thus enabling progressive attention to face structures.
no code implementations • 23 Jan 2018 • Zeyuan Chen, Shaoliang Nie, Tianfu Wu, Christopher G. Healey
It is a challenging task with the difficulty level increasing significantly with respect to high resolution, the complexity of "holes" and the controllable attributes of filled-in fragments.