Hao Chen

According to our database, Hao Chen authored at least 41 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A Survey on Evaluation of Large Language Models.

Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, Wei Ye, Yue Zhang, Yi Chang, Philip S. Yu, Qiang Yang, Xing Xie

ACM Trans. Intell. Syst. Technol., June, 2024

Exploring Vision-Language Models for Imbalanced Learning.

Yidong Wang, Zhuohao Yu, Jindong Wang, Qiang Heng, Hao Chen, Wei Ye, Rui Xie, Xing Xie, Shikun Zhang

Int. J. Comput. Vis., January, 2024

PromptBench: A Unified Library for Evaluation of Large Language Models.

Kaijie Zhu, Qinlin Zhao, Hao Chen, Jindong Wang, Xing Xie

J. Mach. Learn. Res., 2024

On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective.

Jindong Wang, Xixu Hu, Wenxin Hou, Hao Chen, Runkai Zheng, Yidong Wang, Linyi Yang, Wei Ye, Haojun Huang, Xiubo Geng, Binxing Jiao, Yue Zhang, Xing Xie

IEEE Data Eng. Bull., 2024

SoftVQ-VAE: Efficient 1-Dimensional Continuous Tokenizer.

Hao Chen, Ze Wang, Xiang Li, Ximeng Sun, Fangyi Chen, Jiang Liu, Jindong Wang, Bhiksha Raj, Zicheng Liu, Emad Barsoum

CoRR, 2024

XQ-GAN: An Open-source Image Tokenization Framework for Autoregressive Generation.

Xiang Li, Kai Qiu, Hao Chen, Jason Kuen, Jiuxiang Gu, Jindong Wang, Zhe Lin, Bhiksha Raj

CoRR, 2024

On the Diversity of Synthetic Data and its Impact on Training Large Language Models.

Hao Chen, Abdul Waheed, Xiang Li, Yidong Wang, Jindong Wang, Bhiksha Raj, Marah I Abdin

CoRR, 2024

ImageFolder: Autoregressive Image Generation with Folded Tokens.

Xiang Li, Kai Qiu, Hao Chen, Jason Kuen, Jiuxiang Gu, Bhiksha Raj, Zhe Lin

CoRR, 2024

Efficient Autoregressive Audio Modeling via Next-Scale Prediction.

Kai Qiu, Xiang Li, Hao Chen, Jie Sun, Jinglu Wang, Zhe Lin, Marios Savvides, Bhiksha Raj

CoRR, 2024

ControlVAR: Exploring Controllable Visual Autoregressive Modeling.

Xiang Li, Kai Qiu, Hao Chen, Jason Kuen, Zhe Lin, Rita Singh, Bhiksha Raj

CoRR, 2024

Slight Corruption in Pre-training Data Makes Better Diffusion Models.

Hao Chen, Yujin Han, Diganta Misra, Xiang Li, Kai Hu, Difan Zou, Masashi Sugiyama, Jindong Wang, Bhiksha Raj

CoRR, 2024

RTGen: Generating Region-Text Pairs for Open-Vocabulary Object Detection.

Fangyi Chen, Han Zhang, Zhantao Yang, Hao Chen, Kai Hu, Marios Savvides

CoRR, 2024

Learning with Noisy Foundation Models.

Hao Chen, Jindong Wang, Zihan Wang, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj

CoRR, 2024

On Catastrophic Inheritance of Large Foundation Models.

Hao Chen, Bhiksha Raj, Xing Xie, Jindong Wang

CoRR, 2024

PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts.

Kaijie Zhu, Jindong Wang, Jiaheng Zhou, Zichen Wang, Hao Chen, Yidong Wang, Linyi Yang, Wei Ye, Yue Zhang, Neil Gong, Xing Xie

Proceedings of the 1st ACM Workshop on Large AI Systems and Models with Privacy and Safety Analysis, 2024

CompeteAI: Understanding the Competition Dynamics of Large Language Model-based Agents.

Qinlin Zhao, Jindong Wang, Yixuan Zhang, Yiqiao Jin, Kaijie Zhu, Hao Chen, Xing Xie

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Completing Visual Objects via Bridging Generation and Segmentation.

Xiang Li, Yinpeng Chen, Chung-Ching Lin, Hao Chen, Kai Hu, Rita Singh, Bhiksha Raj, Lijuan Wang, Zicheng Liu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

A General Framework for Learning from Weak Supervision.

Hao Chen, Jindong Wang, Lei Feng, Xiang Li, Yidong Wang, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj

Proceedings of the Forty-first International Conference on Machine Learning, 2024

PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization.

Yidong Wang, Zhuohao Yu, Wenjin Yao, Zhengran Zeng, Linyi Yang, Cunxiang Wang, Hao Chen, Chaoya Jiang, Rui Xie, Jindong Wang, Xing Xie, Wei Ye, Shikun Zhang, Yue Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks.

Hao Chen, Jindong Wang, Ankit Shah, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj

Proceedings of the Twelfth International Conference on Learning Representations, 2024

AgentReview: Exploring Peer Review Dynamics with LLM Agents.

Yiqiao Jin, Qinlin Zhao, Yiyang Wang, Hao Chen, Kaijie Zhu, Yijia Xiao, Jindong Wang

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

R²-Bench: Benchmarking the Robustness of Referring Perception Models Under Perturbations.

Xiang Li, Kai Qiu, Jinglu Wang, Xiaohao Xu, Rita Singh, Kashu Yamazaki, Hao Chen, Xiaonan Huang, Bhiksha Raj

Proceedings of the Computer Vision - ECCV 2024, 2024

Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets.

Hao Chen, Ran Tao, Han Zhang, Yidong Wang, Xiang Li, Wei Ye, Jindong Wang, Guosheng Hu, Marios Savvides

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

CompeteAI: Understanding the Competition Behaviors in Large Language Model-based Agents.

Qinlin Zhao, Jindong Wang, Yixuan Zhang, Yiqiao Jin, Kaijie Zhu, Hao Chen, Xing Xie

CoRR, 2023

PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization.

Yidong Wang, Zhuohao Yu, Zhengran Zeng, Linyi Yang, Cunxiang Wang, Hao Chen, Chaoya Jiang, Rui Xie, Jindong Wang, Xing Xie, Wei Ye, Shikun Zhang, Yue Zhang

CoRR, 2023

PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts.

Kaijie Zhu, Jindong Wang, Jiaheng Zhou, Zichen Wang, Hao Chen, Yidong Wang, Linyi Yang, Wei Ye, Neil Zhenqiang Gong, Yue Zhang, Xing Xie

CoRR, 2023

Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations.

Hao Chen, Ankit Shah, Jindong Wang, Ran Tao, Yidong Wang, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj

CoRR, 2023

SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning.

Hao Chen, Ran Tao, Yue Fan, Yidong Wang, Jindong Wang, Bernt Schiele, Xing Xie, Bhiksha Raj, Marios Savvides

CoRR, 2023

FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning.

Yidong Wang, Hao Chen, Qiang Heng, Wenxin Hou, Yue Fan, Zhen Wu, Jindong Wang, Marios Savvides, Takahiro Shinozaki, Bhiksha Raj, Bernt Schiele, Xing Xie

Proceedings of the Eleventh International Conference on Learning Representations, 2023

SoftMatch: Addressing the Quantity-Quality Tradeoff in Semi-supervised Learning.

Hao Chen, Ran Tao, Yue Fan, Yidong Wang, Jindong Wang, Bernt Schiele, Xing Xie, Bhiksha Raj, Marios Savvides

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Boosting Transductive Few-Shot Fine-tuning with Margin-based Uncertainty Weighting and Probability Regularization.

Ran Tao, Hao Chen, Marios Savvides

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

3D Human Pose, Shape and Texture From Low-Resolution Images and Videos.

Xiangyu Xu, Hao Chen, Francesc Moreno-Noguer, László A. Jeni, Fernando De la Torre

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets.

Hao Chen, Ran Tao, Han Zhang, Yidong Wang, Wei Ye, Jindong Wang, Guosheng Hu, Marios Savvides

CoRR, 2022

USB: A Unified Semi-supervised Learning Benchmark.

Yidong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wenxin Hou, Renjie Wang, Linyi Yang, Zhi Zhou, Lan-Zhe Guo, Heli Qi, Zhen Wu, Yufeng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jindong Wang, Xing Xie, Yue Zhang

CoRR, 2022

FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning.

Yidong Wang, Hao Chen, Qiang Heng, Wenxin Hou, Yue Fan, Zhen Wu, Marios Savvides, Takahiro Shinozaki, Bhiksha Raj, Bernt Schiele

CoRR, 2022

USB: A Unified Semi-supervised Learning Benchmark for Classification.

Yidong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wenxin Hou, Renjie Wang, Linyi Yang, Zhi Zhou, Lan-Zhe Guo, Heli Qi, Zhen Wu, Yufeng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jindong Wang, Xing Xie, Yue Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Unitail: Detecting, Reading, and Matching in Retail Scene.

Fangyi Chen, Han Zhang, Zaiwang Li, Jiachen Dou, Shentong Mo, Hao Chen, Yongxin Zhang, Uzair Ahmed, Chenchen Zhu, Marios Savvides

Proceedings of the Computer Vision - ECCV 2022, 2022

2020

3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised Learning.

Xiangyu Xu, Hao Chen, Francesc Moreno-Noguer, László A. Jeni, Fernando De la Torre

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Blind Inpainting of Large-scale Masks of Thin Structures with Adversarial and Reinforcement Learning.

Hao Chen, Mario Valerio Giuffrida, Peter Doerner, Sotirios A. Tsaftaris

CoRR, 2019

Adversarial Large-Scale Root Gap Inpainting.

Hao Chen, Mario Valerio Giuffrida, Peter Doerner, Sotirios A. Tsaftaris

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018

Root Gap Correction with a Deep Inpainting Model.

Hao Chen, Mario Valerio Giuffrida, Sotirios A. Tsaftaris, Peter Doerner

Proceedings of the British Machine Vision Conference 2018, 2018