Feng Hong

According to our database, Feng Hong authored at least 21 papers between 2023 and 2026.

Collaborative distances:

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

2026

Focal Reward: Balanced Reinforcement Learning under Rubric-Based Rewards.

Yu Huang, Zihua Zhao, Zhaoxin Huan, Wanli Gu, Feng Hong, Xinmu Ge, Lin Yuan, Weichang Wu, Qiang Hu, Xiaolu Zhang, Jun Zhou, Jiangchao Yao

CoRR, May, 2026

Roll Out and Roll Back: Diffusion LLMs are Their Own Efficiency Teachers.

Fanqin Zeng, Feng Hong, Geng Yu, Huangjie Zheng, Xiaofeng Cao, Ya Zhang, Bo Han, Yanfeng Wang, Jiangchao Yao

CoRR, May, 2026

Dual-granularity Sinkhorn Distillation for Enhanced Learning from Long-Tailed Noisy Data.

Feng Hong, Yu Huang, Zihua Zhao, Zhihan Zhou, Jiangchao Yao, Dongsheng Li, Ya Zhang, Yanfeng Wang

Mach. Learn., March, 2026

Rejection Mixing: Fast Semantic Propagation of Mask Tokens for Efficient DLLM Inference.

Yushi Ye, Feng Hong, Huangjie Zheng, Xu Chen, Zhiyong Chen, Yanfeng Wang, Jiangchao Yao

CoRR, February, 2026

TriSpec: Ternary Speculative Decoding via Lightweight Proxy Verification.

Haoyun Jiang, Junqi He, Feng Hong, Xinlong Yang, Jianwei Zhang, Zheng Li, Zhengyang Zhuge, Zhiyong Chen, Bo Han, Junyang Lin, Jiangchao Yao

CoRR, January, 2026

2025

Innovator: Scientific Continued Pretraining with Fine-grained MoE Upcycling.

Ning Liao, Xiaoxing Wang, Zehao Lin, Weiyang Guo, Feng Hong, Shixiang Song, Geng Yu, Zihua Zhao, Sitao Xie, Longxuan Wei, Xiangqi Jin, Xiaohan Qin, Jiale Ma, Kai Chen, Jiangchao Yao, Zhouhan Lin, Junchi Yan, Zhiyu Li, Feiyu Xiong, Yanfeng Wang, Linfeng Zhang

CoRR, July, 2025

Wide-In, Narrow-Out: Revokable Decoding for Efficient and Effective DLLMs.

Feng Hong, Geng Yu, Yushi Ye, Haicheng Huang, Huangjie Zheng, Ya Zhang, Yanfeng Wang, Jiangchao Yao

CoRR, July, 2025

Uncover the balanced geometry in long-tailed contrastive language-image pretraining.

Zhihan Zhou, Yushi Ye, Feng Hong, Peisen Zhao, Jiangchao Yao, Ya Zhang, Qi Tian, Yanfeng Wang

Mach. Learn., April, 2025

Learning to Instruct for Visual Instruction Tuning.

Zhihan Zhou, Feng Hong, Jiaan Luo, Jiangchao Yao, Dongsheng Li, Bo Han, Ya Zhang, Yanfeng Wang

CoRR, March, 2025

Long-tailed Recognition with Model Rebalancing.

Jiaan Luo, Feng Hong, Qiang Hu, Xiaofeng Cao, Feng Liu, Jiangchao Yao

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Differential-Informed Sample Selection Accelerates Multimodal Contrastive Learning.

Zihua Zhao, Feng Hong, Mengxi Chen, Pengyi Chen, Benyuan Liu, Jiangchao Yao, Ya Zhang, Yanfeng Wang

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

2024

UniChest: Conquer-and-Divide Pre-Training for Multi-Source Chest X-Ray Classification.

Tianjie Dai, Ruipeng Zhang, Feng Hong, Jiangchao Yao, Ya Zhang, Yanfeng Wang

IEEE Trans. Medical Imaging, August, 2024

Balanced Destruction-Reconstruction Dynamics for Memory-Replay Class Incremental Learning.

Yuhang Zhou, Jiangchao Yao, Feng Hong, Ya Zhang, Yanfeng Wang

IEEE Trans. Image Process., 2024

Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge.

Gregory Holste, Yiliang Zhou, Song Wang, Ajay Jaiswal, Mingquan Lin, Sherry Zhuge, Yuzhe Yang, Dongkyun Kim, Trong-Hieu Nguyen Mau, Minh-Triet Tran, Jaehyup Jeong, Wongi Park, Jongbin Ryu, Feng Hong, Arsh Verma, Yosuke Yamagishi, Changhyun Kim, Hyeryeong Seo, Myungjoo Kang, Leo Anthony Celi, Zhiyong Lu, Ronald M. Summers, George Shih, Zhangyang Wang, Yifan Peng

Medical Image Anal., 2024

Revive Re-weighting in Imbalanced Learning by Density Ratio Estimation.

Jiaan Luo, Feng Hong, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Diversified Batch Selection for Training Acceleration.

Feng Hong, Yueming Lyu, Jiangchao Yao, Ya Zhang, Ivor W. Tsang, Yanfeng Wang

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

On Harmonizing Implicit Subpopulations.

Feng Hong, Jiangchao Yao, Yueming Lyu, Zhihan Zhou, Ivor W. Tsang, Ya Zhang, Yanfeng Wang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge.

Gregory Holste, Yiliang Zhou, Song Wang, Ajay Jaiswal, Mingquan Lin, Sherry Zhuge, Yuzhe Yang, Dongkyun Kim, Trong-Hieu Nguyen Mau, Minh-Triet Tran, Jaehyup Jeong, Wongi Park, Jongbin Ryu, Feng Hong, Arsh Verma, Yosuke Yamagishi, Changhyun Kim, Hyeryeong Seo, Myungjoo Kang, Leo Anthony Celi, Zhiyong Lu, Ronald M. Summers, George Shih, Zhangyang Wang, Yifan Peng

CoRR, 2023

Bag of Tricks for Long-Tailed Multi-Label Classification on Chest X-Rays.

Feng Hong, Tianjie Dai, Jiangchao Yao, Ya Zhang, Yanfeng Wang

CoRR, 2023

Combating Representation Learning Disparity with Geometric Harmonization.

Zhihan Zhou, Jiangchao Yao, Feng Hong, Ya Zhang, Bo Han, Yanfeng Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Long-Tailed Partial Label Learning via Dynamic Rebalancing.

Feng Hong, Jiangchao Yao, Zhihan Zhou, Ya Zhang, Yanfeng Wang

Proceedings of the Eleventh International Conference on Learning Representations, 2023