Lu Hou - RankMe

88 papers A* 18Journal 52Unranked 18

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	CTRL: Connect Collaborative and Language Model for CTR Prediction. Trans. Recomm. Syst. Xiangyang Li, Bo Chen, Lu Hou, Ruiming Tang
2026	J	`jnl`	The Synergy Dilemma of Long-CoT SFT and RL: Investigating Post-Training Techniques for Reasoning VLMs. Trans. Mach. Learn. Res. Jierun Chen, Tiezheng Yu, Haoli Bai, Lewei Yao, Jiannan Wu, Kaican Li, Fei Mi, Chaofan Tao, Lei Zhu, Manyi Zhang, Xiao-Hui Li, Lu Hou, Lifeng Shang, Qun Liu
2026	J	`jnl`	What Makes Low-Bit Quantization-Aware Training Work for Reasoning LLMs? A Systematic Study. CoRR Keyu Lv, Manyi Zhang, Xiaobo Xia, Jingchen Ni, Shannan Yan, Xianzhi Yu, Lu Hou, Chun Yuan, Haoli Bai
2025	J	`jnl`	A Simple Linear Patch Revives Layer-Pruned Large Language Models. CoRR Xinrui Chen, Haoli Bai, Tao Yuan, Ruikang Liu, Kang Zhao, Xianzhi Yu, Lu Hou, Tian Guan, Yonghong He, Chun Yuan
2025	J	`jnl`	DrivePI: Spatial-aware 4D MLLM for Unified Autonomous Driving Understanding, Perception, Prediction and Planning. CoRR Zhe Liu, Runhui Huang, Rui Yang, Siming Yan, Zining Wang, Lu Hou, Di Lin, Xiang Bai, Hengshuang Zhao
2025	J	`jnl`	E CoRR Tao Yuan, Haoli Bai, Yinfei Pan, Xuyang Cao, Tianyu Zhang, Lu Hou, Ting Hu, Xianzhi Yu
2025	A*	`conf`	EMOVA: Empowering Language Models to See, Hear and Speak with Vivid Emotions. CVPR Kai Chen, Yunhao Gou, Runhui Huang, Zhili Liu, Daxin Tan, Jing Xu, Chunwei Wang, Yi Zhu, Yihan Zeng, Kuo Yang, Dingdong Wang, Kun Xiang, Haoyuan Li, Haoli Bai, Jianhua Han, Xiaohui Li, Weike Jin, Nian Xie, Yu Zhang, James T. Kwok, Hengshuang Zhao, Xiaodan Liang, Dit-Yan Yeung, Xiao Chen, Zhenguo Li, Wei Zhang, Qun Liu, Lanqing Hong, Lu Hou, Hang Xu
2025	—	`conf`	Efficient Inference for Large Language Models -Algorithm, Model, and System. EMNLP (Tutorial Abstracts) Xuefei Ning, Guohao Dai, Haoli Bai, Lu Hou, Yu Wang, Qun Liu
2025	—	`conf`	Faster and Better LLMs via Latency-Aware Test-Time Scaling. EMNLP (Findings) Zili Wang, Tianyu Zhang, Haoli Bai, Lu Hou, Xianzhi Yu, Wulong Liu, Shiming Xiang, Lei Zhu
2025	J	`jnl`	Faster and Better LLMs via Latency-Aware Test-Time Scaling. CoRR Zili Wang, Tianyu Zhang, Lei Zhu, Haoli Bai, Lu Hou, Shiming Xiang, Xianzhi Yu, Wulong Liu
2025	A*	`conf`	FlatQuant: Flatness Matters for LLM Quantization. ICML Yuxuan Sun, Ruikang Liu, Haoli Bai, Han Bao, Kang Zhao, Yuening Li, Jiaxin Hu, Xianzhi Yu, Lu Hou, Chun Yuan, Xin Jiang, Wulong Liu, Jun Yao
2025	J	`jnl`	Fourier-VLM: Compressing Vision Tokens in the Frequency Domain for Large Vision-Language Models. CoRR Huanyu Wang, Jushi Kai, Haoli Bai, Lu Hou, Bo Jiang, Ziwei He, Zhouhan Lin
2025	A*	`conf`	HiRes-LLaVA: Restoring Fragmentation Input in High-Resolution Large Vision-Language Models. CVPR Runhui Huang, Xinpeng Ding, Chunwei Wang, Jianhua Han, Yulong Liu, Hengshuang Zhao, Hang Xu, Lu Hou, Wei Zhang, Xiaodan Liang
2025	J	`jnl`	ILLUME+: Illuminating Unified MLLM with Dual Visual Tokenization and Diffusion Refinement. CoRR Runhui Huang, Chunwei Wang, Junwei Yang, Guansong Lu, Yunlong Yuan, Jianhua Han, Lu Hou, Wei Zhang, Lanqing Hong, Hengshuang Zhao, Hang Xu
2025	J	`jnl`	InSight-o3: Empowering Multimodal Foundation Models with Generalized Visual Search. CoRR Kaican Li, Lewei Yao, Jiannan Wu, Tiezheng Yu, Jierun Chen, Haoli Bai, Lu Hou, Lanqing Hong, Wei Zhang, Nevin L. Zhang
2025	J	`jnl`	Pre-Trained Models for Search and Recommendation: Introduction to the Special Issue - Part 1. ACM Trans. Inf. Syst. Wenjie Wang, Zheng Liu, Fuli Feng, Zhicheng Dou, Qingyao Ai, Grace Hui Yang, Defu Lian, Lu Hou, Aixin Sun, Hamed Zamani, Donald Metzler, Maarten de Rijke
2025	J	`jnl`	Pre-Trained Models for Search and Recommendation: Introduction to the Special Issue - Part 2. ACM Trans. Inf. Syst. Wenjie Wang, Zheng Liu, Fuli Feng, Zhicheng Dou, Qingyao Ai, Grace Hui Yang, Defu Lian, Lu Hou, Aixin Sun, Hamed Zamani, Donald Metzler, Maarten de Rijke
2025	J	`jnl`	Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models. CoRR Ruikang Liu, Yuxuan Sun, Manyi Zhang, Haoli Bai, Xianzhi Yu, Tiezheng Yu, Chun Yuan, Lu Hou
2025	J	`jnl`	The Synergy Dilemma of Long-CoT SFT and RL: Investigating Post-Training Techniques for Reasoning VLMs. CoRR Jierun Chen, Tiezheng Yu, Haoli Bai, Lewei Yao, Jiannan Wu, Kaican Li, Fei Mi, Chaofan Tao, Lei Zhu, Manyi Zhang, Xiaohui Li, Lu Hou, Lifeng Shang, Qun Liu
2025	J	`jnl`	Think Before You Talk: Enhancing Meaningful Dialogue Generation in Full-Duplex Speech Language Models with Planning-Inspired Text Guidance. CoRR Wenqian Cui, Lei Zhu, Xiaohui Li, Zhihan Guo, Haoli Bai, Lu Hou, Irwin King
2025	J	`jnl`	Unifying Multimodal Large Language Model Capabilities and Modalities via Model Merging. CoRR Yongxian Wei, Runxi Cheng, Weike Jin, Enneng Yang, Li Shen, Lu Hou, Sinan Du, Chun Yuan, Xiaochun Cao, Dacheng Tao
2024	J	`jnl`	DeCo: Decoupling Token Compression from Semantic Abstraction in Multimodal Large Language Models. CoRR Linli Yao, Lei Li, Shuhuai Ren, Lean Wang, Yuanxin Liu, Xu Sun, Lu Hou
2024	J	`jnl`	EMOVA: Empowering Language Models to See, Hear and Speak with Vivid Emotions. CoRR Kai Chen, Yunhao Gou, Runhui Huang, Zhili Liu, Daxin Tan, Jing Xu, Chunwei Wang, Yi Zhu, Yihan Zeng, Kuo Yang, Dingdong Wang, Kun Xiang, Haoyuan Li, Haoli Bai, Jianhua Han, Xiaohui Li, Weike Jin, Nian Xie, Yu Zhang, James T. Kwok, Hengshuang Zhao, Xiaodan Liang, Dit-Yan Yeung, Xiao Chen, Zhenguo Li, Wei Zhang, Qun Liu, Jun Yao, Lanqing Hong, Lu Hou, Hang Xu
2024	J	`jnl`	Embedding Compression in Recommender Systems: A Survey. CoRR Shiwei Li, Huifeng Guo, Xing Tang, Ruiming Tang, Lu Hou, Ruixuan Li, Rui Zhang
2024	J	`jnl`	Embedding Compression in Recommender Systems: A Survey. ACM Comput. Surv. Shiwei Li, Huifeng Guo, Xing Tang, Ruiming Tang, Lu Hou, Ruixuan Li, Rui Zhang
2024	J	`jnl`	FastAttention: Extend FlashAttention2 to NPUs and Low-resource GPUs. CoRR Haoran Lin, Xianzhi Yu, Kang Zhao, Lu Hou, Zongyuan Zhan, Stanislav Kamenev, Han Bao, Ting Hu, Mingkai Wang, Qixin Chang, Siyue Sui, Weihao Sun, Jiaxin Hu, Jun Yao, Zekun Yin, Cheng Qian, Ying Zhang, Yinfei Pan, Yu Yang, Weiguo Liu
2024	J	`jnl`	FlatQuant: Flatness Matters for LLM Quantization. CoRR Yuxuan Sun, Ruikang Liu, Haoli Bai, Han Bao, Kang Zhao, Yuening Li, Jiaxin Hu, Xianzhi Yu, Lu Hou, Chun Yuan, Xin Jiang, Wulong Liu, Jun Yao
2024	J	`jnl`	HiRes-LLaVA: Restoring Fragmentation Input in High-Resolution Large Vision-Language Models. CoRR Runhui Huang, Xinpeng Ding, Chunwei Wang, Jianhua Han, Yulong Liu, Hengshuang Zhao, Hang Xu, Lu Hou, Wei Zhang, Xiaodan Liang
2024	J	`jnl`	ILLUME: Illuminating Your LLMs to See, Draw, and Self-Enhance. CoRR Chunwei Wang, Guansong Lu, Junwei Yang, Runhui Huang, Jianhua Han, Lu Hou, Wei Zhang, Hang Xu
2024	—	`conf`	IntactKV: Improving Large Language Model Quantization by Keeping Pivot Tokens Intact. ACL (Findings) Ruikang Liu, Haoli Bai, Haokun Lin, Yuening Li, Han Gao, Zhengzhuo Xu, Lu Hou, Jun Yao, Chun Yuan
2024	J	`jnl`	IntactKV: Improving Large Language Model Quantization by Keeping Pivot Tokens Intact. CoRR Ruikang Liu, Haoli Bai, Haokun Lin, Yuening Li, Han Gao, Zhengzhuo Xu, Lu Hou, Jun Yao, Chun Yuan
2024	A*	`conf`	MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-Wise Pruning Error Metric. CVPR Haokun Lin, Haoli Bai, Zhili Liu, Lu Hou, Muyi Sun, Linqi Song, Ying Wei, Zhenan Sun
2024	J	`jnl`	MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-wise Pruning Error Metric. CoRR Haokun Lin, Haoli Bai, Zhili Liu, Lu Hou, Muyi Sun, Linqi Song, Ying Wei, Zhenan Sun
2024	A*	`conf`	Plug-and-Play: An Efficient Post-training Pruning Method for Large Language Models. ICLR Yingtao Zhang, Haoli Bai, Haokun Lin, Jialin Zhao, Lu Hou, Carlo Vittorio Cannistraci
2024	J	`jnl`	Power Law in Deep Neural Networks: Sparse Network Generation and Continual Learning With Preferential Attachment. IEEE Trans. Neural Networks Learn. Syst. Fan Feng, Lu Hou, Qi She, Rosa H. M. Chan, James T. Kwok
2024	—	`conf`	TempCompass: Do Video LLMs Really Understand Videos? ACL (Findings) Yuanxin Liu, Shicheng Li, Yi Liu, Yuxiang Wang, Shuhuai Ren, Lei Li, Sishuo Chen, Xu Sun, Lu Hou
2024	J	`jnl`	TempCompass: Do Video LLMs Really Understand Videos? CoRR Yuanxin Liu, Shicheng Li, Yi Liu, Yuxiang Wang, Shuhuai Ren, Lei Li, Sishuo Chen, Xu Sun, Lu Hou
2024	A*	`conf`	TimeChat: A Time-sensitive Multimodal Large Language Model for Long Video Understanding. CVPR Shuhuai Ren, Linli Yao, Shicheng Li, Xu Sun, Lu Hou
2024	J	`jnl`	Towards Multimodal Video Paragraph Captioning Models Robust to Missing Modality. CoRR Sishuo Chen, Lei Li, Shuhuai Ren, Rundong Gao, Yuanxin Liu, Xiaohan Bi, Xu Sun, Lu Hou
2024	A*	`conf`	UNIT: Unifying Image and Text Recognition in One Vision Encoder. NeurIPS Yi Zhu, Yanpeng Zhou, Chunwei Wang, Yang Cao, Jianhua Han, Lu Hou, Hang Xu
2024	J	`jnl`	UNIT: Unifying Image and Text Recognition in One Vision Encoder. CoRR Yi Zhu, Yanpeng Zhou, Chunwei Wang, Yang Cao, Jianhua Han, Lu Hou, Hang Xu
2024	—	`conf`	VITATECS: A Diagnostic Dataset for Temporal Concept Understanding of Video-Language Models. ECCV (70) Shicheng Li, Lei Li, Yi Liu, Shuhuai Ren, Yuanxin Liu, Rundong Gao, Xu Sun, Lu Hou
2024	—	`conf`	Visually Guided Generative Text-Layout Pre-training for Document Intelligence. NAACL-HLT Zhiming Mao, Haoli Bai, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Kam-Fai Wong
2024	J	`jnl`	Visually Guided Generative Text-Layout Pre-training for Document Intelligence. CoRR Zhiming Mao, Haoli Bai, Lu Hou, Jiansheng Wei, Xin Jiang, Qun Liu, Kam-Fai Wong
2023	A*	`conf`	Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction. AAAI Shiwei Li, Huifeng Guo, Lu Hou, Wei Zhang, Xing Tang, Ruiming Tang, Rui Zhang, Ruixuan Li
2023	J	`jnl`	CTRL: Connect Tabular and Language Model for CTR Prediction. CoRR Xiangyang Li, Bo Chen, Lu Hou, Ruiming Tang
2023	A*	`conf`	FETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation. NeurIPS Yuanxin Liu, Lei Li, Shuhuai Ren, Rundong Gao, Shicheng Li, Sishuo Chen, Xu Sun, Lu Hou
2023	J	`jnl`	FETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation. CoRR Yuanxin Liu, Lei Li, Shuhuai Ren, Rundong Gao, Shicheng Li, Sishuo Chen, Xu Sun, Lu Hou
2023	—	`conf`	Structured Pruning for Efficient Generative Pre-trained Language Models. ACL (Findings) Chaofan Tao, Lu Hou, Haoli Bai, Jiansheng Wei, Xin Jiang, Qun Liu, Ping Luo, Ngai Wong
2023	—	`conf`	TESTA: Temporal-Spatial Token Aggregation for Long-form Video-Language Understanding. EMNLP (Findings) Shuhuai Ren, Sishuo Chen, Shicheng Li, Xu Sun, Lu Hou
2023	J	`jnl`	TESTA: Temporal-Spatial Token Aggregation for Long-form Video-Language Understanding. CoRR Shuhuai Ren, Sishuo Chen, Shicheng Li, Xu Sun, Lu Hou
2023	J	`jnl`	TimeChat: A Time-sensitive Multimodal Large Language Model for Long Video Understanding. CoRR Shuhuai Ren, Linli Yao, Shicheng Li, Xu Sun, Lu Hou
2023	J	`jnl`	VITATECS: A Diagnostic Dataset for Temporal Concept Understanding of Video-Language Models. CoRR Shicheng Li, Lei Li, Shuhuai Ren, Yuanxin Liu, Yi Liu, Rundong Gao, Xu Sun, Lu Hou
2023	—	`conf`	Wukong-Reader: Multi-modal Pre-training for Fine-grained Visual Document Understanding. ACL (1) Haoli Bai, Zhiguang Liu, Xiaojun Meng, Wentao Li, Shuang Liu, Yifeng Luo, Nian Xie, Rongfu Zheng, Liangwei Wang, Lu Hou, Jiansheng Wei, Xin Jiang, Qun Liu
2023	—	`conf`	mCLIP: Multilingual CLIP via Cross-lingual Transfer. ACL (1) Guanhua Chen, Lu Hou, Yun Chen, Wenliang Dai, Lifeng Shang, Xin Jiang, Qun Liu, Jia Pan, Wenping Wang
2022	J	`jnl`	Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction. CoRR Shiwei Li, Huifeng Guo, Lu Hou, Wei Zhang, Xing Tang, Ruiming Tang, Rui Zhang, Ruixuan Li
2022	—	`conf`	Compression of Generative Pre-trained Language Models via Quantization. ACL (1) Chaofan Tao, Lu Hou, Wei Zhang, Lifeng Shang, Xin Jiang, Qun Liu, Ping Luo, Ngai Wong
2022	J	`jnl`	Compression of Generative Pre-trained Language Models via Quantization. CoRR Chaofan Tao, Lu Hou, Wei Zhang, Lifeng Shang, Xin Jiang, Qun Liu, Ping Luo, Ngai Wong
2022	—	`conf`	Enabling Multimodal Generation on CLIP via Vision-Language Knowledge Distillation. ACL (Findings) Wenliang Dai, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Pascale Fung
2022	J	`jnl`	Enabling Multimodal Generation on CLIP via Vision-Language Knowledge Distillation. CoRR Wenliang Dai, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Pascale Fung
2022	A*	`conf`	FILIP: Fine-grained Interactive Language-Image Pre-Training. ICLR Lewei Yao, Runhui Huang, Lu Hou, Guansong Lu, Minzhe Niu, Hang Xu, Xiaodan Liang, Zhenguo Li, Xin Jiang, Chunjing Xu
2022	A*	`conf`	LiteVL: Efficient Video-Language Learning with Enhanced Spatial-Temporal Modeling. EMNLP Dongsheng Chen, Chaofan Tao, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu
2022	J	`jnl`	LiteVL: Efficient Video-Language Learning with Enhanced Spatial-Temporal Modeling. CoRR Dongsheng Chen, Chaofan Tao, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu
2022	A*	`conf`	Towards Efficient Post-training Quantization of Pre-trained Language Models. NeurIPS Haoli Bai, Lu Hou, Lifeng Shang, Xin Jiang, Irwin King, Michael R. Lyu
2022	J	`jnl`	Wukong-Reader: Multi-modal Pre-training for Fine-grained Visual Document Understanding. CoRR Haoli Bai, Zhiguang Liu, Xiaojun Meng, Wentao Li, Shuang Liu, Nian Xie, Rongfu Zheng, Liangwei Wang, Lu Hou, Jiansheng Wei, Xin Jiang, Qun Liu
2022	J	`jnl`	Wukong: 100 Million Large-scale Chinese Cross-modal Pre-training Dataset and A Foundation Framework. CoRR Jiaxi Gu, Xiaojun Meng, Guansong Lu, Lu Hou, Minzhe Niu, Hang Xu, Xiaodan Liang, Wei Zhang, Xin Jiang, Chunjing Xu
2022	A*	`conf`	Wukong: A 100 Million Large-scale Chinese Cross-modal Pre-training Benchmark. NeurIPS Jiaxi Gu, Xiaojun Meng, Guansong Lu, Lu Hou, Niu Minzhe, Xiaodan Liang, Lewei Yao, Runhui Huang, Wei Zhang, Xin Jiang, Chunjing Xu, Hang Xu
2021	—	`conf`	BinaryBERT: Pushing the Limit of BERT Quantization. ACL/IJCNLP (1) Haoli Bai, Wei Zhang, Lu Hou, Lifeng Shang, Jin Jin, Xin Jiang, Qun Liu, Michael R. Lyu, Irwin King
2021	J	`jnl`	FILIP: Fine-grained Interactive Language-Image Pre-Training. CoRR Lewei Yao, Runhui Huang, Lu Hou, Guansong Lu, Minzhe Niu, Hang Xu, Xiaodan Liang, Zhenguo Li, Xin Jiang, Chunjing Xu
2021	—	`conf`	GhostBERT: Generate More Features with Cheap Operations for BERT. ACL/IJCNLP (1) Zhiqi Huang, Lu Hou, Lifeng Shang, Xin Jiang, Xiao Chen, Qun Liu
2021	J	`jnl`	Improved OOD Generalization via Adversarial Training and Pre-training. CoRR Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma
2021	A*	`conf`	Improved OOD Generalization via Adversarial Training and Pretraing. ICML Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhiming Ma
2021	A*	`conf`	Reweighting Augmented Samples by Minimizing the Maximal Expected Loss. ICLR Mingyang Yi, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma
2021	J	`jnl`	Reweighting Augmented Samples by Minimizing the Maximal Expected Loss. CoRR Mingyang Yi, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma
2021	J	`jnl`	Towards Efficient Post-training Quantization of Pre-trained Language Models. CoRR Haoli Bai, Lu Hou, Lifeng Shang, Xin Jiang, Irwin King, Michael R. Lyu
2020	J	`jnl`	BinaryBERT: Pushing the Limit of BERT Quantization. CoRR Haoli Bai, Wei Zhang, Lu Hou, Lifeng Shang, Jing Jin, Xin Jiang, Qun Liu, Michael R. Lyu, Irwin King
2020	A*	`conf`	DynaBERT: Dynamic BERT with Adaptive Width and Depth. NeurIPS Lu Hou, Zhiqi Huang, Lifeng Shang, Xin Jiang, Xiao Chen, Qun Liu
2020	J	`jnl`	DynaBERT: Dynamic BERT with Adaptive Width and Depth. CoRR Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu
2020	—	`conf`	TernaryBERT: Distillation-aware Ultra-low Bit BERT. EMNLP (1) Wei Zhang, Lu Hou, Yichun Yin, Lifeng Shang, Xiao Chen, Xin Jiang, Qun Liu
2020	J	`jnl`	TernaryBERT: Distillation-aware Ultra-low Bit BERT. CoRR Wei Zhang, Lu Hou, Yichun Yin, Lifeng Shang, Xiao Chen, Xin Jiang, Qun Liu
2019	—	`conf`	Analysis of Quantized Models. ICLR (Poster) Lu Hou, Ruiliang Zhang, James T. Kwok
2019	A*	`conf`	Normalization Helps Training of Quantized LSTM. NeurIPS Lu Hou, Jinhua Zhu, James T. Kwok, Fei Gao, Tao Qin, Tie-Yan Liu
2018	—	`conf`	Loss-aware Weight Quantization of Deep Networks. ICLR (Poster) Lu Hou, James T. Kwok
2018	J	`jnl`	Loss-aware Weight Quantization of Deep Networks. CoRR Lu Hou, James T. Kwok
2018	J	`jnl`	Power Law in Sparsified Deep Neural Networks. CoRR Lu Hou, James T. Kwok
2017	—	`conf`	Loss-aware Binarization of Deep Networks. ICLR (Poster) Lu Hou, Quanming Yao, James T. Kwok
2016	A*	`conf`	Efficient Learning of Timeseries Shapelets. AAAI Lu Hou, James T. Kwok, Jacek M. Zurada
2016	J	`jnl`	Loss-aware Binarization of Deep Networks. CoRR Lu Hou, Quanming Yao, James T. Kwok