Hou, Lu

26 publications

TMLR 2026 The Synergy Dilemma of Long-CoT SFT and RL: Investigating Post-Training Techniques for Reasoning VLMs 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

NeurIPS 2025 A Simple Linear Patch Revives Layer-Pruned Large Language Models Xinrui Chen, Haoli Bai, Tao Yuan, Ruikang Liu, Kang Zhao, Xianzhi Yu, Lu Hou, Tian Guan, Yonghong He, Chun Yuan

NeurIPS 2025 DeepDiver: Adaptive Web-Search Intensity Scaling via Reinforcement Learning Wenxuan Shi, Haochen Tan, Chuqiao Kuang, Xiaoguang Li, Hanting Chen, Xiaozhe Ren, Yasheng Wang, Lu Hou, Lifeng Shang

CVPR 2025 EMOVA: Empowering Language Models to See, Hear and Speak with Vivid Emotions 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

ICML 2025 FlatQuant: Flatness Matters for LLM Quantization 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

CVPR 2025 HiRes-LLaVA: Restoring Fragmentation Input in High-Resolution Large Vision-Language Models Runhui Huang, Xinpeng Ding, Chunwei Wang, Jianhua Han, Yulong Liu, Hengshuang Zhao, Hang Xu, Lu Hou, Wei Zhang, Xiaodan Liang

ICCV 2025 ILLUME: Illuminating Your LLMs to See, Draw, and Self-Enhance Chunwei Wang, Guansong Lu, Junwei Yang, Runhui Huang, Jianhua Han, Lu Hou, Wei Zhang, Hang Xu

AAAI 2025 OAC: Output-Adaptive Calibration for Accurate Post-Training Quantization Ali Edalati, Alireza Ghaffari, Mahsa Ghazvini Nejad, Lu Hou, Boxing Chen, Masoud Asgharian, Vahid Partovi Nia

CVPR 2024 MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-Wise Pruning Error Metric Haokun Lin, Haoli Bai, Zhili Liu, Lu Hou, Muyi Sun, Linqi Song, Ying Wei, Zhenan Sun

ICLR 2024 Plug-and-Play: An Efficient Post-Training Pruning Method for Large Language Models Yingtao Zhang, Haoli Bai, Haokun Lin, Jialin Zhao, Lu Hou, Carlo Vittorio Cannistraci

CVPR 2024 TimeChat: A Time-Sensitive Multimodal Large Language Model for Long Video Understanding Shuhuai Ren, Linli Yao, Shicheng Li, Xu Sun, Lu Hou

NeurIPS 2024 UNIT: Unifying Image and Text Recognition in One Vision Encoder Yi Zhu, Yanpeng Zhou, Chunwei Wang, Yang Cao, Jianhua Han, Lu Hou, Hang Xu

ECCV 2024 VITATECS: A Diagnostic Dataset for Temporal Concept Understanding of Video-Language Models Shicheng Li, Lei Li, Yi Liu, Shuhuai Ren, Yuanxin Liu, Rundong Gao, Xu Sun, Lu Hou

AAAI 2023 Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction Shiwei Li, Huifeng Guo, Lu Hou, Wei Zhang, Xing Tang, Ruiming Tang, Rui Zhang, Ruixuan Li

NeurIPS 2023 FETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation Yuanxin Liu, Lei Li, Shuhuai Ren, Rundong Gao, Shicheng Li, Sishuo Chen, Xu Sun, Lu Hou

ICLR 2022 FILIP: Fine-Grained Interactive Language-Image Pre-Training Lewei Yao, Runhui Huang, Lu Hou, Guansong Lu, Minzhe Niu, Hang Xu, Xiaodan Liang, Zhenguo Li, Xin Jiang, Chunjing Xu

NeurIPS 2022 Towards Efficient Post-Training Quantization of Pre-Trained Language Models Haoli Bai, Lu Hou, Lifeng Shang, Xin Jiang, Irwin King, Michael R Lyu

NeurIPS 2022 Wukong: A 100 Million Large-Scale Chinese Cross-Modal Pre-Training Benchmark Jiaxi Gu, Xiaojun Meng, Guansong Lu, Lu Hou, Niu Minzhe, Xiaodan Liang, Lewei Yao, Runhui Huang, Wei Zhang, Xin Jiang, Chunjing Xu, Hang Xu

ICML 2021 Improved OOD Generalization via Adversarial Training and Pretraing Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhiming Ma

ICLR 2021 Reweighting Augmented Samples by Minimizing the Maximal Expected Loss Mingyang Yi, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma

NeurIPS 2020 DynaBERT: Dynamic BERT with Adaptive Width and Depth Lu Hou, Zhiqi Huang, Lifeng Shang, Xin Jiang, Xiao Chen, Qun Liu

ICLR 2019 Analysis of Quantized Models Lu Hou, Ruiliang Zhang, James T. Kwok

NeurIPS 2019 Normalization Helps Training of Quantized LSTM Lu Hou, Jinhua Zhu, James Kwok, Fei Gao, Tao Qin, Tie-Yan Liu

ICLR 2018 Loss-Aware Weight Quantization of Deep Networks Lu Hou, James T. Kwok

ICLR 2017 Loss-Aware Binarization of Deep Networks Lu Hou, Quanming Yao, James T. Kwok

AAAI 2016 Efficient Learning of Timeseries Shapelets Lu Hou, James T. Kwok, Jacek M. Zurada