Lu Hou

According to our database, Lu Hou authored at least 55 papers between 2016 and 2025.

Collaborative distances:

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

2025

Pre-Trained Models for Search and Recommendation: Introduction to the Special Issue - Part 2.

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

ACM Trans. Inf. Syst., September, 2025

Think Before You Talk: Enhancing Meaningful Dialogue Generation in Full-Duplex Speech Language Models with Planning-Inspired Text Guidance.

Wenqian Cui, Lei Zhu, Xiaohui Li, Zhihan Guo, Haoli Bai, Lu Hou, Irwin King

CoRR, August, 2025

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, Xiaohui Li, Lu Hou, Lifeng Shang, Qun Liu

CoRR, July, 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

CoRR, May, 2025

Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models.

Ruikang Liu, Yuxuan Sun, Manyi Zhang, Haoli Bai, Xianzhi Yu, Tiezheng Yu, Chun Yuan, Lu Hou

CoRR, April, 2025

ILLUME+: Illuminating Unified MLLM with Dual Visual Tokenization and Diffusion Refinement.

Runhui Huang, Chunwei Wang, Junwei Yang, Guansong Lu, Yunlong Yuan, Jianhua Han, Lu Hou, Wei Zhang, Lanqing Hong, Hengshuang Zhao, Hang Xu

CoRR, April, 2025

Pre-Trained Models for Search and Recommendation: Introduction to the Special Issue - Part 1.

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

ACM Trans. Inf. Syst., March, 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

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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

Power Law in Deep Neural Networks: Sparse Network Generation and Continual Learning With Preferential Attachment.

Fan Feng, Lu Hou, Qi She, Rosa H. M. Chan, James T. Kwok

IEEE Trans. Neural Networks Learn. Syst., July, 2024

Embedding Compression in Recommender Systems: A Survey.

Shiwei Li, Huifeng Guo, Xing Tang, Ruiming Tang, Lu Hou, Ruixuan Li, Rui Zhang

ACM Comput. Surv., May, 2024

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

CoRR, 2024

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

CoRR, 2024

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, Jun Yao, Lanqing Hong, Lu Hou, Hang Xu

CoRR, 2024

DeCo: Decoupling Token Compression from Semantic Abstraction in Multimodal Large Language Models.

Linli Yao, Lei Li, Shuhuai Ren, Lean Wang, Yuanxin Liu, Xu Sun, Lu Hou

CoRR, 2024

Towards Multimodal Video Paragraph Captioning Models Robust to Missing Modality.

Sishuo Chen, Lei Li, Shuhuai Ren, Rundong Gao, Yuanxin Liu, Xiaohan Bi, Xu Sun, Lu Hou

CoRR, 2024

Visually Guided Generative Text-Layout Pre-training for Document Intelligence.

Zhiming Mao, Haoli Bai, Lu Hou, Jiansheng Wei, Xin Jiang, Qun Liu, Kam-Fai Wong

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Visually Guided Generative Text-Layout Pre-training for Document Intelligence.

Zhiming Mao, Haoli Bai, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Kam-Fai Wong

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 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

Proceedings of the Twelfth International Conference on Learning Representations, 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

Proceedings of the Computer Vision - ECCV 2024, 2024

TimeChat: A Time-sensitive Multimodal Large Language Model for Long Video Understanding.

Shuhuai Ren, Linli Yao, Shicheng Li, Xu Sun, Lu Hou

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

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

TempCompass: Do Video LLMs Really Understand Videos?

Yuanxin Liu, Shicheng Li, Yi Liu, Yuxiang Wang, Shuhuai Ren, Lei Li, Sishuo Chen, Xu Sun, Lu Hou

Proceedings of the Findings of the Association for Computational Linguistics, 2024

IntactKV: Improving Large Language Model Quantization by Keeping Pivot Tokens Intact.

Ruikang Liu, Haoli Bai, Haokun Lin, Yuening Li, Han Gao, Zhengzhuo Xu, Lu Hou, Jun Yao, Chun Yuan

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

CTRL: Connect Tabular and Language Model for CTR Prediction.

Xiangyang Li, Bo Chen, Lu Hou, Ruiming Tang

CoRR, 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

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

TESTA: Temporal-Spatial Token Aggregation for Long-form Video-Language Understanding.

Shuhuai Ren, Sishuo Chen, Shicheng Li, Xu Sun, Lu Hou

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Structured Pruning for Efficient Generative Pre-trained Language Models.

Chaofan Tao, Lu Hou, Haoli Bai, Jiansheng Wei, Xin Jiang, Qun Liu, Ping Luo, Ngai Wong

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

mCLIP: Multilingual CLIP via Cross-lingual Transfer.

Guanhua Chen, Lu Hou, Yun Chen, Wenliang Dai, Lifeng Shang, Xin Jiang, Qun Liu, Jia Pan, Wenping Wang

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Wukong-Reader: Multi-modal Pre-training for Fine-grained Visual Document Understanding.

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

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 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

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Wukong-Reader: Multi-modal Pre-training for Fine-grained Visual Document Understanding.

Haoli Bai, Zhiguang Liu, Xiaojun Meng, Wentao Li, Shuang Liu, Nian Xie, Rongfu Zheng, Liangwei Wang, Lu Hou, Jiansheng Wei, Xin Jiang, Qun Liu

CoRR, 2022

Wukong: 100 Million Large-scale Chinese Cross-modal Pre-training Dataset and A Foundation Framework.

Jiaxi Gu, Xiaojun Meng, Guansong Lu, Lu Hou, Minzhe Niu, Hang Xu, Xiaodan Liang, Wei Zhang, Xin Jiang, Chunjing Xu

CoRR, 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

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

Towards Efficient Post-training Quantization of Pre-trained Language Models.

Haoli Bai, Lu Hou, Lifeng Shang, Xin Jiang, Irwin King, Michael R. Lyu

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

Proceedings of the Tenth International Conference on Learning Representations, 2022

LiteVL: Efficient Video-Language Learning with Enhanced Spatial-Temporal Modeling.

Dongsheng Chen, Chaofan Tao, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Compression of Generative Pre-trained Language Models via Quantization.

Chaofan Tao, Lu Hou, Wei Zhang, Lifeng Shang, Xin Jiang, Qun Liu, Ping Luo, Ngai Wong

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Enabling Multimodal Generation on CLIP via Vision-Language Knowledge Distillation.

Wenliang Dai, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Pascale Fung

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021

Improved OOD Generalization via Adversarial Training and Pre-training.

Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma

CoRR, 2021

Improved OOD Generalization via Adversarial Training and Pretraing.

Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhiming Ma

Proceedings of the 38th International Conference on Machine Learning, 2021

Reweighting Augmented Samples by Minimizing the Maximal Expected Loss.

Mingyang Yi, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma

Proceedings of the 9th International Conference on Learning Representations, 2021

GhostBERT: Generate More Features with Cheap Operations for BERT.

Zhiqi Huang, Lu Hou, Lifeng Shang, Xin Jiang, Xiao Chen, Qun Liu

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

BinaryBERT: Pushing the Limit of BERT Quantization.

Haoli Bai, Wei Zhang, Lu Hou, Lifeng Shang, Jin Jin, Xin Jiang, Qun Liu, Michael R. Lyu, Irwin King

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

BinaryBERT: Pushing the Limit of BERT Quantization.

Haoli Bai, Wei Zhang, Lu Hou, Lifeng Shang, Jing Jin, Xin Jiang, Qun Liu, Michael R. Lyu, Irwin King

CoRR, 2020

DynaBERT: Dynamic BERT with Adaptive Width and Depth.

Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu

CoRR, 2020

DynaBERT: Dynamic BERT with Adaptive Width and Depth.

Lu Hou, Zhiqi Huang, Lifeng Shang, Xin Jiang, Xiao Chen, Qun Liu

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

TernaryBERT: Distillation-aware Ultra-low Bit BERT.

Wei Zhang, Lu Hou, Yichun Yin, Lifeng Shang, Xiao Chen, Xin Jiang, Qun Liu

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019

Normalization Helps Training of Quantized LSTM.

Lu Hou, Jinhua Zhu, James T. Kwok, Fei Gao, Tao Qin, Tie-Yan Liu

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Analysis of Quantized Models.

Lu Hou, Ruiliang Zhang, James T. Kwok

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Power Law in Sparsified Deep Neural Networks.

Lu Hou, James T. Kwok

CoRR, 2018

Loss-aware Weight Quantization of Deep Networks.

Lu Hou, James T. Kwok

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Loss-aware Binarization of Deep Networks.

Lu Hou, Quanming Yao, James T. Kwok

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Efficient Learning of Timeseries Shapelets.

Lu Hou, James T. Kwok, Jacek M. Zurada

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016