Haokun Lin

According to our database, Haokun Lin authored at least 24 papers between 2023 and 2025.

Collaborative distances:

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

2025

Quantization Meets dLLMs: A Systematic Study of Post-training Quantization for Diffusion LLMs.

Haokun Lin, Haobo Xu, Yichen Wu, Ziyu Guo, Renrui Zhang, Zhichao Lu, Ying Wei, Qingfu Zhang, Zhenan Sun

CoRR, August, 2025

LRQ-DiT: Log-Rotation Post-Training Quantization of Diffusion Transformers for Text-to-Image Generation.

Lianwei Yang, Haokun Lin, Tianchen Zhao, Yichen Wu, Hongyu Zhu, Ruiqi Xie, Zhenan Sun, Yu Wang, Qingyi Gu

CoRR, August, 2025

Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS.

Alex ZH Dou, Zhongwei Wan, Dongfei Cui, Xin Wang, Jing Xiong, Haokun Lin, Chaofan Tao, Shen Yan, Mi Zhang

CoRR, July, 2025

PhyBlock: A Progressive Benchmark for Physical Understanding and Planning via 3D Block Assembly.

Liang Ma, Jiajun Wen, Min Lin, Rongtao Xu, Xiwen Liang, Bingqian Lin, Jun Ma, Yongxin Wang, Ziming Wei, Haokun Lin, Mingfei Han, Meng Cao, Bokui Chen, Ivan Laptev, Xiaodan Liang

CoRR, June, 2025

TokLIP: Marry Visual Tokens to CLIP for Multimodal Comprehension and Generation.

Haokun Lin, Teng Wang, Yixiao Ge, Yuying Ge, Zhichao Lu, Ying Wei, Qingfu Zhang, Zhenan Sun, Ying Shan

CoRR, May, 2025

Scale Up Composed Image Retrieval Learning via Modification Text Generation.

Yinan Zhou, Yaxiong Wang, Haokun Lin, Chen Ma, Li Zhu, Zhedong Zheng

CoRR, April, 2025

Singular Value Fine-tuning for Few-Shot Class-Incremental Learning.

Zhiwu Wang, Yichen Wu, Renzhen Wang, Haokun Lin, Quanziang Wang, Qian Zhao, Deyu Meng

CoRR, March, 2025

EfficientLLM: Scalable Pruning-Aware Pretraining for Architecture-Agnostic Edge Language Models.

Xingrun Xing, Zheng Liu, Shitao Xiao, Boyan Gao, Yiming Liang, Wanpeng Zhang, Haokun Lin, Guoqi Li, Jiajun Zhang

CoRR, February, 2025

Image-level Memorization Detection via Inversion-based Inference Perturbation.

Yue Jiang, Haokun Lin, Yang Bai, Bo Peng, Zhili Liu, Yueming Lyu, Yong Yang, Xing Zheng, Jing Dong

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

EACO: Enhancing Alignment in Multimodal LLMs via Critical Observation.

Yongxin Wang, Meng Cao, Haokun Lin, Mingfei Han, Liang Ma, Jin Jiang, Yuhao Cheng, Xiaodan Liang

CoRR, 2024

DOGE: Towards Versatile Visual Document Grounding and Referring.

Yinan Zhou, Yuxin Chen, Haokun Lin, Shuyu Yang, Li Zhu, Zhongang Qi, Chen Ma, Ying Shan

CoRR, 2024

Rotation and Permutation for Advanced Outlier Management and Efficient Quantization of LLMs.

Haokun Lin, Haobo Xu, Yichen Wu, Jingzhi Cui, Yingtao Zhang, Linzhan Mou, Linqi Song, Zhenan Sun, Ying Wei

CoRR, 2024

MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?

Renrui Zhang, Dongzhi Jiang, Yichi Zhang, Haokun Lin, Ziyu Guo, Pengshuo Qiu, Aojun Zhou, Pan Lu, Kai-Wei Chang, Peng Gao, Hongsheng Li

CoRR, 2024

Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs.

Sukmin Yun, Haokun Lin, Rusiru Thushara, Mohammad Qazim Bhat, Yongxin Wang, Zutao Jiang, Mingkai Deng, Jinhong Wang, Tianhua Tao, Junbo Li, Haonan Li, Preslav Nakov, Timothy Baldwin, Zhengzhong Liu, Eric P. Xing, Xiaodan Liang, Zhiqiang Shen

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

DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs.

Haokun Lin, Haobo Xu, Yichen Wu, Jingzhi Cui, Yingtao Zhang, Linzhan Mou, Linqi Song, Zhenan Sun, Ying Wei

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

MATHVERSE: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?

Renrui Zhang, Dongzhi Jiang, Yichi Zhang, Haokun Lin, Ziyu Guo, Pengshuo Qiu, Aojun Zhou, Pan Lu, Kai-Wei Chang, Yu Qiao, Peng Gao, Hongsheng Li

Proceedings of the Computer Vision - ECCV 2024, 2024

Contrastive Learning with Counterfactual Explanations for Radiology Report Generation.

Mingjie Li, Haokun Lin, Liang Qiu, Xiaodan Liang, Ling Chen, Abdulmotaleb Elsaddik, Xiaojun Chang

Proceedings of the Computer Vision - ECCV 2024, 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

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

Single Line-to-Ground Fault Type Multilevel Classification in Distribution Network Using Realistic Recorded Waveform.

Jiajun Liu, Chenjing Li, Yue Liu, Ji Sun, Haokun Lin

Sensors, November, 2023

Research on Parameter Optimization Method of Sliding Mode Controller for the Grid-Connected Composite Device Based on IMFO Algorithm.

Ji Sun, Jiajun Liu, Miao Miao, Haokun Lin

Sensors, 2023

Towards Medical Artificial General Intelligence via Knowledge-Enhanced Multimodal Pretraining.

Bingqian Lin, Zicong Chen, Mingjie Li, Haokun Lin, Hang Xu, Yi Zhu, Jianzhuang Liu, Wenjia Cai, Lei Yang, Shen Zhao, Chenfei Wu, Ling Chen, Xiaojun Chang, Yi Yang, Lei Xing, Xiaodan Liang

CoRR, 2023

Dynamic Graph Enhanced Contrastive Learning for Chest X-Ray Report Generation.

Mingjie Li, Bingqian Lin, Zicong Chen, Haokun Lin, Xiaodan Liang, Xiaojun Chang

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