Ligong Han

According to our database, Ligong Han authored at least 50 papers between 2016 and 2025.

Collaborative distances:

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

2025

Your Reward Function for RL is Your Best PRM for Search: Unifying RL and Search-Based TTS.

Can Jin, Yang Zhou, Qixin Zhang, Hongwu Peng, Di Zhang, Marco Pavone, Ligong Han, Zhang-Wei Hong, Tong Che, Dimitris N. Metaxas

CoRR, August, 2025

CATP: Contextually Adaptive Token Pruning for Efficient and Enhanced Multimodal In-Context Learning.

Yanshu Li, Jianjiang Yang, Zhennan Shen, Ligong Han, Haoyan Xu, Ruixiang Tang

CoRR, August, 2025

Hopscotch: Discovering and Skipping Redundancies in Language Models.

Mustafa Eyceoz, Nikhil Shivakumar Nayak, Hao Wang, Ligong Han, Akash Srivastava

CoRR, June, 2025

Token-Level Uncertainty Estimation for Large Language Model Reasoning.

Tunyu Zhang, Haizhou Shi, Yibin Wang, Hengyi Wang, Xiaoxiao He, Zhuowei Li, Haoxian Chen, Ligong Han, Kai Xu, Huan Zhang, Dimitris N. Metaxas, Hao Wang

CoRR, May, 2025

Sculpting Subspaces: Constrained Full Fine-Tuning in LLMs for Continual Learning.

Nikhil Shivakumar Nayak, Krishnateja Killamsetty, Ligong Han, Abhishek Bhandwaldar, Prateek Chanda, Kai Xu, Hao Wang, Aldo Pareja, Oleg Silkin, Mustafa Eyceoz, Akash Srivastava

CoRR, April, 2025

SQuat: Subspace-orthogonal KV Cache Quantization.

Hao Wang, Ligong Han, Kai Xu, Akash Srivastava

CoRR, March, 2025

Can Large Vision-Language Models Detect Images Copyright Infringement from GenAI?

Qipan Xu, Zhenting Wang, Xiaoxiao He, Ligong Han, Ruixiang Tang

CoRR, February, 2025

APEER : Automatic Prompt Engineering Enhances Large Language Model Reranking.

Can Jin, Hongwu Peng, Shiyu Zhao, Zhenting Wang, Wujiang Xu, Ligong Han, Jiahui Zhao, Kai Zhong, Sanguthevar Rajasekaran, Dimitris N. Metaxas

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

SODA: Spectral Orthogonal Decomposition Adaptation for Diffusion Models.

Xinxi Zhang, Song Wen, Ligong Han, Felix Juefei-Xu, Akash Srivastava, Junzhou Huang, Vladimir Pavlovic, Hao Wang, Molei Tao, Dimitris N. Metaxas

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

Rate-My-LoRA: EFFICIENT AND ADAPTIVE FEDERATED MODEL TUNING FOR CARDIAC MRI SEGMENTATION.

Xiaoxiao He, Haizhou Shi, Ligong Han, Chaowei Tan, Bo Liu, Zihao Xu, Meng Ye, Leon Axel, Kang Li, Dimitris N. Metaxas

Proceedings of the 22nd IEEE International Symposium on Biomedical Imaging, 2025

Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs.

Aldo Pareja, Nikhil Shivakumar Nayak, Hao Wang, Krishnateja Killamsetty, Shivchander Sudalairaj, Wenlong Zhao, Seungwook Han, Abhishek Bhandwaldar, Guangxuan Xu, Kai Xu, Ligong Han, Luke Inglis, Akash Srivastava

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

LoR-VP: Low-Rank Visual Prompting for Efficient Vision Model Adaptation.

Can Jin, Ying Li, Mingyu Zhao, Shiyu Zhao, Zhenting Wang, Xiaoxiao He, Ligong Han, Tong Che, Dimitris N. Metaxas

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Implicit In-context Learning.

Zhuowei Li, Zihao Xu, Ligong Han, Yunhe Gao, Song Wen, Di Liu, Hao Wang, Dimitris N. Metaxas

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

MLLM-as-a-Judge for Image Safety without Human Labeling.

Zhenting Wang, Shuming Hu, Shiyu Zhao, Xiaowen Lin, Felix Juefei-Xu, Zhuowei Li, Ligong Han, Harihar Subramanyam, Li Chen, Jianfa Chen, Nan Jiang, Lingjuan Lyu, Shiqing Ma, Dimitris N. Metaxas, Ankit Jain

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

2024

Training-Free Bayesianization for Low-Rank Adapters of Large Language Models.

Haizhou Shi, Yibin Wang, Ligong Han, Huan Zhang, Hao Wang

CoRR, 2024

DICE: Discrete Inversion Enabling Controllable Editing for Multinomial Diffusion and Masked Generative Models.

Xiaoxiao He, Ligong Han, Quan Dao, Song Wen, Minhao Bai, Di Liu, Han Zhang, Martin Renqiang Min, Felix Juefei-Xu, Chaowei Tan, Bo Liu, Kang Li, Hongdong Li, Junzhou Huang, Faez Ahmed, Akash Srivastava, Dimitris N. Metaxas

CoRR, 2024

Spectrum-Aware Parameter Efficient Fine-Tuning for Diffusion Models.

Xinxi Zhang, Song Wen, Ligong Han, Felix Juefei-Xu, Akash Srivastava, Junzhou Huang, Hao Wang, Molei Tao, Dimitris N. Metaxas

CoRR, 2024

StyleGAN-Fusion: Diffusion Guided Domain Adaptation of Image Generators.

Kunpeng Song, Ligong Han, Bingchen Liu, Dimitris N. Metaxas, Ahmed Elgammal

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

ProxEdit: Improving Tuning-Free Real Image Editing with Proximal Guidance.

Ligong Han, Song Wen, Qi Chen, Zhixing Zhang, Kunpeng Song, Mengwei Ren, Ruijiang Gao, Anastasis Stathopoulos, Xiaoxiao He, Yuxiao Chen, Di Liu, Qilong Zhangli, Jindong Jiang, Zhaoyang Xia, Akash Srivastava, Dimitris N. Metaxas

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models.

Yibin Wang, Haizhou Shi, Ligong Han, Dimitris N. Metaxas, Hao Wang

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

Score-Guided Diffusion for 3D Human Recovery.

Anastasis Stathopoulos, Ligong Han, Dimitris N. Metaxas

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

2023

Mitigating Confirmation Bias in Semi-supervised Learning via Efficient Bayesian Model Averaging.

Charlotte Loh, Rumen Dangovski, Shivchander Sudalairaj, Seungwook Han, Ligong Han, Leonid Karlinsky, Marin Soljacic, Akash Srivastava

Trans. Mach. Learn. Res., 2023

Improving Tuning-Free Real Image Editing with Proximal Guidance.

Ligong Han, Song Wen, Qi Chen, Zhixing Zhang, Kunpeng Song, Mengwei Ren, Ruijiang Gao, Yuxiao Chen, Di Liu, Qilong Zhangli, Anastasis Stathopoulos, Jindong Jiang, Zhaoyang Xia, Akash Srivastava, Dimitris N. Metaxas

CoRR, 2023

Constructive Assimilation: Boosting Contrastive Learning Performance through View Generation Strategies.

Ligong Han, Seungwook Han, Shivchander Sudalairaj, Charlotte Loh, Rumen Dangovski, Fei Deng, Pulkit Agrawal, Dimitris N. Metaxas, Leonid Karlinsky, Tsui-Wei Weng, Akash Srivastava

CoRR, 2023

Learning Complementary Policies for Human-AI Teams.

Ruijiang Gao, Maytal Saar-Tsechansky, Maria De-Arteaga, Ligong Han, Wei Sun, Min Kyung Lee, Matthew Lease

CoRR, 2023

On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm.

Qi Chen, Changjian Shui, Ligong Han, Mario Marchand

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

DMCVR: Morphology-Guided Diffusion Model for 3D Cardiac Volume Reconstruction.

Xiaoxiao He, Chaowei Tan, Ligong Han, Bo Liu, Leon Axel, Kang Li, Dimitris N. Metaxas

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

SVDiff: Compact Parameter Space for Diffusion Fine-Tuning.

Ligong Han, Yinxiao Li, Han Zhang, Peyman Milanfar, Dimitris N. Metaxas, Feng Yang

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

SINE: SINgle Image Editing with Text-to-Image Diffusion Models.

Zhixing Zhang, Ligong Han, Arnab Ghosh, Dimitris N. Metaxas, Jian Ren

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

Learning Articulated Shape with Keypoint Pseudo-Labels from Web Images.

Anastasis Stathopoulos, Georgios Pavlakos, Ligong Han, Dimitris N. Metaxas

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

2022

Diffusion Guided Domain Adaptation of Image Generators.

Kunpeng Song, Ligong Han, Bingchen Liu, Dimitris N. Metaxas, Ahmed Elgammal

CoRR, 2022

On the Importance of Calibration in Semi-supervised Learning.

Charlotte Loh, Rumen Dangovski, Shivchander Sudalairaj, Seungwook Han, Ligong Han, Leonid Karlinsky, Marin Soljacic, Akash Srivastava

CoRR, 2022

AE-StyleGAN: Improved Training of Style-Based Auto-Encoders.

Ligong Han, Sri Harsha Musunuri, Martin Renqiang Min, Ruijiang Gao, Yu Tian, Dimitris N. Metaxas

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Region Proposal Rectification Towards Robust Instance Segmentation of Biological Images.

Qilong Zhangli, Jingru Yi, Di Liu, Xiaoxiao He, Zhaoyang Xia, Qi Chang, Ligong Han, Yunhe Gao, Song Wen, Haiming Tang, He Wang, Mu Zhou, Dimitris N. Metaxas

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

TransFusion: Multi-view Divergent Fusion for Medical Image Segmentation with Transformers.

Di Liu, Yunhe Gao, Qilong Zhangli, Ligong Han, Xiaoxiao He, Zhaoyang Xia, Song Wen, Qi Chang, Zhennan Yan, Mu Zhou, Dimitris N. Metaxas

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Hierarchically Self-supervised Transformer for Human Skeleton Representation Learning.

Yuxiao Chen, Long Zhao, Jianbo Yuan, Yu Tian, Zhaoyang Xia, Shijie Geng, Ligong Han, Dimitris N. Metaxas

Proceedings of the Computer Vision - ECCV 2022, 2022

Show Me What and Tell Me How: Video Synthesis via Multimodal Conditioning.

Ligong Han, Jian Ren, Hsin-Ying Lee, Francesco Barbieri, Kyle Olszewski, Shervin Minaee, Dimitris N. Metaxas, Sergey Tulyakov

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Enhancing Counterfactual Classification Performance via Self-Training.

Ruijiang Gao, Max Biggs, Wei Sun, Ligong Han

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Enhancing Counterfactual Classification via Self-Training.

Ruijiang Gao, Max Biggs, Wei Sun, Ligong Han

CoRR, 2021

Human-AI Collaboration with Bandit Feedback.

Ruijiang Gao, Maytal Saar-Tsechansky, Maria De-Arteaga, Ligong Han, Min Kyung Lee, Matthew Lease

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Disentangled Recurrent Wasserstein Autoencoder.

Jun Han, Martin Renqiang Min, Ligong Han, Li Erran Li, Xuan Zhang

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

Dual Projection Generative Adversarial Networks for Conditional Image Generation.

Ligong Han, Martin Renqiang Min, Anastasis Stathopoulos, Yu Tian, Ruijiang Gao, Asim Kadav, Dimitris N. Metaxas

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Unbiased Auxiliary Classifier GANs with MINE.

Ligong Han, Anastasis Stathopoulos, Tao Xue, Dimitris N. Metaxas

CoRR, 2020

Robust Conditional GAN from Uncertainty-Aware Pairwise Comparisons.

Ligong Han, Ruijiang Gao, Mun Kim, Xin Tao, Bo Liu, Dimitris N. Metaxas

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Unsupervised Domain Adaptation via Calibrating Uncertainties.

Ligong Han, Yang Zou, Ruijiang Gao, Lezi Wang, Dimitris N. Metaxas

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018

Deep contextual recurrent residual networks for scene labeling.

T. Hoang Ngan Le, Chi Nhan Duong, Ligong Han, Khoa Luu, Kha Gia Quach, Marios Savvides

Pattern Recognit., 2018

Learning Generative Models of Tissue Organization with Supervised GANs.

Ligong Han, Robert F. Murphy, Deva Ramanan

Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

2017

Deep Contextual Recurrent Residual Networks for Scene Labeling.

T. Hoang Ngan Le, Chi Nhan Duong, Ligong Han, Khoa Luu, Marios Savvides, Dipan K. Pal

CoRR, 2017

An automatic cells detection and segmentation.

Ligong Han, T. Hoang Ngan Le, Marios Savvides

Proceedings of the Medical Imaging 2017: Biomedical Applications in Molecular, 2017

2016

Hierarchical Feature Extraction for Nuclear Morphometry-Based Cancer Diagnosis.

Chi Liu, Yue Huang, Ligong Han, John A. Ozolek, Gustavo K. Rohde

Proceedings of the Deep Learning and Data Labeling for Medical Applications, 2016