Hierarchical Feature Extraction for Nuclear Morphometry-Based Cancer Diagnosis. - Chi Liu; Yue Huang 001; Ligong Han; John A. Ozolek; Gustavo K. Rohde (LABELS/DLMIA@MICCAI, 2016)

An automatic cells detection and segmentation. - Ligong Han; T. Hoang Ngan Le; Marios Savvides (Biomedical Applications in Molecular, Structural, and Functional Imaging, 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)

Learning Generative Models of Tissue Organization with Supervised GANs. - Ligong Han; Robert F. Murphy; Deva Ramanan (WACV, 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)

Unsupervised Domain Adaptation via Calibrating Uncertainties. - Ligong Han; Yang Zou; Ruijiang Gao; Lezi Wang; Dimitris N. Metaxas (CVPR Workshops, 2019)

Robust Conditional GAN from Uncertainty-Aware Pairwise Comparisons. - Ligong Han; Ruijiang Gao; Mun Kim; Xin Tao; Bo Liu 005; Dimitris N. Metaxas (AAAI, 2020)

Unbiased Auxiliary Classifier GANs with MINE. - Ligong Han; Anastasis Stathopoulos; Tao Xue; Dimitris N. Metaxas (CoRR, 2020)

Dual Projection Generative Adversarial Networks for Conditional Image Generation. - Ligong Han; Martin Renqiang Min; Anastasis Stathopoulos; Yu Tian 003; Ruijiang Gao; Asim Kadav; Dimitris N. Metaxas (ICCV, 2021)

Disentangled Recurrent Wasserstein Autoencoder. - Jun Han; Martin Renqiang Min; Ligong Han; Li Erran Li; Xuan Zhang (ICLR, 2021)

Human-AI Collaboration with Bandit Feedback. - Ruijiang Gao; Maytal Saar-Tsechansky; Maria De-Arteaga; Ligong Han; Min Kyung Lee; Matthew Lease (IJCAI, 2021)

Enhancing Counterfactual Classification via Self-Training. - Ruijiang Gao; Max Biggs; Wei Sun 031; Ligong Han (CoRR, 2021)

Enhancing Counterfactual Classification Performance via Self-Training. - Ruijiang Gao; Max Biggs; Wei Sun 031; Ligong Han (AAAI, 2022)

Show Me What and Tell Me How: Video Synthesis via Multimodal Conditioning. - Ligong Han; Jian Ren 005; Hsin-Ying Lee 001; Francesco Barbieri; Kyle Olszewski; Shervin Minaee; Dimitris N. Metaxas; Sergey Tulyakov (CVPR, 2022)

Hierarchically Self-supervised Transformer for Human Skeleton Representation Learning. - Yuxiao Chen 002; Long Zhao 003; Jianbo Yuan; Yu Tian 003; Zhaoyang Xia; Shijie Geng; Ligong Han; Dimitris N. Metaxas (ECCV (26), 2022)

TransFusion: Multi-view Divergent Fusion for Medical Image Segmentation with Transformers. - Di Liu 003; Yunhe Gao; Qilong Zhangli; Ligong Han; Xiaoxiao He; Zhaoyang Xia; Song Wen 001; Qi Chang; Zhennan Yan; Mu Zhou; Dimitris N. Metaxas (MICCAI (5), 2022)

Region Proposal Rectification Towards Robust Instance Segmentation of Biological Images. - Qilong Zhangli; Jingru Yi; Di Liu 003; Xiaoxiao He; Zhaoyang Xia; Qi Chang; Ligong Han; Yunhe Gao; Song Wen 001; Haiming Tang; He Wang 016; Mu Zhou; et al. (MICCAI (4), 2022)

AE-StyleGAN: Improved Training of Style-Based Auto-Encoders. - Ligong Han; Sri Harsha Musunuri; Martin Renqiang Min; Ruijiang Gao; Yu Tian 003; Dimitris N. Metaxas (WACV, 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)

Diffusion Guided Domain Adaptation of Image Generators. - Kunpeng Song; Ligong Han; Bingchen Liu; Dimitris N. Metaxas; Ahmed Elgammal (CoRR, 2022)

Learning Articulated Shape with Keypoint Pseudo-Labels from Web Images. - Anastasis Stathopoulos; Georgios Pavlakos; Ligong Han; Dimitris N. Metaxas (CVPR, 2023)

SINE: SINgle Image Editing with Text-to-Image Diffusion Models. - Zhixing Zhang; Ligong Han; Arnab Ghosh; Dimitris N. Metaxas; Jian Ren 005 (CVPR, 2023)

SVDiff: Compact Parameter Space for Diffusion Fine-Tuning. - Ligong Han; Yinxiao Li; Han Zhang 010; Peyman Milanfar; Dimitris N. Metaxas; Feng Yang 008 (ICCV, 2023)

DMCVR: Morphology-Guided Diffusion Model for 3D Cardiac Volume Reconstruction. - Xiaoxiao He; Chaowei Tan; Ligong Han; Bo Liu 005; Leon Axel; Kang Li 004; Dimitris N. Metaxas (MICCAI (7), 2023)

On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm. - Qi Chen 015; Changjian Shui; Ligong Han; Mario Marchand (NeurIPS, 2023)

Learning Complementary Policies for Human-AI Teams. - Ruijiang Gao; Maytal Saar-Tsechansky; Maria De-Arteaga; Ligong Han; Wei Sun 031; Min Kyung Lee; Matthew Lease (CoRR, 2023)

Constructive Assimilation: Boosting Contrastive Learning Performance through View Generation Strategies. - Ligong Han; Seungwook Han; Shivchander Sudalairaj; Charlotte Loh; Rumen Dangovski; Fei Deng 001; Pulkit Agrawal 001; Dimitris N. Metaxas; Leonid Karlinsky; Tsui-Wei Weng; Akash Srivastava (CoRR, 2023)

Improving Tuning-Free Real Image Editing with Proximal Guidance. - Ligong Han; Song Wen 001; Qi Chen; Zhixing Zhang; Kunpeng Song; Mengwei Ren; Ruijiang Gao; Yuxiao Chen 002; Di Liu 003; Qilong Zhangli; Anastasis Stathopoulos; Jindong Jiang; et al. (CoRR, 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)

Score-Guided Diffusion for 3D Human Recovery. - Anastasis Stathopoulos; Ligong Han; Dimitris N. Metaxas (CVPR, 2024)

BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models. - Yibin Wang 005; Haizhou Shi; Ligong Han; Dimitris N. Metaxas; Hao Wang 014 (NeurIPS, 2024)

ProxEdit: Improving Tuning-Free Real Image Editing with Proximal Guidance. - Ligong Han; Song Wen 001; Qi Chen; Zhixing Zhang; Kunpeng Song; Mengwei Ren; Ruijiang Gao; Anastasis Stathopoulos; Xiaoxiao He; Yuxiao Chen 002; Di Liu 003; Qilong Zhangli; et al. (WACV, 2024)

StyleGAN-Fusion: Diffusion Guided Domain Adaptation of Image Generators. - Kunpeng Song; Ligong Han; Bingchen Liu; Dimitris N. Metaxas; Ahmed Elgammal (WACV, 2024)

Spectrum-Aware Parameter Efficient Fine-Tuning for Diffusion Models. - Xinxi Zhang; Song Wen 001; Ligong Han; Felix Juefei-Xu; Akash Srivastava; Junzhou Huang; Hao Wang 014; Molei Tao; Dimitris N. Metaxas (CoRR, 2024)

DICE: Discrete Inversion Enabling Controllable Editing for Multinomial Diffusion and Masked Generative Models. - Xiaoxiao He; Ligong Han; Quan Dao; Song Wen 001; Minhao Bai; Di Liu 003; Han Zhang 010; Martin Renqiang Min; Felix Juefei-Xu; Chaowei Tan; Bo Liu 005; Kang Li 004; et al. (CoRR, 2024)

Training-Free Bayesianization for Low-Rank Adapters of Large Language Models. - Haizhou Shi; Yibin Wang 005; Ligong Han; Huan Zhang; Hao Wang 014 (CoRR, 2024)

MLLM-as-a-Judge for Image Safety without Human Labeling. - Zhenting Wang; Shuming Hu; Shiyu Zhao; Xiaowen Lin; Felix Juefei-Xu; Zhuowei Li 002; Ligong Han; Harihar Subramanyam; Li Chen; Jianfa Chen; Nan Jiang; Lingjuan Lyu; et al. (CVPR, 2025)

Implicit In-context Learning. - Zhuowei Li 002; Zihao Xu 001; Ligong Han; Yunhe Gao; Song Wen 001; Di Liu 003; Hao Wang 014; Dimitris N. Metaxas (ICLR, 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 (ICLR, 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 001; Seungwook Han; Abhishek Bhandwaldar; Guangxuan Xu; Kai Xu 016; Ligong Han; Luke Inglis; et al. (ICLR, 2025)

Rate-My-LoRA: EFFICIENT AND ADAPTIVE FEDERATED MODEL TUNING FOR CARDIAC MRI SEGMENTATION. - Xiaoxiao He; Haizhou Shi; Ligong Han; Chaowei Tan; Bo Liu 005; Zihao Xu 001; Meng Ye 003; Leon Axel; Kang Li 004; Dimitris N. Metaxas (ISBI, 2025)

SODA: Spectral Orthogonal Decomposition Adaptation for Diffusion Models. - Xinxi Zhang; Song Wen 001; Ligong Han; Felix Juefei-Xu; Akash Srivastava; Junzhou Huang; Vladimir Pavlovic 001; Hao Wang 014; Molei Tao; Dimitris N. Metaxas (WACV, 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 (WWW (Companion Volume), 2025)

Can Large Vision-Language Models Detect Images Copyright Infringement from GenAI? - Qipan Xu; Zhenting Wang; Xiaoxiao He; Ligong Han; Ruixiang Tang (CoRR, 2025)

SQuat: Subspace-orthogonal KV Cache Quantization. - Hao Wang; Ligong Han; Kai Xu 016; Akash Srivastava (CoRR, 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 016; Hao Wang; Aldo Pareja; Oleg Silkin; Mustafa Eyceoz; Akash Srivastava (CoRR, 2025)

Token-Level Uncertainty Estimation for Large Language Model Reasoning. - Tunyu Zhang; Haizhou Shi; Yibin Wang 005; Hengyi Wang; Xiaoxiao He; Zhuowei Li 002; Haoxian Chen 005; Ligong Han; Kai Xu; Huan Zhang; Dimitris N. Metaxas; Hao Wang 014 (CoRR, 2025)

Hopscotch: Discovering and Skipping Redundancies in Language Models. - Mustafa Eyceoz; Nikhil Shivakumar Nayak; Hao Wang; Ligong Han; Akash Srivastava (CoRR, 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, 2025)

Your Reward Function for RL is Your Best PRM for Search: Unifying RL and Search-Based TTS. - Can Jin; Yang Zhou 019; Qixin Zhang 001; Hongwu Peng; Di Zhang; Marco Pavone 001; Ligong Han; Zhang-Wei Hong; Tong Che; Dimitris N. Metaxas (CoRR, 2025)