Han, Ligong

29 publications

ICLR 2026 Sculpting Subspaces: Constrained Full Fine-Tuning in LLMs for Continual Learning Nikhil Shivakumar Nayak, Krishnateja Killamsetty, Ligong Han, Abhishek Bhandwaldar, Prateek Chanda, Kai Xu, Oleg Silkin, Mustafa Eyceoz, Hao Wang, Aldo Pareja, Akash Srivastava

ICLR 2026 TokUR: 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

ICLR 2025 Implicit In-Context Learning Zhuowei Li, Zihao Xu, Ligong Han, Yunhe Gao, Song Wen, Di Liu, Hao Wang, 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

CVPR 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

NeurIPS 2025 Optimize Any Topology: A Foundation Model for Shape- and Resolution-Free Structural Topology Optimization Amin Heyrani Nobari, Lyle Regenwetter, Cyril Picard, Ligong Han, Faez Ahmed

WACV 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 Metaxas

NeurIPS 2025 Training-Free Bayesianization for Low-Rank Adapters of Large Language Models Haizhou Shi, Yibin Wang, Ligong Han, Huan Zhang, Hao Wang

ICLRW 2025 Training-Free Bayesianization for Low-Rank Adapters of Large Language Models Haizhou Shi, Yibin Wang, Ligong Han, Huan Zhang, Hao Wang

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, Seungwook Han, Abhishek Bhandwaldar, Guangxuan Xu, Kai Xu, Ligong Han, Luke Inglis, Akash Srivastava

NeurIPS 2024 BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models Yibin Wang, Haizhou Shi, Ligong Han, Dimitris Metaxas, Hao Wang

WACV 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 Metaxas

CVPR 2024 Score-Guided Diffusion for 3D Human Recovery Anastasis Stathopoulos, Ligong Han, Dimitris Metaxas

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

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

TMLR 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

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

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

ICCV 2023 SVDiff: Compact Parameter Space for Diffusion Fine-Tuning Ligong Han, Yinxiao Li, Han Zhang, Peyman Milanfar, Dimitris Metaxas, Feng Yang

WACV 2022 AE-StyleGAN: Improved Training of Style-Based Auto-Encoders Ligong Han, Sri Harsha Musunuri, Martin Renqiang Min, Ruijiang Gao, Yu Tian, Dimitris Metaxas

AAAI 2022 Enhancing Counterfactual Classification Performance via Self-Training Ruijiang Gao, Max Biggs, Wei Sun, Ligong Han

ECCV 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

CVPR 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 Metaxas, Sergey Tulyakov

ICLR 2021 Disentangled Recurrent Wasserstein Autoencoder Jun Han, Martin Renqiang Min, Ligong Han, Li Erran Li, Xuan Zhang

ICCV 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

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

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

CVPRW 2019 Unsupervised Domain Adaptation via Calibrating Uncertainties Ligong Han, Yang Zou, Ruijiang Gao, Lezi Wang, Dimitris N. Metaxas

WACV 2018 Learning Generative Models of Tissue Organization with Supervised GANs Ligong Han, Robert F. Murphy, Deva Ramanan