Kangning Liu

According to our database, Kangning Liu authored at least 28 papers between 2021 and 2026.

Collaborative distances:

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

2026

SNCE: Geometry-Aware Supervision for Scalable Discrete Image Generation.

Shufan Li, Jiuxiang Gu, Kangning Liu, Zhe Lin, Aditya Grover, Jason Kuen

CoRR, March, 2026

LaViDa-R1: Advancing Reasoning for Unified Multimodal Diffusion Language Models.

Shufan Li, Yuchen Zhu, Jiuxiang Gu, Kangning Liu, Zhe Lin, Yongxin Chen, Molei Tao, Aditya Grover, Jason Kuen

CoRR, February, 2026

2025

Sparse-LaViDa: Sparse Multimodal Discrete Diffusion Language Models.

Shufan Li, Jiuxiang Gu, Kangning Liu, Zhe Lin, Zijun Wei, Aditya Grover, Jason Kuen

CoRR, December, 2025

VGent: Visual Grounding via Modular Design for Disentangling Reasoning and Prediction.

Weitai Kang, Jason Kuen, Mengwei Ren, Zijun Wei, Yan Yan, Kangning Liu

CoRR, December, 2025

Multi-Objective optimization of courtyard block design: balancing thermal comfort and cooling efficiency using NSGA-III.

Hehong Ma, Kangning Liu

Signal Image Video Process., November, 2025

Lavida-O: Elastic Large Masked Diffusion Models for Unified Multimodal Understanding and Generation.

Shufan Li, Jiuxiang Gu, Kangning Liu, Zhe Lin, Zijun Wei, Aditya Grover, Jason Kuen

CoRR, September, 2025

Agentic Lybic: Multi-Agent Execution System with Tiered Reasoning and Orchestration.

Liangxuan Guo, Bin Zhu, Qingqian Tao, Kangning Liu, Xun Zhao, Xianzhe Qin, Jin Gao, Guangfu Hao

CoRR, September, 2025

Refer to Anything with Vision-Language Prompts.

Shengcao Cao, Zijun Wei, Jason Kuen, Kangning Liu, Lingzhi Zhang, Jiuxiang Gu, Hyunjoon Jung, Liang-Yan Gui, Yu-Xiong Wang

CoRR, June, 2025

Learn, Denoise, and Discover: A guide to deep denoising with an application to electron microscopy.

Sreyas Mohan, Kangning Liu, Peter A. Crozier, Carlos Fernandez-Granda

IEEE Signal Process. Mag., March, 2025

Refer to Any Segmentation Mask Group with Vision-Language Prompts.

Shengcao Cao, Zijun Wei, Jason Kuen, Kangning Liu, Lingzhi Zhang, Jiuxiang Gu, Hyunjoon Jung, Liang-Yan Gui, Yu-Xiong Wang

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

conSAMme: Achieving Consistent Segmentations with SAM.

Josh Myers-Dean, Kangning Liu, Brian L. Price, Yifei Fan, Jason Kuen, Danna Gurari

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

2024

Social Power Antecedents of Knowledge Sharing in Project-Oriented Online Communities.

Jianyao Jia, Guofeng Ma, Hongyang Li, Jiyong Ding, Kangning Liu

IEEE Trans. Engineering Management, 2024

Quantifying impairment and disease severity using AI models trained on healthy subjects.

Boyang Yu, Aakash Kaku, Kangning Liu, Avinash Parnandi, Emily Fokas, Anita Venkatesan, Natasha Pandit, Rajesh Ranganath, Heidi M. Schambra, Carlos Fernandez-Granda

npj Digit. Medicine, 2024

A machine learning framework for intelligent development of Ultra-High performance concrete (UHPC): From dataset cleaning to performance predicting.

Liuliu Xu, Dingqiang Fan, Kangning Liu, Wangyang Xu, Rui Yu

Expert Syst. Appl., 2024

AutoGLM: Autonomous Foundation Agents for GUIs.

Xiao Liu, Bo Qin, Dongzhu Liang, Guang Dong, Hanyu Lai, Hanchen Zhang, Hanlin Zhao, Iat Long Iong, Jiadai Sun, Jiaqi Wang, Junjie Gao, Junjun Shan, Kangning Liu, Shudan Zhang, Shuntian Yao, Siyi Cheng, Wentao Yao, Wenyi Zhao, Xinghan Liu, Xinyi Liu, Xinying Chen, Xinyue Yang, Yang Yang, Yifan Xu, Yu Yang, Yujia Wang, Yulin Xu, Zehan Qi, Yuxiao Dong, Jie Tang

CoRR, 2024

Multi-modal AI for comprehensive breast cancer prognostication.

Jan Witowski, Ken Zeng, Joseph Cappadona, Jailan Elayoubi, Elena Diana Chiru, Nancy Chan, Young-Joon Kang, Frederick Howard, Irina Ostrovnaya, Carlos Fernandez-Granda, Freya Schnabel, Ugur Ozerdem, Kangning Liu, Zoe Steinsnyder, Nitya Thakore, Mohammad Sadic, Frank Yeung, Elisa Liu, Theodore Hill, Benjamin Swett, Danielle Rigau, Andrew Clayburn, Valerie Speirs, Marcus Vetter, Lina Sojak, Simone Muenst Soysal, Daniel Baumhoer, Khalil Choucair, Yu Zong, Lina Daoud, Anas Saad, Waleed Abdulsattar, Rafic Beydoun, Jia-Wern Pan, Haslina Makmur, Soo-Hwang Teo, Linda Ma Pak, Victor Angel, Dovile Zilenaite-Petrulaitiene, Arvydas Laurinavicius, Natalie Klar, Brian Piening, Carlo Bifulco, Sun-Young Jun, Jae Pak Yi, Su Hyun Lim, Adam Brufsky, Francisco J. Esteva, Lajos Pusztai, Yann LeCun, Krzysztof J. Geras

CoRR, 2024

Uncertainty-aware Fine-tuning of Segmentation Foundation Models.

Kangning Liu, Brian L. Price, Jason Kuen, Yifei Fan, Zijun Wei, Luis Figueroa, Krzysztof J. Geras, Carlos Fernandez-Granda

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Research on Rice Fields Extraction by NDVI Difference Method Based on Sentinel Data.

Jinglian Tian, Yongzhong Tian, Yan Cao, Wenhao Wan, Kangning Liu

Sensors, July, 2023

Controllable One-Shot Face Video Synthesis With Semantic Aware Prior.

Kangning Liu, Yu-Chuan Su, Wei Hong, Ruijin Cang, Xuhui Jia

CoRR, 2023

Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning.

Kangning Liu, Weicheng Zhu, Yiqiu Shen, Sheng Liu, Narges Razavian, Krzysztof J. Geras, Carlos Fernandez-Granda

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

2022

Are All Losses Created Equal: A Neural Collapse Perspective.

Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu

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

StrokeRehab: A Benchmark Dataset for Sub-second Action Identification.

Aakash Kaku, Kangning Liu, Avinash Parnandi, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Anita Venkatesan, Audre Wirtanen, Natasha Pandit, Heidi M. Schambra, Carlos Fernandez-Granda

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

Adaptive Early-Learning Correction for Segmentation from Noisy Annotations.

Sheng Liu, Kangning Liu, Weicheng Zhu, Yiqiu Shen, Carlos Fernandez-Granda

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

2021

An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization.

Yiqiu Shen, Nan Wu, Jason Phang, Jungkyu Park, Kangning Liu, Sudarshini Tyagi, Laura Heacock, Sungheon Gene Kim, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras

Medical Image Anal., 2021

Sequence-to-Sequence Modeling for Action Identification at High Temporal Resolution.

Aakash Kaku, Kangning Liu, Avinash Parnandi, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Anita Venkatesan, Audre Wirtanen, Natasha Pandit, Heidi M. Schambra, Carlos Fernandez-Granda

CoRR, 2021

Cramér-Rao bound-informed training of neural networks for quantitative MRI.

Xiaoxia Zhang, Quentin Duchemin, Kangning Liu, Sebastian Flassbeck, Cem Gultekin, Carlos Fernandez-Granda, Jakob Assländer

CoRR, 2021

Unsupervised Multimodal Video-to-Video Translation via Self-Supervised Learning.

Kangning Liu, Shuhang Gu, Andrés Romero, Radu Timofte

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis.

Kangning Liu, Yiqiu Shen, Nan Wu, Jakub Piotr Chledowski, Carlos Fernandez-Granda, Krzysztof J. Geras

Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021