Liu, Weiyang

61 publications

ICLR 2025 Can Large Language Models Understand Symbolic Graphics Programs? Zeju Qiu, Weiyang Liu, Haiwen Feng, Zhen Liu, Tim Z. Xiao, Katherine M. Collins, Joshua B. Tenenbaum, Adrian Weller, Michael J. Black, Bernhard Schölkopf
CVPR 2025 ChatHuman: Chatting About 3D Humans with Tools Jing Lin, Yao Feng, Weiyang Liu, Michael J. Black
ICLR 2025 Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Zhen Liu, Tim Z. Xiao, Weiyang Liu, Yoshua Bengio, Dinghuai Zhang
TMLR 2025 Generating Symbolic World Models via Test-Time Scaling of Large Language Models Zhouliang Yu, Yuhuan Yuan, Tim Z. Xiao, Fuxiang Frank Xia, Jie Fu, Ge Zhang, Ge Lin, Weiyang Liu
ICLRW 2025 Generating Symbolic World Models via Test-Time Scaling of Large Language Models Zhouliang Yu, Yuhuan Yuan, Tim Z. Xiao, Fuxiang Frank Xia, Jie Fu, Ge Zhang, Ge Lin, Weiyang Liu
NeurIPS 2025 Reparameterized LLM Training via Orthogonal Equivalence Transformation Zeju Qiu, Simon Buchholz, Tim Z. Xiao, Maximilian Dax, Bernhard Schölkopf, Weiyang Liu
ICLRW 2025 Representational Alignment Supports Effective Teaching Ilia Sucholutsky, Katherine M. Collins, Maya Malaviya, Nori Jacoby, Weiyang Liu, Theodore Sumers, Michalis Korakakis, Umang Bhatt, Mark K Ho, Joshua B. Tenenbaum, Bradley C. Love, Zachary Pardos, Adrian Weller, Thomas L. Griffiths
ICML 2025 SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator Guoxuan Chen, Han Shi, Jiawei Li, Yihang Gao, Xiaozhe Ren, Yimeng Chen, Xin Jiang, Zhenguo Li, Weiyang Liu, Chao Huang
NeurIPS 2025 Speculative Jacobi-Denoising Decoding for Accelerating Autoregressive Text-to-Image Generation Yao Teng, Fu-Yun Wang, Xian Liu, Zhekai Chen, Han Shi, Yu Wang, Zhenguo Li, Weiyang Liu, Difan Zou, Xihui Liu
CVPR 2025 VERA: Explainable Video Anomaly Detection via Verbalized Learning of Vision-Language Models Muchao Ye, Weiyang Liu, Pan He
NeurIPS 2025 Value Gradient Guidance for Flow Matching Alignment Zhen Liu, Tim Z. Xiao, Carles Domingo-Enrich, Weiyang Liu, Dinghuai Zhang
TMLR 2025 Verbalized Machine Learning: Revisiting Machine Learning with Language Models Tim Z. Xiao, Robert Bamler, Bernhard Schölkopf, Weiyang Liu
AISTATS 2025 Your Finetuned Large Language Model Is Already a Powerful Out-of-Distribution Detector Andi Zhang, Tim Z. Xiao, Weiyang Liu, Robert Bamler, Damon Wischik
NeurIPS 2024 Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision Zhiqing Sun, Longhui Yu, Yikang Shen, Weiyang Liu, Yiming Yang, Sean Welleck, Chuang Gan
ICLR 2024 Ghost on the Shell: An Expressive Representation of General 3D Shapes Zhen Liu, Yao Feng, Yuliang Xiu, Weiyang Liu, Liam Paull, Michael J. Black, Bernhard Schölkopf
CVPR 2024 GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs Gege Gao, Weiyang Liu, Anpei Chen, Andreas Geiger, Bernhard Schölkopf
ICMLW 2024 In Defense of Structural Sparse Adapters for Concurrent LLM Serving Junda Su, Zirui Liu, Zeju Qiu, Weiyang Liu, Zhaozhuo Xu
ICMLW 2024 Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design Shengchao Liu, Liang Yan, Weitao Du, Weiyang Liu, Hongyu Guo, Christian Borgs, Jennifer T Chayes, Anima Anandkumar
ICLR 2024 MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu
ICLR 2024 Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization Weiyang Liu, Zeju Qiu, Yao Feng, Yuliang Xiu, Yuxuan Xue, Longhui Yu, Haiwen Feng, Zhen Liu, Juyeon Heo, Songyou Peng, Yandong Wen, Michael J. Black, Adrian Weller, Bernhard Schölkopf
TMLR 2024 Re-Thinking Inverse Graphics with Large Language Models Peter Kulits, Haiwen Feng, Weiyang Liu, Victoria Fernandez Abrevaya, Michael J. Black
ICMLW 2024 Verbalized Machine Learning: Revisiting Machine Learning with Language Models Tim Z. Xiao, Robert Bamler, Bernhard Schölkopf, Weiyang Liu
ICMLW 2024 Verbalized Machine Learning: Revisiting Machine Learning with Language Models Tim Z. Xiao, Robert Bamler, Bernhard Schölkopf, Weiyang Liu
NeurIPSW 2023 A Compact Representation for Bayesian Neural Networks by Removing Permutation Symmetry Tim Z. Xiao, Weiyang Liu, Robert Bamler
TMLR 2023 Continual Learning by Modeling Intra-Class Variation Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu, Adrian Weller, Weiyang Liu
NeurIPS 2023 Controlling Text-to-Image Diffusion by Orthogonal Finetuning Zeju Qiu, Weiyang Liu, Haiwen Feng, Yuxuan Xue, Yao Feng, Zhen Liu, Dan Zhang, Adrian Weller, Bernhard Schölkopf
ICLR 2023 Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap Weiyang Liu, Longhui Yu, Adrian Weller, Bernhard Schölkopf
UAI 2023 Human-in-the-Loop Mixup Katherine M. Collins, Umang Bhatt, Weiyang Liu, Vihari Piratla, Ilia Sucholutsky, Bradley Love, Adrian Weller
AISTATS 2023 Iterative Teaching by Data Hallucination Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf
ICLR 2023 MeshDiffusion: Score-Based Generative 3D Mesh Modeling Zhen Liu, Yao Feng, Michael J. Black, Derek Nowrouzezahrai, Liam Paull, Weiyang Liu
ICML 2023 Nonparametric Iterative Machine Teaching Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor Tsang, James Kwok
NeurIPS 2023 Nonparametric Teaching for Multiple Learners Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok
ICCV 2023 One-Shot Implicit Animatable Avatars with Model-Based Priors Yangyi Huang, Hongwei Yi, Weiyang Liu, Haofan Wang, Boxi Wu, Wenxiao Wang, Binbin Lin, Debing Zhang, Deng Cai
ICCV 2023 Pairwise Similarity Learning Is SimPLE Yandong Wen, Weiyang Liu, Yao Feng, Bhiksha Raj, Rita Singh, Adrian Weller, Michael J. Black, Bernhard Schölkopf
AISTATS 2022 Provable Lifelong Learning of Representations Xinyuan Cao, Weiyang Liu, Santosh Vempala
ICLR 2022 Pre-Training Molecular Graph Representation with 3D Geometry Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang
ICLRW 2022 Pre-Training Molecular Graph Representation with 3D Geometry Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang
ICLR 2022 SphereFace2: Binary Classification Is All You Need for Deep Face Recognition Yandong Wen, Weiyang Liu, Adrian Weller, Bhiksha Raj, Rita Singh
ECCV 2022 Structural Causal 3D Reconstruction Weiyang Liu, Zhen Liu, Liam Paull, Adrian Weller, Bernhard Schölkopf
CVPR 2022 Towards Principled Disentanglement for Domain Generalization Hanlin Zhang, Yi-Fan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric P. Xing
AISTATS 2021 Learning with Hyperspherical Uniformity Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller
NeurIPS 2021 Iterative Teaching by Label Synthesis Weiyang Liu, Zhen Liu, Hanchen Wang, Liam Paull, Bernhard Schölkopf, Adrian Weller
NeurIPS 2021 Locality Sensitive Teaching Zhaozhuo Xu, Beidi Chen, Chaojian Li, Weiyang Liu, Le Song, Yingyan Lin, Anshumali Shrivastava
CVPR 2021 Orthogonal Over-Parameterized Training Weiyang Liu, Rongmei Lin, Zhen Liu, James M. Rehg, Liam Paull, Li Xiong, Le Song, Adrian Weller
ICCV 2021 Self-Supervised 3D Face Reconstruction via Conditional Estimation Yandong Wen, Weiyang Liu, Bhiksha Raj, Rita Singh
ICML 2020 Angular Visual Hardness Beidi Chen, Weiyang Liu, Zhiding Yu, Jan Kautz, Anshumali Shrivastava, Animesh Garg, Animashree Anandkumar
ICMLW 2019 Angular Visual Hardness Beidi Chen, Weiyang Liu, Animesh Garg, Zhiding Yu, Anshumali Shrivastava, Anima Anandkumar
ICLR 2019 Disjoint Mapping Network for Cross-Modal Matching of Voices and Faces Yandong Wen, Mahmoud Al Ismail, Weiyang Liu, Bhiksha Raj, Rita Singh
NeurIPS 2019 Meta Architecture Search Albert Shaw, Wei Wei, Weiyang Liu, Le Song, Bo Dai
NeurIPS 2019 Neural Similarity Learning Weiyang Liu, Zhen Liu, James M. Rehg, Le Song
NeurIPS 2018 Coupled Variational Bayes via Optimization Embedding Bo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao, Le Song
NeurIPS 2018 Learning Towards Minimum Hyperspherical Energy Weiyang Liu, Rongmei Lin, Zhen Liu, Lixin Liu, Zhiding Yu, Bo Dai, Le Song
ECCV 2018 Simultaneous Edge Alignment and Learning Zhiding Yu, Weiyang Liu, Yang Zou, Chen Feng, Srikumar Ramalingam, B. V. K. Vijaya Kumar, Jan Kautz
ICML 2018 Towards Black-Box Iterative Machine Teaching Weiyang Liu, Bo Dai, Xingguo Li, Zhen Liu, James Rehg, Le Song
NeurIPS 2017 Deep Hyperspherical Learning Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhiding Yu, Bo Dai, Tuo Zhao, Le Song
ICML 2017 Iterative Machine Teaching Weiyang Liu, Bo Dai, Ahmad Humayun, Charlene Tay, Chen Yu, Linda B. Smith, James M. Rehg, Le Song
CVPR 2017 SphereFace: Deep Hypersphere Embedding for Face Recognition Weiyang Liu, Yandong Wen, Zhiding Yu, Ming Li, Bhiksha Raj, Le Song
AAAI 2016 Analysis-Synthesis Dictionary Learning for Universality-Particularity Representation Based Classification Meng Yang, Weiyang Liu, Weixin Luo, Linlin Shen
ICML 2016 Large-Margin SoftMax Loss for Convolutional Neural Networks Weiyang Liu, Yandong Wen, Zhiding Yu, Meng Yang
AAAI 2016 On Order-Constrained Transitive Distance Clustering Zhiding Yu, Weiyang Liu, Wenbo Liu, Yingzhen Yang, Ming Li, B. V. K. Vijaya Kumar
IJCAI 2015 Generalized Transitive Distance with Minimum Spanning Random Forest Zhiding Yu, Weiyang Liu, Wenbo Liu, Xi Peng, Zhuo Hui, B. V. K. Vijaya Kumar