Zhang, Tianyi

59 publications

NeurIPS 2025 70% Size, 100% Accuracy: Lossless LLM Compression for Efficient GPU Inference via Dynamic-Length Float (DFloat11) Tianyi Zhang, Mohsen Hariri, Shaochen Zhong, Vipin Chaudhary, Yang Sui, Xia Hu, Anshumali Shrivastava

AAAI 2025 Adaptive Merchant-Centric Risk Control via Unbiased Decision-Making and Dynamic Optimization in E-Commerce Xu Liu, Yiqiang Lu, Jian Liu, Tianyi Zhang, Weiqiang Wang, Qian Liu, Shuai Li

NeurIPS 2025 Breaking the Frozen Subspace: Importance Sampling for Low-Rank Optimization in LLM Pretraining Haochen Zhang, Junze Yin, Guanchu Wang, Zirui Liu, Lin Yang, Tianyi Zhang, Anshumali Shrivastava, Vladimir Braverman

NeurIPS 2025 Building 3D Representations and Generating Motions from a Single Image via Video-Generation Weiming Zhi, Ziyong Ma, Tianyi Zhang, Matthew Johnson-Roberson

ICLRW 2025 DOSE3 : Diffusion-Based Out-of-Distribution Detection on SE(3) Trajectories Hongzhe Cheng, Tianyou Zheng, Tianyi Zhang, Matthew Johnson-Roberson, Weiming Zhi

ICCV 2025 Dita: Scaling Diffusion Transformer for Generalist Vision-Language-Action Policy Zhi Hou, Tianyi Zhang, Yuwen Xiong, Haonan Duan, Hengjun Pu, Ronglei Tong, Chengyang Zhao, Xizhou Zhu, Yu Qiao, Jifeng Dai, Yuntao Chen

CVPR 2025 From Poses to Identity: Training-Free Person Re-Identification via Feature Centralization Chao Yuan, Guiwei Zhang, Changxiao Ma, Tianyi Zhang, Guanglin Niu

ICLRW 2025 Infinite Leagues Under the Sea: Realistic 3D Underwater Terrain Generation Augmented by Visual Foundation Models Tianyi Zhang, Weiming Zhi, Joshua G Mangelson, Matthew Johnson-Roberson

ICLR 2025 LeanQuant: Accurate and Scalable Large Language Model Quantization with Loss-Error-Aware Grid Tianyi Zhang, Anshumali Shrivastava

ICLRW 2025 Multi-Hypothesis Spatial Foundation Model: Rethinking and Decoupling Depth Ambiguity via Laplacian Visual Prompting Xiaohao Xu, Feng Xue, Xiang Li, Haowei Li, Shusheng Yang, Tianyi Zhang, Matthew Johnson-Roberson, Xiaonan Huang

CVPRW 2025 Neighbor-Based Feature and Index Enhancement for Person Re-Identification Chao Yuan, Tianyi Zhang, Guanglin Niu

NeurIPS 2025 One Filters All: A Generalist Filter for State Estimation Shiqi Liu, Wenhan Cao, Chang Liu, Zeyu He, Tianyi Zhang, Yinuo Wang, Shengbo Eben Li

ICCV 2025 Quanta Neural Networks: From Photons to Perception Varun Sundar, Tianyi Zhang, Sacha Jungerman, Mohit Gupta

ICLR 2025 Scalable Benchmarking and Robust Learning for Noise-Free Ego-Motion and 3D Reconstruction from Noisy Video Xiaohao Xu, Tianyi Zhang, Shibo Zhao, Xiang Li, Sibo Wang, Yongqi Chen, Ye Li, Bhiksha Raj, Matthew Johnson-Roberson, Sebastian Scherer, Xiaonan Huang

ICML 2025 Selective Prompt Anchoring for Code Generation Yuan Tian, Tianyi Zhang

ICML 2025 Sketch to Adapt: Fine-Tunable Sketches for Efficient LLM Adaptation Tianyi Zhang, Junda Su, Aditya Desai, Oscar Wu, Zhaozhuo Xu, Anshumali Shrivastava

TMLR 2025 Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models Yang Sui, Yu-Neng Chuang, Guanchu Wang, Jiamu Zhang, Tianyi Zhang, Jiayi Yuan, Hongyi Liu, Andrew Wen, Shaochen Zhong, Na Zou, Hanjie Chen, Xia Hu

ICML 2025 Uncertainty-Based Extensible Codebook for Discrete Federated Learning in Heterogeneous Data Silos Tianyi Zhang, Yu Cao, Dianbo Liu

AAAI 2024 Compositional Inversion for Stable Diffusion Models Xulu Zhang, Xiao-Yong Wei, Jinlin Wu, Tianyi Zhang, Zhaoxiang Zhang, Zhen Lei, Qing Li

CVPR 2024 DL3DV-10K: A Large-Scale Scene Dataset for Deep Learning-Based 3D Vision Lu Ling, Yichen Sheng, Zhi Tu, Wentian Zhao, Cheng Xin, Kun Wan, Lantao Yu, Qianyu Guo, Zixun Yu, Yawen Lu, Xuanmao Li, Xingpeng Sun, Rohan Ashok, Aniruddha Mukherjee, Hao Kang, Xiangrui Kong, Gang Hua, Tianyi Zhang, Bedrich Benes, Aniket Bera

NeurIPSW 2024 Embodied-RAG: General Non-Parametric Embodied Memory for Retrieval and Generation Quanting Xie, So Yeon Min, Tianyi Zhang, Kedi Xu, Aarav Bajaj, Russ Salakhutdinov, Matthew Johnson-Roberson, Yonatan Bisk

ECML-PKDD 2024 GraphRPM: Risk Pattern Mining on Industrial Large Attributed Graphs Sheng Tian, Xintan Zeng, Yifei Hu, Baokun Wang, Yongchao Liu, Yue Jin, Changhua Meng, Chuntao Hong, Tianyi Zhang, Weiqiang Wang

ICML 2024 GroupCover: A Secure, Efficient and Scalable Inference Framework for On-Device Model Protection Based on TEEs Zheng Zhang, Na Wang, Ziqi Zhang, Yao Zhang, Tianyi Zhang, Jianwei Liu, Ye Wu

NeurIPS 2024 KV Cache Is 1 Bit per Channel: Efficient Large Language Model Inference with Coupled Quantization Tianyi Zhang, Jonah Yi, Zhaozhuo Xu, Anshumali Shrivastava

AAAI 2024 Multi-Modality Affinity Inference for Weakly Supervised 3D Semantic Segmentation Xiawei Li, Qingyuan Xu, Jing Zhang, Tianyi Zhang, Qian Yu, Lu Sheng, Dong Xu

NeurIPS 2024 NoMAD-Attention: Efficient LLM Inference on CPUs Through Multiply-Add-Free Attention Tianyi Zhang, Jonah Yi, Bowen Yao, Zhaozhuo Xu, Anshumali Shrivastava

WACV 2024 Patch-Based Selection and Refinement for Early Object Detection Tianyi Zhang, Kishore Kasichainula, Yaoxin Zhuo, Baoxin Li, Jae-Sun Seo, Yu Cao

ECCV 2024 Robust Incremental Structure-from-Motion with Hybrid Features Shaohui Liu, Yidan Gao, Tianyi Zhang, Rémi Pautrat, Johannes L Schönberger, Viktor Larsson, Marc Pollefeys

ECCVW 2024 Soybean Pod and Seed Counting in Both Outdoor Fields and Indoor Laboratories Using Unions of Deep Neural Networks Tianyou Jiang, Mingshun Shao, Tianyi Zhang, Xiaoyu Liu, Qun Yu

NeurIPS 2024 Stronger than You Think: Benchmarking Weak Supervision on Realistic Tasks Tianyi Zhang, Linrong Cai, Jeffrey Li, Nicholas Roberts, Neel Guha, Frederic Sala

AAAI 2024 Transformer-Based Selective Super-Resolution for Efficient Image Refinement Tianyi Zhang, Kishore Kasichainula, Yaoxin Zhuo, Baoxin Li, Jae-Sun Seo, Yu Cao

NeurIPS 2023 AlpacaFarm: A Simulation Framework for Methods That Learn from Human Feedback Yann Dubois, Chen Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B Hashimoto

ICML 2023 Coder Reviewer Reranking for Code Generation Tianyi Zhang, Tao Yu, Tatsunori Hashimoto, Mike Lewis, Wen-Tau Yih, Daniel Fried, Sida Wang

ICML 2023 DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation Yuhang Lai, Chengxi Li, Yiming Wang, Tianyi Zhang, Ruiqi Zhong, Luke Zettlemoyer, Wen-Tau Yih, Daniel Fried, Sida Wang, Tao Yu

ICML 2023 Efficient Graph Field Integrators Meet Point Clouds Krzysztof Marcin Choromanski, Arijit Sehanobish, Han Lin, Yunfan Zhao, Eli Berger, Tetiana Parshakova, Alvin Pan, David Watkins, Tianyi Zhang, Valerii Likhosherstov, Somnath Basu Roy Chowdhury, Kumar Avinava Dubey, Deepali Jain, Tamas Sarlos, Snigdha Chaturvedi, Adrian Weller

NeurIPSW 2023 FedGKD: Unleashing the Power of Collaboration in Federated Graph Neural Networks Qiying Pan, Ruofan Wu, Tengfei Liu, Tianyi Zhang, Yifei Zhu, Weiqiang Wang

UAI 2023 Graph Self-Supervised Learning via Proximity Distribution Minimization Tianyi Zhang, Zhenwei Dai, Zhaozhuo Xu, Anshumali Shrivastava

TMLR 2023 Holistic Evaluation of Language Models Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D Manning, Christopher Re, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel Orr, Lucia Zheng, Mert Yuksekgonul, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Andrew Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda

NeurIPS 2023 Neural Frailty Machine: Beyond Proportional Hazard Assumption in Neural Survival Regressions Ruofan Wu, Jiawei Qiao, Mingzhe Wu, Wen Yu, Ming Zheng, Tengfei Liu, Tianyi Zhang, Weiqiang Wang

NeurIPSW 2023 Privacy-Preserving Design of Graph Neural Networks with Applications to Vertical Federated Learning Ruofan Wu, Mingyang Zhang, Lingjuan Lyu, Xiaolong Xu, Xiuquan Hao, Xinyi Fu, Tengfei Liu, Tianyi Zhang, Weiqiang Wang

IJCAI 2023 SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs Sheng Tian, Jihai Dong, Jintang Li, Wenlong Zhao, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen

NeurIPS 2022 Decentralized Training of Foundation Models in Heterogeneous Environments Binhang Yuan, Yongjun He, Jared Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Ré, Ce Zhang

ICML 2022 From Block-Toeplitz Matrices to Differential Equations on Graphs: Towards a General Theory for Scalable Masked Transformers Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamas Sarlos, Adrian Weller, Thomas Weingarten

ACML 2022 Multi-Class Classification from Multiple Unlabeled Datasets with Partial Risk Regularization Yuting Tang, Nan Lu, Tianyi Zhang, Masashi Sugiyama

NeurIPS 2022 Retaining Knowledge for Learning with Dynamic Definition Zichang Liu, Benjamin Coleman, Tianyi Zhang, Anshumali Shrivastava

COLT 2021 Learning to Stop with Surprisingly Few Samples Daniel Russo, Assaf Zeevi, Tianyi Zhang

AAAI 2021 Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection Dongbo Xi, Bowen Song, Fuzhen Zhuang, Yongchun Zhu, Shuai Chen, Tianyi Zhang, Yuan Qi, Qing He

CVPR 2021 PSRR-MaxpoolNMS: Pyramid Shifted MaxpoolNMS with Relationship Recovery Tianyi Zhang, Jie Lin, Peng Hu, Bin Zhao, Mohamed M. Sabry Aly

ICLR 2021 Revisiting Few-Sample BERT Fine-Tuning Tianyi Zhang, Felix Wu, Arzoo Katiyar, Kilian Q Weinberger, Yoav Artzi

ACML 2020 A One-Step Approach to Covariate Shift Adaptation Tianyi Zhang, Ikko Yamane, Nan Lu, Masashi Sugiyama

ICLR 2020 BERTScore: Evaluating Text Generation with BERT Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, Yoav Artzi

NeurIPS 2020 Demystifying Orthogonal Monte Carlo and Beyond Han Lin, Haoxian Chen, Krzysztof M Choromanski, Tianyi Zhang, Clement Laroche

NeurIPS 2020 Identifying Mislabeled Data Using the Area Under the Margin Ranking Geoff Pleiss, Tianyi Zhang, Ethan Elenberg, Kilian Q. Weinberger

AISTATS 2020 Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach Nan Lu, Tianyi Zhang, Gang Niu, Masashi Sugiyama

ECCV 2020 Splitting vs. Merging: Mining Object Regions with Discrepancy and Intersection Loss for Weakly Supervised Semantic Segmentation Tianyi Zhang, Guosheng Lin, Weide Liu, Jianfei Cai, Alex Kot

ICML 2019 SWALP : Stochastic Weight Averaging in Low Precision Training Guandao Yang, Tianyi Zhang, Polina Kirichenko, Junwen Bai, Andrew Gordon Wilson, Chris De Sa

ICML 2019 Simplifying Graph Convolutional Networks Felix Wu, Amauri Souza, Tianyi Zhang, Christopher Fifty, Tao Yu, Kilian Weinberger

MLJ 2019 Stochastic Gradient Hamiltonian Monte Carlo with Variance Reduction for Bayesian Inference Zhize Li, Tianyi Zhang, Shuyu Cheng, Jun Zhu, Jian Li