Tianlong Chen

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 260

Top Venues

Publications

Dawei Li, Zhen Tan, Tianlong Chen, Huan Liu
Contextualization Distillation from Large Language Model for Knowledge Graph Completion. CoRR (2024)
Zhiyuan Wang, Jinhao Duan, Chenxi Yuan, Qingyu Chen, Tianlong Chen, Huaxiu Yao, Yue Zhang, Ren Wang, Kaidi Xu, Xiaoshuang Shi
Word-Sequence Entropy: Towards Uncertainty Estimation in Free-Form Medical Question Answering Applications and Beyond. CoRR (2024)
Dawei Li, Zhen Tan, Tianlong Chen, Huan Liu
Contextualization Distillation from Large Language Model for Knowledge Graph Completion. EACL (Findings) (2024)
Chi-Yang Hsu, Kyle Cox, Jiawei Xu, Zhen Tan, Tianhua Zhai, Mengzhou Hu, Dexter Pratt, Tianlong Chen, Ziniu Hu, Ying Ding
Thought Graph: Generating Thought Process for Biological Reasoning. WWW (Companion Volume) (2024)
Yihua Zhang, Pingzhi Li, Junyuan Hong, Jiaxiang Li, Yimeng Zhang, Wenqing Zheng, Pin-Yu Chen, Jason D. Lee, Wotao Yin, Mingyi Hong, Zhangyang Wang, Sijia Liu, Tianlong Chen
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark. CoRR (2024)
Ajay Jaiswal, Bodun Hu, Lu Yin, Yeonju Ro, Shiwei Liu, Tianlong Chen, Aditya Akella
FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping. CoRR (2024)
Zhen Tan, Daize Dong, Xinyu Zhao, Jie Peng, Yu Cheng, Tianlong Chen
DLO: Dynamic Layer Operation for Efficient Vertical Scaling of LLMs. CoRR (2024)
Arinbjorn Kolbeinsson, Kyle O'Brien, Tianjin Huang, Shanghua Gao, Shiwei Liu, Jonathan Richard Schwarz, Anurag Vaidya, Faisal Mahmood, Marinka Zitnik, Tianlong Chen, Thomas Hartvigsen
Composable Interventions for Language Models. CoRR (2024)
Xinnan Zhang, Jialin Wu, Junyi Xie, Tianlong Chen, Kaixiong Zhou
Benchmark on Drug Target Interaction Modeling from a Structure Perspective. CoRR (2024)
Shwai He, Tianlong Chen
RESSA: Repair Sparse Vision-Language Models via Sparse Cross-Modality Adaptation. CoRR (2024)
Tianjin Huang, Meng Fang, Li Shen, Fan Liu, Yulong Pei, Mykola Pechenizkiy, Shiwei Liu, Tianlong Chen
(PASS) Visual Prompt Locates Good Structure Sparsity through a Recurrent HyperNetwork. CoRR (2024)
Zhen Tan, Jie Peng, Tianlong Chen, Huan Liu
Tuning-Free Accountable Intervention for LLM Deployment - A Metacognitive Approach. CoRR (2024)
Zhen Tan, Chengshuai Zhao, Raha Moraffah, Yifan Li, Yu Kong, Tianlong Chen, Huan Liu
The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative. CoRR (2024)
Jinhao Duan, Shiqi Wang, James Diffenderfer, Lichao Sun, Tianlong Chen, Bhavya Kailkhura, Kaidi Xu
ReTA: Recursively Thinking Ahead to Improve the Strategic Reasoning of Large Language Models. NAACL-HLT (2024)
Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chao Zhang, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao
TrustLLM: Trustworthiness in Large Language Models. CoRR (2024)
Aditi Khandelwal, Harman Singh, Hengrui Gu, Tianlong Chen, Kaixiong Zhou
Cross-Lingual Multi-Hop Knowledge Editing - Benchmarks, Analysis and a Simple Contrastive Learning based Approach. CoRR (2024)
Zhen Tan, Chengshuai Zhao, Raha Moraffah, Yifan Li, Song Wang, Jundong Li, Tianlong Chen, Huan Liu
"Glue pizza and eat rocks" - Exploiting Vulnerabilities in Retrieval-Augmented Generative Models. CoRR (2024)
Dawei Li, Shu Yang, Zhen Tan, Jae Young Baik, Sukwon Yun, Joseph Lee, Aaron Chacko, Bojian Hou, Duy Duong-Tran, Ying Ding, Huan Liu, Li Shen, Tianlong Chen
DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer's Disease Questions with Scientific Literature. CoRR (2024)
Song Wang, Zhen Tan, Xinyu Zhao, Tianlong Chen, Huan Liu, Jundong Li
GraphRCG: Self-conditioned Graph Generation via Bootstrapped Representations. CoRR (2024)
Guanjie Chen, Xinyu Zhao, Tianlong Chen, Yu Cheng
MoE-RBench: Towards Building Reliable Language Models with Sparse Mixture-of-Experts. CoRR (2024)
Guibin Zhang, Xiangguo Sun, Yanwei Yue, Kun Wang, Tianlong Chen, Shirui Pan
Graph Sparsification via Mixture of Graphs. CoRR (2024)
Tiejin Chen, Longchao Da, Huixue Zhou, Pingzhi Li, Kaixiong Zhou, Tianlong Chen, Hua Wei
Privacy-preserving Fine-tuning of Large Language Models through Flatness. CoRR (2024)
Guibin Zhang, Yanwei Yue, Kun Wang, Junfeng Fang, Yongduo Sui, Kai Wang, Yuxuan Liang, Dawei Cheng, Shirui Pan, Tianlong Chen
Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness. CoRR (2024)
Chi-Yang Hsu, Kyle Cox, Jiawei Xu, Zhen Tan, Tianhua Zhai, Mengzhou Hu, Dexter Pratt, Tianlong Chen, Ziniu Hu, Ying Ding
Thought Graph: Generating Thought Process for Biological Reasoning. CoRR (2024)
Yifan Li, Anh Dao, Wentao Bao, Zhen Tan, Tianlong Chen, Huan Liu, Yu Kong
Facial Affective Behavior Analysis with Instruction Tuning. CoRR (2024)
Taishi Nakamura, Mayank Mishra, Simone Tedeschi, Yekun Chai, Jason T. Stillerman, Felix Friedrich, Prateek Yadav, Tanmay Laud, Minh Chien Vu, Terry Yue Zhuo, Diganta Misra, Ben Bogin, Xuan-Son Vu, Marzena Karpinska, Arnav Varma Dantuluri, Wojciech Kusa, Tommaso Furlanello, Rio Yokota, Niklas Muennighoff, Suhas Pai, Tosin P. Adewumi, Veronika Laippala, Xiaozhe Yao, Adalberto Junior, Alpay Ariyak, Aleksandr Drozd, Jordan Clive, Kshitij Gupta, Liangyu Chen, Qi Sun, Ken Tsui, Noah Persaud, Nour Moustafa-Fahmy, Tianlong Chen, Mohit Bansal, Nicolo Monti, Tai Dang, Ziyang Luo, Tien-Tung Bui, Roberto Navigli, Virendra Mehta, Matthew Blumberg, Victor May, Huu Nguyen, Sampo Pyysalo
Aurora-M: The First Open Source Multilingual Language Model Red-teamed according to the U.S. Executive Order. CoRR (2024)
Xuxi Chen, Zhendong Wang, Daouda Sow, Junjie Yang, Tianlong Chen, Yingbin Liang, Mingyuan Zhou, Zhangyang Wang
Take the Bull by the Horns: Hard Sample-Reweighted Continual Training Improves LLM Generalization. CoRR (2024)
Pingzhi Li, Xiaolong Jin, Yu Cheng, Tianlong Chen
Examining Post-Training Quantization for Mixture-of-Experts: A Benchmark. CoRR (2024)
Tianlong Chen, Zhenyu Zhang, Hanrui Wang, Jiaqi Gu, Zirui Li, David Z. Pan, Frederic T. Chong, Song Han, Zhangyang Wang
QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum Circuits. CoRR (2024)
Zhen Tan, Tianlong Chen, Zhenyu Zhang, Huan Liu
Sparsity-Guided Holistic Explanation for LLMs with Interpretable Inference-Time Intervention. AAAI (2024)
Jinhao Duan, Renming Zhang, James Diffenderfer, Bhavya Kailkhura, Lichao Sun, Elias Stengel-Eskin, Mohit Bansal, Tianlong Chen, Kaidi Xu
GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations. CoRR (2024)
Lichi Li, Zainul Abi Din, Zhen Tan, Sam London, Tianlong Chen, Ajay H. Daptardar
MerRec: A Large-scale Multipurpose Mercari Dataset for Consumer-to-Consumer Recommendation Systems. CoRR (2024)
Xinyu Zhao, Xuxi Chen, Yu Cheng, Tianlong Chen
Sparse MoE with Language Guided Routing for Multilingual Machine Translation. ICLR (2024)
Bernardo Consoli, Xizhi Wu, Song Wang, Xinyu Zhao, Yanshan Wang, Justin F. Rousseau, Tom Hartvigsen, Li Shen, Huanmei Wu, Yifan Peng, Qi Long, Tianlong Chen, Ying Ding
SDoH-GPT: Using Large Language Models to Extract Social Determinants of Health (SDoH). CoRR (2024)
Sukwon Yun, Jie Peng, Alexandro E. Trevino, Chanyoung Park, Tianlong Chen
Mew: Multiplexed Immunofluorescence Image Analysis through an Efficient Multiplex Network. CoRR (2024)
Pingzhi Li, Zhenyu Zhang, Prateek Yadav, Yi-Lin Sung, Yu Cheng, Mohit Bansal, Tianlong Chen
Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy. ICLR (2024)
Pingzhi Li, Junyu Liu, Hanrui Wang, Tianlong Chen
Hybrid Quantum-Classical Scheduling for Accelerating Neural Network Training with Newton's Gradient Descent. CoRR (2024)
Tianlong Chen, Kaixiong Zhou, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study. IEEE Trans. Pattern Anal. Mach. Intell. 45 (3) (2023)
Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark W. Barrett, Zhangyang Wang, Beidi Chen
O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. CoRR (2023)
Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy
Enhancing Adversarial Training via Reweighting Optimization Trajectory. ECML/PKDD (1) (2023)
Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Kumar Jaiswal, Zhangyang Wang
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! ICLR (2023)
Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Tommi Kärkkäinen, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. ICLR (2023)
Zhenglun Kong, Haoyu Ma, Geng Yuan, Mengshu Sun, Yanyue Xie, Peiyan Dong, Xin Meng, Xuan Shen, Hao Tang, Minghai Qin, Tianlong Chen, Xiaolong Ma, Xiaohui Xie, Zhangyang Wang, Yanzhi Wang
Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training. AAAI (2023)
Junjie Yang, Tianlong Chen, Mingkang Zhu, Fengxiang He, Dacheng Tao, Yingbin Liang, Zhangyang Wang
Learning to Generalize Provably in Learning to Optimize. AISTATS (2023)
Zhangheng Li, Tianlong Chen, Linyi Li, Bo Li, Zhangyang Wang
Can Pruning Improve Certified Robustness of Neural Networks? Trans. Mach. Learn. Res. 2023 (2023)
Xuxi Chen, Nelson Vadori, Tianlong Chen, Zhangyang Wang
Learning to Optimize Differentiable Games. ICML (2023)
Ajay Jaiswal, Tianlong Chen, Justin F. Rousseau, Yifan Peng, Ying Ding, Zhangyang Wang
Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances. WACV (2023)
Chaobo Li, Xiaokang Peng, Wei Shang, Zou Yuhan, Tianlong Chen
Formation Control of Spacecraft Based on SE(3) With Asymmetric Saturated Input. IEEE Access 11 (2023)
Haotao Wang, Tianlong Chen, Zhangyang Wang, Kede Ma
Troubleshooting image segmentation models with human-in-the-loop. Mach. Learn. 112 (3) (2023)
Tianjin Huang, Tianlong Chen, Zhangyang Wang, Shiwei Liu
The Counterattack of CNNs in Self-Supervised Learning: Larger Kernel Size might be All You Need. CoRR (2023)
Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models. CoRR (2023)
Xuxi Chen, Tianlong Chen, Weizhu Chen, Ahmed Hassan Awadallah, Zhangyang Wang, Yu Cheng
DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models. ACL (1) (2023)
Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang Wang, Sijia Liu
Robust Mixture-of-Expert Training for Convolutional Neural Networks. ICCV (2023)
Pingzhi Li, Zhenyu Zhang, Prateek Yadav, Yi-Lin Sung, Yu Cheng, Mohit Bansal, Tianlong Chen
Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy. CoRR (2023)
Wenyan Cong, Hanxue Liang, Peihao Wang, Zhiwen Fan, Tianlong Chen, Mukund Varma T, Yi Wang, Zhangyang Wang
Enhancing NeRF akin to Enhancing LLMs: Generalizable NeRF Transformer with Mixture-of-View-Experts. ICCV (2023)
Tianlong Chen, Zhenyu Zhang, Ajay Kumar Jaiswal, Shiwei Liu, Zhangyang Wang
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers. ICLR (2023)
Yan Han, Yuning You, Wenqing Zheng, Scott Hoang, Tianxin Wei, Majdi Hassan, Tianlong Chen, Ying Ding, Yang Shen, Zhangyang Wang
Graph Contrastive Learning: An Odyssey towards Generalizable, Scalable and Principled Representation Learning on Graphs. IEEE Data Eng. Bull. 46 (2) (2023)
Zhangheng Li, Yu Gong, Zhenyu Zhang, Xingyun Xue, Tianlong Chen, Yi Liang, Bo Yuan, Zhangyang Wang
Accelerable Lottery Tickets with the Mixed-Precision Quantization. CVPR Workshops (2023)
Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy
Enhancing Adversarial Training via Reweighting Optimization Trajectory. CoRR (2023)
Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication. ICML (2023)
Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Zhangyang Wang
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter. CoRR (2023)
Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication. CoRR (2023)
Mukund Varma T, Peihao Wang, Xuxi Chen, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang
Is Attention All That NeRF Needs? ICLR (2023)
Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Jaiswal, Zhangyang Wang
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! CoRR (2023)
Junjie Yang, Xuxi Chen, Tianlong Chen, Zhangyang Wang, Yingbin Liang
M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation. ICLR (2023)
Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang Wang, Sijia Liu
Robust Mixture-of-Expert Training for Convolutional Neural Networks. CoRR (2023)
Shiwei Liu, Yuesong Tian, Tianlong Chen, Li Shen
Don't Be So Dense: Sparse-to-Sparse GAN Training Without Sacrificing Performance. Int. J. Comput. Vis. 131 (10) (2023)
Junjie Yang, Tianlong Chen, Mingkang Zhu, Fengxiang He, Dacheng Tao, Yingbin Liang, Zhangyang Wang
Learning to Generalize Provably in Learning to Optimize. CoRR (2023)
Yun Zhu, Nevan Wichers, Chu-Cheng Lin, Xinyi Wang, Tianlong Chen, Lei Shu, Han Lu, Canoee Liu, Liangchen Luo, Jindong Chen, Lei Meng
SiRA: Sparse Mixture of Low Rank Adaptation. CoRR (2023)
Zhen Tan, Tianlong Chen, Zhenyu Zhang, Huan Liu
Sparsity-Guided Holistic Explanation for LLMs with Interpretable Inference-Time Intervention. CoRR (2023)
Junjie Yang, Tianlong Chen, Xuxi Chen, Zhangyang Wang, Yingbin Liang
Rethinking PGD Attack: Is Sign Function Necessary? CoRR (2023)
Junjie Yang, Xuxi Chen, Tianlong Chen, Zhangyang Wang, Yingbin Liang
M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation. CoRR (2023)
Tianlong Chen, Xuxi Chen, Xianzhi Du, Abdullah Rashwan, Fan Yang, Huizhong Chen, Zhangyang Wang, Yeqing Li
AdaMV-MoE: Adaptive Multi-Task Vision Mixture-of-Experts. ICCV (2023)
Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Zhangyang Wang
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter. NeurIPS (2023)
Yushi Huang, Ruihao Gong, Jing Liu, Tianlong Chen, Xianglong Liu
TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models. CoRR (2023)
Tianlong Chen, Zhenyu Zhang, Ajay Jaiswal, Shiwei Liu, Zhangyang Wang
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers. CoRR (2023)
Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
Graph Domain Adaptation via Theory-Grounded Spectral Regularization. ICLR (2023)
Tianlong Chen, Chengyue Gong, Daniel Jesus Diaz, Xuxi Chen, Jordan Tyler Wells, Qiang Liu, Zhangyang Wang, Andrew D. Ellington, Alex Dimakis, Adam R. Klivans
HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing. ICLR (2023)
Tianlong Chen, Zhenyu Zhang, Hanrui Wang, Jiaqi Gu, Zirui Li, David Z. Pan, Frederic T. Chong, Song Han, Zhangyang Wang
QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum Circuits. QCE (2023)
Wenyan Cong, Hanxue Liang, Peihao Wang, Zhiwen Fan, Tianlong Chen, Mukund Varma T, Yi Wang, Zhangyang Wang
Enhancing NeRF akin to Enhancing LLMs: Generalizable NeRF Transformer with Mixture-of-View-Experts. CoRR (2023)
Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark W. Barrett, Zhangyang Wang, Beidi Chen
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. NeurIPS (2023)
Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models. ICML (2023)
Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen
Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective. CoRR (2023)
Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. CoRR (2022)
Yuning You, Yue Cao, Tianlong Chen, Zhangyang Wang, Yang Shen
Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How. ICLR (2022)
Shixing Yu, Tianlong Chen, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Liu, Zhangyang Wang
Unified Visual Transformer Compression. ICLR (2022)
Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang
Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning. Trans. Mach. Learn. Res. 2022 (2022)
Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu
Advancing Model Pruning via Bi-level Optimization. CoRR (2022)
Tianlong Chen, Peihao Wang, Zhiwen Fan, Zhangyang Wang
Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations. CoRR (2022)
Wenqing Zheng, Tianlong Chen, Ting-Kuei Hu, Zhangyang Wang
Symbolic Learning to Optimize: Towards Interpretability and Scalability. CoRR (2022)
Zhenglun Kong, Haoyu Ma, Geng Yuan, Mengshu Sun, Yanyue Xie, Peiyan Dong, Xin Meng, Xuan Shen, Hao Tang, Minghai Qin, Tianlong Chen, Xiaolong Ma, Xiaohui Xie, Zhangyang Wang, Yanzhi Wang
Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training. CoRR (2022)
Tianshu Huang, Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang
Optimizer Amalgamation. ICLR (2022)
Tianlong Chen, Zhenyu Zhang, Yihua Zhang, Shiyu Chang, Sijia Liu, Zhangyang Wang
Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free. CoRR (2022)
Xinyu Gong, Wuyang Chen, Tianlong Chen, Zhangyang Wang
Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity. WACV (2022)
Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations. CoRR (2022)
Tianlong Chen, Xuxi Chen, Xiaolong Ma, Yanzhi Wang, Zhangyang Wang
Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets. ICML (2022)
Tianlong Chen, Xuxi Chen, Xiaolong Ma, Yanzhi Wang, Zhangyang Wang
Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets. CoRR (2022)
Diganta Misra, Bharat Runwal, Tianlong Chen, Zhangyang Wang, Irina Rish
APP: Anytime Progressive Pruning. CoRR (2022)
Mukund Varma T, Peihao Wang, Xuxi Chen, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang
Is Attention All NeRF Needs? CoRR (2022)
Hanxue Liang, Zhiwen Fan, Rishov Sarkar, Ziyu Jiang, Tianlong Chen, Kai Zou, Yu Cheng, Cong Hao, Zhangyang Wang
M³ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design. NeurIPS (2022)

Tianlong Chen.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Tianlong Chen