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2020 – today
- 2024
[c13]Baiqi Li, Zhiqiu Lin, Deepak Pathak, Jiayao Li, Yixin Fei, Kewen Wu, Xide Xia, Pengchuan Zhang, Graham Neubig, Deva Ramanan:
Evaluating and Improving Compositional Text-to-Visual Generation. CVPR Workshops 2024: 5290-5301- [c12]Shihong Liu, Samuel Yu, Zhiqiu Lin, Deepak Pathak, Deva Ramanan:
Language Models as Black-Box Optimizers for Vision-Language Models. CVPR 2024: 12687-12697 - [c11]Shubham Parashar, Zhiqiu Lin, Tian Liu, Xiangjue Dong, Yanan Li, Deva Ramanan, James Caverlee, Shu Kong:
The Neglected Tails in Vision-Language Models. CVPR 2024: 12988-12997 - [c10]Zhiqiu Lin, Deepak Pathak, Baiqi Li, Jiayao Li, Xide Xia, Graham Neubig, Pengchuan Zhang, Deva Ramanan:
Evaluating Text-to-Visual Generation with Image-to-Text Generation. ECCV (9) 2024: 366-384 - [c9]Zhiqiu Lin, Xinyue Chen, Deepak Pathak, Pengchuan Zhang, Deva Ramanan:
Revisiting the Role of Language Priors in Vision-Language Models. ICML 2024 - [c8]Jia Shi, Gautam Rajendrakumar Gare, Jinjin Tian, Siqi Chai, Zhiqiu Lin, Arun Balajee Vasudevan, Di Feng, Francesco Ferroni, Shu Kong:
LCA-on-the-Line: Benchmarking Out of Distribution Generalization with Class Taxonomies. ICML 2024 - [i15]Shubham Parashar, Zhiqiu Lin, Tian Liu, Xiangjue Dong, Yanan Li, Deva Ramanan, James Caverlee, Shu Kong:
The Neglected Tails of Vision-Language Models. CoRR abs/2401.12425 (2024) - [i14]Zhiqiu Lin, Deepak Pathak, Baiqi Li, Jiayao Li, Xide Xia, Graham Neubig, Pengchuan Zhang, Deva Ramanan:
Evaluating Text-to-Visual Generation with Image-to-Text Generation. CoRR abs/2404.01291 (2024) - [i13]Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C. Li, Adrien Bardes, Suzanne Petryk, Oscar Mañas, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, Mark Ibrahim, Melissa Hall, Yunyang Xiong, Jonathan Lebensold, Candace Ross, Srihari Jayakumar, Chuan Guo, Diane Bouchacourt, Haider Al-Tahan, Karthik Padthe, Vasu Sharma, Hu Xu, Xiaoqing Ellen Tan, Megan Richards, Samuel Lavoie, Pietro Astolfi, Reyhane Askari Hemmat, Jun Chen, Kushal Tirumala, Rim Assouel, Mazda Moayeri, Arjang Talattof, Kamalika Chaudhuri, Zechun Liu, Xilun Chen, Quentin Garrido, Karen Ullrich, Aishwarya Agrawal, Kate Saenko, Asli Celikyilmaz, Vikas Chandra:
An Introduction to Vision-Language Modeling. CoRR abs/2405.17247 (2024) - [i12]Baiqi Li, Zhiqiu Lin, Deepak Pathak, Jiayao Li, Yixin Fei, Kewen Wu, Tiffany Ling, Xide Xia, Pengchuan Zhang, Graham Neubig, Deva Ramanan:
GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation. CoRR abs/2406.13743 (2024) - [i11]Jia Shi, Gautam Rajendrakumar Gare, Jinjin Tian, Siqi Chai, Zhiqiu Lin, Arun Balajee Vasudevan, Di Feng, Francesco Ferroni, Shu Kong:
LCA-on-the-Line: Benchmarking Out-of-Distribution Generalization with Class Taxonomies. CoRR abs/2407.16067 (2024) - 2023
- [j1]Yanzhao Xie, Guangxing Hu, Yu Liu
, Zhiqiu Lin, Ke Zhou, Yuhong Zhao:
How visual chirality affects the performance of image hashing. Neural Comput. Appl. 35(12): 9003-9016 (2023) - [c7]Zhiqiu Lin, Samuel Yu, Zhiyi Kuang, Deepak Pathak, Deva Ramanan:
Multimodality Helps Unimodality: Cross-Modal Few-Shot Learning with Multimodal Models. CVPR 2023: 19325-19337 - [c6]Shubham Parashar, Zhiqiu Lin, Yanan Li, Shu Kong:
Prompting Scientific Names for Zero-Shot Species Recognition. EMNLP 2023: 9856-9861 - [i10]Zhiqiu Lin, Samuel Yu, Zhiyi Kuang, Deepak Pathak, Deva Ramanan:
Multimodality Helps Unimodality: Cross-Modal Few-Shot Learning with Multimodal Models. CoRR abs/2301.06267 (2023) - [i9]Zhiqiu Lin, Xinyue Chen, Deepak Pathak, Pengchuan Zhang, Deva Ramanan:
VisualGPTScore: Visio-Linguistic Reasoning with Multimodal Generative Pre-Training Scores. CoRR abs/2306.01879 (2023) - [i8]Shihong Liu, Samuel Yu, Zhiqiu Lin, Deepak Pathak, Deva Ramanan:
Language Models as Black-Box Optimizers for Vision-Language Models. CoRR abs/2309.05950 (2023) - [i7]Shubham Parashar, Zhiqiu Lin, Yanan Li, Shu Kong:
Prompting Scientific Names for Zero-Shot Species Recognition. CoRR abs/2310.09929 (2023) - 2022
- [c5]Zhiqiu Lin, Deepak Pathak, Yu-Xiong Wang, Deva Ramanan, Shu Kong:
Continual Learning with Evolving Class Ontologies. NeurIPS 2022 - [i6]Zhiqiu Lin, Jia Shi, Deepak Pathak, Deva Ramanan:
The CLEAR Benchmark: Continual LEArning on Real-World Imagery. CoRR abs/2201.06289 (2022) - [i5]Zhiqiu Lin, Deepak Pathak, Yu-Xiong Wang, Deva Ramanan, Shu Kong:
Learning with an Evolving Class Ontology. CoRR abs/2210.04993 (2022) - 2021
- [c4]Zhiqiu Lin, Jia Shi, Deepak Pathak, Deva Ramanan:
The CLEAR Benchmark: Continual LEArning on Real-World Imagery. NeurIPS Datasets and Benchmarks 2021 - [i4]Zhiqiu Lin, Deva Ramanan, Aayush Bansal:
Streaming Self-Training via Domain-Agnostic Unlabeled Images. CoRR abs/2104.03309 (2021) - 2020
- [c3]Zhiqiu Lin, Jin Sun, Abe Davis, Noah Snavely:
Visual Chirality. CVPR 2020: 12292-12300 - [i3]Zhiqiu Lin, Jin Sun, Abe Davis, Noah Snavely:
Visual Chirality. CoRR abs/2006.09512 (2020)
2010 – 2019
- 2019
- [c2]Zikai Alex Wen, Zhiqiu Lin, Rowena Chen, Erik Andersen:
What.Hack: Engaging Anti-Phishing Training Through a Role-playing Phishing Simulation Game. CHI 2019: 108 - [c1]Tianyi Zhang, Zhiqiu Lin, Guandao Yang, Christopher De Sa:
QPyTorch: A Low-Precision Arithmetic Simulation Framework. EMC2@NeurIPS 2019: 10-13 - [i2]Tianyi Zhang, Zhiqiu Lin, Guandao Yang, Christopher De Sa:
QPyTorch: A Low-Precision Arithmetic Simulation Framework. CoRR abs/1910.04540 (2019) - 2018
- [i1]Qian Huang, Zeqi Gu, Isay Katsman, Horace He, Pian Pawakapan, Zhiqiu Lin, Serge J. Belongie, Ser-Nam Lim:
Intermediate Level Adversarial Attack for Enhanced Transferability. CoRR abs/1811.08458 (2018)
Coauthor Index
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