default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDZechun Liu
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2025
[i45]Zechun Liu, Changsheng Zhao, Hanxian Huang, Sijia Chen, Jing Zhang, Jiawei Zhao, Scott Roy, Lisa Jin, Yunyang Xiong, Yangyang Shi, Lin Xiao, Yuandong Tian, Bilge Soran, Raghuraman Krishnamoorthi, Tijmen Blankevoort, Vikas Chandra:
ParetoQ: Scaling Laws in Extremely Low-bit LLM Quantization. CoRR abs/2502.02631 (2025)- [i44]Lisa Jin, Jianhao Ma, Zechun Liu, Andrey Gromov, Aaron Defazio, Lin Xiao:
PARQ: Piecewise-Affine Regularized Quantization. CoRR abs/2503.15748 (2025) - 2024
- [c32]Zechun Liu, Barlas Oguz, Changsheng Zhao, Ernie Chang, Pierre Stock, Yashar Mehdad, Yangyang Shi, Raghuraman Krishnamoorthi, Vikas Chandra:
LLM-QAT: Data-Free Quantization Aware Training for Large Language Models. ACL (Findings) 2024: 467-484 - [c31]Ganesh Jawahar, Haichuan Yang, Yunyang Xiong, Zechun Liu, Dilin Wang, Fei Sun, Meng Li, Aasish Pappu, Barlas Oguz, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Raghuraman Krishnamoorthi, Vikas Chandra:
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts. ACL (Findings) 2024: 10424-10443 - [c30]Ernie Chang, Matteo Paltenghi, Yang Li, Pin-Jie Lin, Changsheng Zhao, Patrick Huber, Zechun Liu, Rastislav Rabatin, Yangyang Shi, Vikas Chandra:
Scaling Parameter-Constrained Language Models with Quality Data. EMNLP (Industry Track) 2024: 80-97 - [c29]Xijie Huang, Zechun Liu, Shih-Yang Liu, Kwang-Ting Cheng:
RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization. EMNLP (Findings) 2024: 7563-7576 - [c28]Ernie Chang, Pin-Jie Lin, Yang Li, Changsheng Zhao, Daeil Kim, Rastislav Rabatin, Zechun Liu, Yangyang Shi, Vikas Chandra:
Target-Aware Language Modeling via Granular Data Sampling. EMNLP 2024: 12927-12935 - [c27]Ernie Chang, Sidd Srinivasan, Mahi Luthra, Pin-Jie Lin, Varun Nagaraja, Forrest N. Iandola, Zechun Liu, Zhaoheng Ni, Changsheng Zhao, Yangyang Shi, Vikas Chandra:
On the Open Prompt Challenge in Conditional Audio Generation. ICASSP 2024: 5315-5319 - [c26]Zechun Liu, Changsheng Zhao, Forrest N. Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra:
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases. ICML 2024 - [i43]Zechun Liu, Changsheng Zhao, Forrest N. Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra:
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases. CoRR abs/2402.14905 (2024) - [i42]Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort:
SpinQuant: LLM quantization with learned rotations. CoRR abs/2405.16406 (2024) - [i41]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) - [i40]Xijie Huang, Zechun Liu, Shih-Yang Liu, Kwang-Ting Cheng:
RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization. CoRR abs/2407.08044 (2024) - [i39]Ernie Chang, Pin-Jie Lin, Yang Li, Changsheng Zhao, Daeil Kim, Rastislav Rabatin, Zechun Liu, Yangyang Shi, Vikas Chandra:
Target-Aware Language Modeling via Granular Data Sampling. CoRR abs/2409.14705 (2024) - [i38]Ernie Chang, Matteo Paltenghi, Yang Li, Pin-Jie Lin, Changsheng Zhao, Patrick Huber, Zechun Liu, Rastislav Rabatin, Yangyang Shi, Vikas Chandra:
Scaling Parameter-Constrained Language Models with Quality Data. CoRR abs/2410.03083 (2024) - [i37]Mingchen Zhuge, Changsheng Zhao, Dylan R. Ashley, Wenyi Wang, Dmitrii Khizbullin, Yunyang Xiong, Zechun Liu, Ernie Chang, Raghuraman Krishnamoorthi, Yuandong Tian, Yangyang Shi, Vikas Chandra, Jürgen Schmidhuber:
Agent-as-a-Judge: Evaluate Agents with Agents. CoRR abs/2410.10934 (2024) - [i36]Xiaoqian Shen, Yunyang Xiong, Changsheng Zhao, Lemeng Wu, Jun Chen, Chenchen Zhu, Zechun Liu, Fanyi Xiao, Balakrishnan Varadarajan, Florian Bordes, Zhuang Liu, Hu Xu, Hyunwoo J. Kim, Bilge Soran, Raghuraman Krishnamoorthi, Mohamed Elhoseiny, Vikas Chandra:
LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding. CoRR abs/2410.17434 (2024) - [i35]Igor Fedorov, Kate Plawiak, Lemeng Wu, Tarek Elgamal, Naveen Suda, Eric Smith, Hongyuan Zhan, Jianfeng Chi, Yuriy Hulovatyy, Kimish Patel, Zechun Liu, Changsheng Zhao, Yangyang Shi, Tijmen Blankevoort, Mahesh Pasupuleti, Bilge Soran, Zacharie Delpierre Coudert, Rachad Alao, Raghuraman Krishnamoorthi, Vikas Chandra:
Llama Guard 3-1B-INT4: Compact and Efficient Safeguard for Human-AI Conversations. CoRR abs/2411.17713 (2024) - [i34]Yunyang Xiong, Chong Zhou, Xiaoyu Xiang, Lemeng Wu, Chenchen Zhu, Zechun Liu, Saksham Suri, Balakrishnan Varadarajan, Ramya Akula, Forrest N. Iandola, Raghuraman Krishnamoorthi, Bilge Soran, Vikas Chandra:
Efficient Track Anything. CoRR abs/2411.18933 (2024) - 2023
- [c25]Zechun Liu, Barlas Oguz, Aasish Pappu, Yangyang Shi, Raghuraman Krishnamoorthi:
Binary and Ternary Natural Language Generation. ACL (1) 2023: 65-77 - [c24]Shih-Yang Liu, Zechun Liu, Xijie Huang, Pingcheng Dong, Kwang-Ting Cheng:
LLM-FP4: 4-Bit Floating-Point Quantized Transformers. EMNLP 2023: 592-605 - [c23]Shih-Yang Liu, Zechun Liu, Kwang-Ting Cheng:
Oscillation-free Quantization for Low-bit Vision Transformers. ICML 2023: 21813-21824 - [i33]Shih-Yang Liu, Zechun Liu, Kwang-Ting Cheng:
Oscillation-free Quantization for Low-bit Vision Transformers. CoRR abs/2302.02210 (2023) - [i32]Renjie Wei, Shuwen Zhang, Zechun Liu, Meng Li, Yuchen Fan, Runsheng Wang, Ru Huang:
EBSR: Enhanced Binary Neural Network for Image Super-Resolution. CoRR abs/2303.12270 (2023) - [i31]Zechun Liu, Barlas Oguz, Changsheng Zhao, Ernie Chang, Pierre Stock, Yashar Mehdad, Yangyang Shi, Raghuraman Krishnamoorthi, Vikas Chandra:
LLM-QAT: Data-Free Quantization Aware Training for Large Language Models. CoRR abs/2305.17888 (2023) - [i30]Zechun Liu, Barlas Oguz, Aasish Pappu, Yangyang Shi, Raghuraman Krishnamoorthi:
Binary and Ternary Natural Language Generation. CoRR abs/2306.01841 (2023) - [i29]Ganesh Jawahar, Haichuan Yang, Yunyang Xiong, Zechun Liu, Dilin Wang, Fei Sun, Meng Li, Aasish Pappu, Barlas Oguz, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Raghuraman Krishnamoorthi, Vikas Chandra:
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts. CoRR abs/2306.04845 (2023) - [i28]Xijie Huang, Zechun Liu, Shih-Yang Liu, Kwang-Ting Cheng:
Efficient Quantization-aware Training with Adaptive Coreset Selection. CoRR abs/2306.07215 (2023) - [i27]Jun Chen, Deyao Zhu, Xiaoqian Shen, Xiang Li, Zechun Liu, Pengchuan Zhang, Raghuraman Krishnamoorthi, Vikas Chandra, Yunyang Xiong, Mohamed Elhoseiny:
MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning. CoRR abs/2310.09478 (2023) - [i26]Shih-Yang Liu, Zechun Liu, Xijie Huang, Pingcheng Dong, Kwang-Ting Cheng:
LLM-FP4: 4-Bit Floating-Point Quantized Transformers. CoRR abs/2310.16836 (2023) - [i25]Ernie Chang, Sidd Srinivasan, Mahi Luthra, Pin-Jie Lin, Varun Nagaraja, Forrest N. Iandola, Zechun Liu, Zhaoheng Ni, Changsheng Zhao, Yangyang Shi, Vikas Chandra:
On The Open Prompt Challenge In Conditional Audio Generation. CoRR abs/2311.00897 (2023) - 2022
- [j5]Yun Li, Zechun Liu, Weiqun Wu, Haotian Yao, Xiangyu Zhang, Chi Zhang, Baoqun Yin:
Weight-Dependent Gates for Network Pruning. IEEE Trans. Circuits Syst. Video Technol. 32(10): 6941-6954 (2022) - [c22]Shichao Li, Zechun Liu, Zhiqiang Shen, Kwang-Ting Cheng:
Stereo Neural Vernier Caliper. AAAI 2022: 1376-1385 - [c21]Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell, Eric Poe Xing:
Un-mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning. AAAI 2022: 2216-2224 - [c20]Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing:
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. CVPR 2022: 4921-4931 - [c19]Zechun Liu, Kwang-Ting Cheng, Dong Huang, Eric P. Xing, Zhiqiang Shen:
Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation. CVPR 2022: 4932-4942 - [c18]Zechun Liu, Zhiqiang Shen, Yun Long, Eric P. Xing, Kwang-Ting Cheng, Chas Leichner:
Data-Free Neural Architecture Search via Recursive Label Calibration. ECCV (24) 2022: 391-406 - [c17]Zhiqiang Shen, Zechun Liu, Eric P. Xing:
Sliced Recursive Transformer. ECCV (24) 2022: 727-744 - [c16]Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Xianghong Hu, Jeffry Wicaksana, Eric P. Xing, Kwang-Ting Cheng:
SDQ: Stochastic Differentiable Quantization with Mixed Precision. ICML 2022: 9295-9309 - [c15]Zechun Liu, Barlas Oguz, Aasish Pappu, Lin Xiao, Scott Yih, Meng Li, Raghuraman Krishnamoorthi, Yashar Mehdad:
BiT: Robustly Binarized Multi-distilled Transformer. NeurIPS 2022 - [i24]Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing:
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. CoRR abs/2201.00814 (2022) - [i23]Shichao Li, Zechun Liu, Zhiqiang Shen, Kwang-Ting Cheng:
Stereo Neural Vernier Caliper. CoRR abs/2203.11018 (2022) - [i22]Zechun Liu, Barlas Oguz, Aasish Pappu, Lin Xiao, Scott Yih, Meng Li, Raghuraman Krishnamoorthi, Yashar Mehdad:
BiT: Robustly Binarized Multi-distilled Transformer. CoRR abs/2205.13016 (2022) - [i21]Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Xianghong Hu, Jeffry Wicaksana, Eric P. Xing, Kwang-Ting Cheng:
SDQ: Stochastic Differentiable Quantization with Mixed Precision. CoRR abs/2206.04459 (2022) - 2021
- [j4]Zhiqiang Shen, Mingyang Huang, Jianping Shi, Zechun Liu, Harsh Maheshwari, Yutong Zheng, Xiangyang Xue, Marios Savvides, Thomas S. Huang:
CDTD: A Large-Scale Cross-Domain Benchmark for Instance-Level Image-to-Image Translation and Domain Adaptive Object Detection. Int. J. Comput. Vis. 129(3): 761-780 (2021) - [j3]Zechun Liu, Xiangyu Zhang, Zhiqiang Shen, Yichen Wei, Kwang-Ting Cheng, Jian Sun:
Joint Multi-Dimension Pruning via Numerical Gradient Update. IEEE Trans. Image Process. 30: 8034-8045 (2021) - [c14]Zhiqiang Shen, Zechun Liu, Jie Qin, Marios Savvides, Kwang-Ting Cheng:
Partial Is Better Than All: Revisiting Fine-tuning Strategy for Few-shot Learning. AAAI 2021: 9594-9602 - [c13]Zhiqiang Shen, Zechun Liu, Jie Qin, Lei Huang, Kwang-Ting Cheng, Marios Savvides:
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-Bit Neural Networks via Guided Distribution Calibration. CVPR 2021: 2165-2174 - [c12]Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang:
"BNN - BN = ?": Training Binary Neural Networks Without Batch Normalization. CVPR Workshops 2021: 4619-4629 - [c11]Zhiqiang Shen, Zechun Liu, Dejia Xu, Zitian Chen, Kwang-Ting Cheng, Marios Savvides:
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study. ICLR 2021 - [c10]Zechun Liu, Zhiqiang Shen, Shichao Li, Koen Helwegen, Dong Huang, Kwang-Ting Cheng:
How Do Adam and Training Strategies Help BNNs Optimization. ICML 2021: 6936-6946 - [c9]Ellen Yi-Ge, Rui Fan, Zechun Liu, Zhiqiang Shen:
Conditional Link Prediction of Category-Implicit Keypoint Detection. WACV 2021: 3439-3448 - [i20]Zhiqiang Shen, Zechun Liu, Jie Qin, Marios Savvides, Kwang-Ting Cheng:
Partial Is Better Than All: Revisiting Fine-tuning Strategy for Few-shot Learning. CoRR abs/2102.03983 (2021) - [i19]Zhiqiang Shen, Zechun Liu, Jie Qin, Lei Huang, Kwang-Ting Cheng, Marios Savvides:
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration. CoRR abs/2102.08946 (2021) - [i18]Zhiqiang Shen, Zechun Liu, Dejia Xu, Zitian Chen, Kwang-Ting Cheng, Marios Savvides:
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study. CoRR abs/2104.00676 (2021) - [i17]Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang:
"BNN - BN = ?": Training Binary Neural Networks without Batch Normalization. CoRR abs/2104.08215 (2021) - [i16]Zechun Liu, Zhiqiang Shen, Shichao Li, Koen Helwegen, Dong Huang, Kwang-Ting Cheng:
How Do Adam and Training Strategies Help BNNs Optimization? CoRR abs/2106.11309 (2021) - [i15]Zhiqiang Shen, Zechun Liu, Eric P. Xing:
Sliced Recursive Transformer. CoRR abs/2111.05297 (2021) - [i14]Zechun Liu, Kwang-Ting Cheng, Dong Huang, Eric P. Xing, Zhiqiang Shen:
Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation. CoRR abs/2111.14826 (2021) - [i13]Zechun Liu, Zhiqiang Shen, Yun Long, Eric P. Xing, Kwang-Ting Cheng, Chas Leichner:
Data-Free Neural Architecture Search via Recursive Label Calibration. CoRR abs/2112.02086 (2021) - 2020
- [j2]Zechun Liu, Wenhan Luo, Baoyuan Wu, Xin Yang, Wei Liu, Kwang-Ting Cheng:
Bi-Real Net: Binarizing Deep Network Towards Real-Network Performance. Int. J. Comput. Vis. 128(1): 202-219 (2020) - [c8]Hai Phan, Zechun Liu, Dang Huynh, Marios Savvides, Kwang-Ting Cheng, Zhiqiang Shen:
Binarizing MobileNet via Evolution-Based Searching. CVPR 2020: 13417-13426 - [c7]Yun Li, Weiqun Wu, Zechun Liu, Chi Zhang, Xiangyu Zhang, Haotian Yao, Baoqun Yin:
Weight-Dependent Gates for Differentiable Neural Network Pruning. ECCV Workshops (5) 2020: 23-37 - [c6]Zechun Liu, Zhiqiang Shen, Marios Savvides, Kwang-Ting Cheng:
ReActNet: Towards Precise Binary Neural Network with Generalized Activation Functions. ECCV (14) 2020: 143-159 - [c5]Zichao Guo, Xiangyu Zhang, Haoyuan Mu, Wen Heng, Zechun Liu, Yichen Wei, Jian Sun:
Single Path One-Shot Neural Architecture Search with Uniform Sampling. ECCV (16) 2020: 544-560 - [c4]Devesh Walawalkar, Zhiqiang Shen, Zechun Liu, Marios Savvides:
Attentive Cutmix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification. ICASSP 2020: 3642-3646 - [i12]Zechun Liu, Zhiqiang Shen, Marios Savvides, Kwang-Ting Cheng:
ReActNet: Towards Precise Binary Neural Network with Generalized Activation Functions. CoRR abs/2003.03488 (2020) - [i11]Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell:
Rethinking Image Mixture for Unsupervised Visual Representation Learning. CoRR abs/2003.05438 (2020) - [i10]Devesh Walawalkar, Zhiqiang Shen, Zechun Liu, Marios Savvides:
Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification. CoRR abs/2003.13048 (2020) - [i9]Hai Phan, Zechun Liu, Dang Huynh, Marios Savvides, Kwang-Ting Cheng, Zhiqiang Shen:
Binarizing MobileNet via Evolution-based Searching. CoRR abs/2005.06305 (2020) - [i8]Zechun Liu, Xiangyu Zhang, Zhiqiang Shen, Zhe Li, Yichen Wei, Kwang-Ting Cheng, Jian Sun:
Joint Multi-Dimension Pruning. CoRR abs/2005.08931 (2020) - [i7]Yun Li, Weiqun Wu, Zechun Liu, Chi Zhang, Xiangyu Zhang, Haotian Yao, Baoqun Yin:
Weight-dependent Gates for Network Pruning. CoRR abs/2007.02066 (2020) - [i6]Ellen Yi-Ge, Rui Fan, Zechun Liu, Zhiqiang Shen:
Conditional Link Prediction of Category-Implicit Keypoint Detection. CoRR abs/2011.14462 (2020)
2010 – 2019
- 2019
- [c3]Zechun Liu, Haoyuan Mu, Xiangyu Zhang, Zichao Guo, Xin Yang, Kwang-Ting Cheng, Jian Sun:
MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning. ICCV 2019: 3295-3304 - [c2]Koen Helwegen, James Widdicombe, Lukas Geiger, Zechun Liu, Kwang-Ting Cheng, Roeland Nusselder:
Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization. NeurIPS 2019: 7531-7542 - [i5]Zechun Liu, Haoyuan Mu, Xiangyu Zhang, Zichao Guo, Xin Yang, Kwang-Ting (Tim) Cheng, Jian Sun:
MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning. CoRR abs/1903.10258 (2019) - [i4]Zichao Guo, Xiangyu Zhang, Haoyuan Mu, Wen Heng, Zechun Liu, Yichen Wei, Jian Sun:
Single Path One-Shot Neural Architecture Search with Uniform Sampling. CoRR abs/1904.00420 (2019) - [i3]Koen Helwegen, James Widdicombe, Lukas Geiger, Zechun Liu, Kwang-Ting Cheng, Roeland Nusselder:
Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization. CoRR abs/1906.02107 (2019) - 2018
- [c1]Zechun Liu, Baoyuan Wu, Wenhan Luo, Xin Yang, Wei Liu, Kwang-Ting Cheng:
Bi-Real Net: Enhancing the Performance of 1-Bit CNNs with Improved Representational Capability and Advanced Training Algorithm. ECCV (15) 2018: 747-763 - [i2]Zechun Liu, Baoyuan Wu, Wenhan Luo, Xin Yang, Wei Liu, Kwang-Ting Cheng:
Bi-Real Net: Enhancing the Performance of 1-bit CNNs With Improved Representational Capability and Advanced Training Algorithm. CoRR abs/1808.00278 (2018) - [i1]Zechun Liu, Wenhan Luo, Baoyuan Wu, Xin Yang, Wei Liu, Kwang-Ting Cheng:
Bi-Real Net: Binarizing Deep Network Towards Real-Network Performance. CoRR abs/1811.01335 (2018) - 2016
- [j1]Bifang He, Guoshi Chai, Yaocong Duan, Zhiqiang Yan, Liuyang Qiu, Huixiong Zhang, Zechun Liu, Qiang He, Ke Han, Beibei Ru, Feng-Biao Guo, Hui Ding, Hao Lin, Xianlong Wang, Nini Rao, Peng Zhou, Jian Huang:
BDB: biopanning data bank. Nucleic Acids Res. 44(Database-Issue): 1127-1132 (2016)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-04-15 21:20 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
