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Li Lyna Zhang
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2020 – today
- 2024
- [c18]Yifei Liu, Jicheng Wen, Yang Wang, Shengyu Ye, Li Lyna Zhang, Ting Cao, Cheng Li, Mao Yang:
VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models. EMNLP 2024: 8181-8196 - [c17]Xijie Huang, Li Lyna Zhang, Kwang-Ting Cheng, Fan Yang, Mao Yang:
Fewer is More: Boosting Math Reasoning with Reinforced Context Pruning. EMNLP 2024: 13674-13695 - [c16]Yiran Ding, Li Lyna Zhang, Chengruidong Zhang, Yuanyuan Xu, Ning Shang, Jiahang Xu, Fan Yang, Mao Yang:
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens. ICML 2024 - [c15]Chengquan Feng, Li Lyna Zhang, Yuanchi Liu, Jiahang Xu, Chengruidong Zhang, Zhiyuan Wang, Ting Cao, Mao Yang, Haisheng Tan:
LitePred: Transferable and Scalable Latency Prediction for Hardware-Aware Neural Architecture Search. NSDI 2024 - [i15]Yiran Ding, Li Lyna Zhang, Chengruidong Zhang, Yuanyuan Xu, Ning Shang, Jiahang Xu, Fan Yang, Mao Yang:
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens. CoRR abs/2402.13753 (2024) - [i14]Marah I Abdin, Sam Ade Jacobs, Ammar Ahmad Awan, Jyoti Aneja, Ahmed Awadallah, Hany Awadalla, Nguyen Bach, Amit Bahree, Arash Bakhtiari, Harkirat S. Behl, Alon Benhaim, Misha Bilenko, Johan Bjorck, Sébastien Bubeck, Martin Cai, Caio César Teodoro Mendes, Weizhu Chen, Vishrav Chaudhary, Parul Chopra, Allie Del Giorno, Gustavo de Rosa, Matthew Dixon, Ronen Eldan, Dan Iter, Amit Garg, Abhishek Goswami, Suriya Gunasekar, Emman Haider, Junheng Hao, Russell J. Hewett, Jamie Huynh, Mojan Javaheripi, Xin Jin, Piero Kauffmann, Nikos Karampatziakis, Dongwoo Kim, Mahoud Khademi, Lev Kurilenko, James R. Lee, Yin Tat Lee, Yuanzhi Li, Chen Liang, Weishung Liu, Eric Lin, Zeqi Lin, Piyush Madan, Arindam Mitra, Hardik Modi, Anh Nguyen, Brandon Norick, Barun Patra, Daniel Perez-Becker, Thomas Portet, Reid Pryzant, Heyang Qin, Marko Radmilac, Corby Rosset, Sambudha Roy, Olatunji Ruwase, Olli Saarikivi, Amin Saied, Adil Salim, Michael Santacroce, Shital Shah, Ning Shang, Hiteshi Sharma, Xia Song, Masahiro Tanaka, Xin Wang, Rachel Ward, Guanhua Wang, Philipp Witte, Michael Wyatt, Can Xu, Jiahang Xu, Sonali Yadav, Fan Yang, Ziyi Yang, Donghan Yu, Chengruidong Zhang, Cyril Zhang, Jianwen Zhang, Li Lyna Zhang, Yi Zhang, Yue Zhang, Yunan Zhang, Xiren Zhou:
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone. CoRR abs/2404.14219 (2024) - [i13]Zhenting Qi, Mingyuan Ma, Jiahang Xu, Li Lyna Zhang, Fan Yang, Mao Yang:
Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers. CoRR abs/2408.06195 (2024) - [i12]Yifei Liu, Jicheng Wen, Yang Wang, Shengyu Ye, Li Lyna Zhang, Ting Cao, Cheng Li, Mao Yang:
VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models. CoRR abs/2409.17066 (2024) - 2023
- [c14]Xudong Wang, Li Lyna Zhang, Jiahang Xu, Quanlu Zhang, Yujing Wang, Yuqing Yang, Ningxin Zheng, Ting Cao, Mao Yang:
SpaceEvo: Hardware-Friendly Search Space Design for Efficient INT8 Inference. ICCV 2023: 5796-5805 - [c13]Chen Tang, Li Lyna Zhang, Huiqiang Jiang, Jiahang Xu, Ting Cao, Quanlu Zhang, Yuqing Yang, Zhi Wang, Mao Yang:
ElasticViT: Conflict-aware Supernet Training for Deploying Fast Vision Transformer on Diverse Mobile Devices. ICCV 2023: 5806-5817 - [c12]Huiqiang Jiang, Li Lyna Zhang, Yuang Li, Yu Wu, Shijie Cao, Ting Cao, Yuqing Yang, Jinyu Li, Mao Yang, Lili Qiu:
Accurate and Structured Pruning for Efficient Automatic Speech Recognition. INTERSPEECH 2023: 4104-4108 - [c11]Junyan Li
, Li Lyna Zhang
Constraint-aware and Ranking-distilled Token Pruning for Efficient Transformer Inference. KDD 2023: 1280-1290 - [c10]Xiaohu Tang
LUT-NN: Empower Efficient Neural Network Inference with Centroid Learning and Table Lookup. MobiCom 2023: 70:1-70:15 - [c9]Chieh-Jan Mike Liang, Zilin Fang, Yuqing Xie, Fan Yang, Zhao Lucis Li, Li Lyna Zhang, Mao Yang, Lidong Zhou:
On Modular Learning of Distributed Systems for Predicting End-to-End Latency. NSDI 2023: 1081-1095 - [i11]Xiaohu Tang, Yang Wang, Ting Cao, Li Lyna Zhang, Qi Chen, Deng Cai, Yunxin Liu, Mao Yang:
LUT-NN: Towards Unified Neural Network Inference by Table Lookup. CoRR abs/2302.03213 (2023) - [i10]Li Lyna Zhang, Xudong Wang, Jiahang Xu, Quanlu Zhang, Yujing Wang, Yuqing Yang, Ningxin Zheng, Ting Cao, Mao Yang:
SpaceEvo: Hardware-Friendly Search Space Design for Efficient INT8 Inference. CoRR abs/2303.08308 (2023) - [i9]Chen Tang, Li Lyna Zhang, Huiqiang Jiang, Jiahang Xu, Ting Cao, Quanlu Zhang, Yuqing Yang, Zhi Wang, Mao Yang:
ElasticViT: Conflict-aware Supernet Training for Deploying Fast Vision Transformer on Diverse Mobile Devices. CoRR abs/2303.09730 (2023) - [i8]Huiqiang Jiang, Li Lyna Zhang, Yuang Li, Yu Wu, Shijie Cao, Ting Cao, Yuqing Yang, Jinyu Li, Mao Yang, Lili Qiu:
Accurate and Structured Pruning for Efficient Automatic Speech Recognition. CoRR abs/2305.19549 (2023) - [i7]Junyan Li, Li Lyna Zhang, Jiahang Xu, Yujing Wang, Shaoguang Yan, Yunqing Xia, Yuqing Yang, Ting Cao, Hao Sun, Weiwei Deng, Qi Zhang, Mao Yang:
Constraint-aware and Ranking-distilled Token Pruning for Efficient Transformer Inference. CoRR abs/2306.14393 (2023) - [i6]Song Guo, Jiahang Xu, Li Lyna Zhang, Mao Yang:
Compresso: Structured Pruning with Collaborative Prompting Learns Compact Large Language Models. CoRR abs/2310.05015 (2023) - [i5]Xijie Huang, Li Lyna Zhang, Kwang-Ting Cheng, Mao Yang:
Boosting LLM Reasoning: Push the Limits of Few-shot Learning with Reinforced In-Context Pruning. CoRR abs/2312.08901 (2023) - 2022
- [c8]Li Lyna Zhang, Youkow Homma, Yujing Wang, Min Wu, Mao Yang, Ruofei Zhang, Ting Cao, Wei Shen:
SwiftPruner: Reinforced Evolutionary Pruning for Efficient Ad Relevance. CIKM 2022: 3654-3663 - [c7]Xudong Wang, Li Lyna Zhang, Yang Wang, Mao Yang:
Towards efficient vision transformer inference: a first study of transformers on mobile devices. HotMobile 2022: 1-7 - [i4]Li Lyna Zhang, Youkow Homma, Yujing Wang, Min Wu, Mao Yang, Ruofei Zhang, Ting Cao, Wei Shen:
SwiftPruner: Reinforced Evolutionary Pruning for Efficient Ad Relevance. CoRR abs/2209.00625 (2022) - 2021
- [j2]Li Lyna Zhang, Shihao Han, Jianyu Wei, Ningxin Zheng, Ting Cao, Yunxin Liu:
nn-METER: Towards Accurate Latency Prediction of DNN Inference on Diverse Edge Devices. GetMobile Mob. Comput. Commun. 25(4): 19-23 (2021) - [c6]Xiaohu Tang, Shihao Han, Li Lyna Zhang, Ting Cao, Yunxin Liu:
To Bridge Neural Network Design and Real-World Performance: A Behaviour Study for Neural Networks. MLSys 2021 - [c5]Yun Li
Boosting Mobile CNN Inference through Semantic Memory. ACM Multimedia 2021: 2362-2371 - [c4]Li Lyna Zhang, Shihao Han, Jianyu Wei, Ningxin Zheng, Ting Cao, Yuqing Yang, Yunxin Liu:
nn-Meter: towards accurate latency prediction of deep-learning model inference on diverse edge devices. MobiSys 2021: 81-93 - [i3]Yuge Zhang, Chenqian Yan, Quanlu Zhang, Li Lyna Zhang, Yaming Yang, Xiaotian Gao, Yuqing Yang:
AceNAS: Learning to Rank Ace Neural Architectures with Weak Supervision of Weight Sharing. CoRR abs/2108.03001 (2021) - [i2]Yun Li, Chen Zhang, Shihao Han, Li Lyna Zhang, Baoqun Yin, Yunxin Liu, Mengwei Xu:
Boosting Mobile CNN Inference through Semantic Memory. CoRR abs/2112.02644 (2021) - 2020
- [c3]Li Lyna Zhang, Yuqing Yang, Yuhang Jiang, Wenwu Zhu, Yunxin Liu:
Fast Hardware-Aware Neural Architecture Search. CVPR Workshops 2020: 2959-2967
2010 – 2019
- 2019
- [i1]Li Lyna Zhang, Yuqing Yang, Yuhang Jiang, Wenwu Zhu, Yunxin Liu:
Hardware-aware One-Shot Neural Architecture Search in Coordinate Ascent Framework. CoRR abs/1910.11609 (2019) - 2018
- [j1]Li Lyna Zhang
Characterizing Privacy Risks of Mobile Apps with Sensitivity Analysis. IEEE Trans. Mob. Comput. 17(2): 279-292 (2018) - 2017
- [c2]Li Lyna Zhang, Chieh-Jan Mike Liang, Yunxin Liu, Enhong Chen:
Systematically testing background services of mobile apps. ASE 2017: 4-15 - [c1]Li Lyna Zhang, Chieh-Jan Mike Liang, Wei Zhang, Enhong Chen:
Towards A Contextual and Scalable Automated-testing Service for Mobile Apps. HotMobile 2017: 97-102
Coauthor Index
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