Systematically testing background services of mobile apps. - Li Lyna Zhang; Chieh-Jan Mike Liang; Yunxin Liu 001; Enhong Chen (ASE, 2017)

Towards A Contextual and Scalable Automated-testing Service for Mobile Apps. - Li Lyna Zhang; Chieh-Jan Mike Liang; Wei Zhang; Enhong Chen (HotMobile, 2017)

Characterizing Privacy Risks of Mobile Apps with Sensitivity Analysis. - Li Lyna Zhang; Chieh-Jan Mike Liang; Zhao Lucis Li; Yunxin Liu 001; Feng Zhao 001; Enhong Chen (IEEE Trans. Mob. Comput., 2018)

Hardware-aware One-Shot Neural Architecture Search in Coordinate Ascent Framework. - Li Lyna Zhang; Yuqing Yang 001; Yuhang Jiang; Wenwu Zhu 001; Yunxin Liu 001 (CoRR, 2019)

Fast Hardware-Aware Neural Architecture Search. - Li Lyna Zhang; Yuqing Yang 001; Yuhang Jiang; Wenwu Zhu 001; Yunxin Liu 001 (CVPR Workshops, 2020)

To Bridge Neural Network Design and Real-World Performance: A Behaviour Study for Neural Networks. - Xiaohu Tang; Shihao Han; Li Lyna Zhang; Ting Cao; Yunxin Liu 001 (MLSys, 2021)

Boosting Mobile CNN Inference through Semantic Memory. - Yun Li; Chen Zhang 001; Shihao Han; Li Lyna Zhang; Baoqun Yin; Yunxin Liu 001; Mengwei Xu (ACM Multimedia, 2021)

nn-Meter: towards accurate latency prediction of deep-learning model inference on diverse edge devices. - Li Lyna Zhang; Shihao Han; Jianyu Wei; Ningxin Zheng; Ting Cao; Yuqing Yang 001; Yunxin Liu 001 (MobiSys, 2021)

AceNAS: Learning to Rank Ace Neural Architectures with Weak Supervision of Weight Sharing. - Yuge Zhang; Chenqian Yan; Quanlu Zhang; Li Lyna Zhang; Yaming Yang 001; Xiaotian Gao; Yuqing Yang 001 (CoRR, 2021)

nn-METER: Towards Accurate Latency Prediction of DNN Inference on Diverse Edge Devices. - Li Lyna Zhang; Shihao Han; Jianyu Wei; Ningxin Zheng; Ting Cao; Yunxin Liu 001 (GetMobile Mob. Comput. Commun., 2021)

SwiftPruner: Reinforced Evolutionary Pruning for Efficient Ad Relevance. - Li Lyna Zhang; Youkow Homma; Yujing Wang; Min Wu; Mao Yang 004; Ruofei Zhang; Ting Cao; Wei Shen (CIKM, 2022)

Towards efficient vision transformer inference: a first study of transformers on mobile devices. - Xudong Wang; Li Lyna Zhang; Yang Wang 053; Mao Yang 004 (HotMobile, 2022)

ElasticViT: Conflict-aware Supernet Training for Deploying Fast Vision Transformer on Diverse Mobile Devices. - Chen Tang; Li Lyna Zhang; Huiqiang Jiang; Jiahang Xu; Ting Cao; Quanlu Zhang; Yuqing Yang 001; Zhi Wang; Mao Yang 004 (ICCV, 2023)

SpaceEvo: Hardware-Friendly Search Space Design for Efficient INT8 Inference. - Xudong Wang; Li Lyna Zhang; Jiahang Xu; Quanlu Zhang; Yujing Wang; Yuqing Yang 001; Ningxin Zheng; Ting Cao; Mao Yang 004 (ICCV, 2023)

Accurate and Structured Pruning for Efficient Automatic Speech Recognition. - Huiqiang Jiang; Li Lyna Zhang; Yuang Li; Yu Wu; Shijie Cao; Ting Cao; Yuqing Yang 001; Jinyu Li; Mao Yang 004; Lili Qiu (INTERSPEECH, 2023)

Constraint-aware and Ranking-distilled Token Pruning for Efficient Transformer Inference. - Junyan Li; Li Lyna Zhang; Jiahang Xu; Yujing Wang; Shaoguang Yan; Yunqing Xia; Yuqing Yang 001; Ting Cao; Hao Sun 015; Weiwei Deng; Qi Zhang 066; Mao Yang 004 (KDD, 2023)

LUT-NN: Empower Efficient Neural Network Inference with Centroid Learning and Table Lookup. - Xiaohu Tang; Yang Wang 053; Ting Cao; Li Lyna Zhang; Qi Chen 009; Deng Cai 001; Yunxin Liu 001; Mao Yang 004 (MobiCom, 2023)

On Modular Learning of Distributed Systems for Predicting End-to-End Latency. - Chieh-Jan Mike Liang; Zilin Fang; Yuqing Xie 005; Fan Yang 024; Zhao Lucis Li; Li Lyna Zhang; Mao Yang 004; Lidong Zhou (NSDI, 2023)

LUT-NN: Towards Unified Neural Network Inference by Table Lookup. - Xiaohu Tang; Yang Wang 053; Ting Cao; Li Lyna Zhang; Qi Chen 009; Deng Cai 001; Yunxin Liu 001; Mao Yang 004 (CoRR, 2023)

Compresso: Structured Pruning with Collaborative Prompting Learns Compact Large Language Models. - Song Guo; Jiahang Xu; Li Lyna Zhang; Mao Yang 004 (CoRR, 2023)

Boosting LLM Reasoning: Push the Limits of Few-shot Learning with Reinforced In-Context Pruning. - Xijie Huang; Li Lyna Zhang; Kwang-Ting Cheng; Mao Yang 004 (CoRR, 2023)

Fewer is More: Boosting Math Reasoning with Reinforced Context Pruning. - Xijie Huang; Li Lyna Zhang; Kwang-Ting Cheng; Fan Yang 024; Mao Yang 004 (EMNLP, 2024)

VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models. - Yifei Liu; Jicheng Wen; Yang Wang 053; Shengyu Ye; Li Lyna Zhang; Ting Cao; Cheng Li 001; Mao Yang 004 (EMNLP, 2024)

LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens. - Yiran Ding; Li Lyna Zhang; Chengruidong Zhang; Yuanyuan Xu; Ning Shang; Jiahang Xu; Fan Yang 024; Mao Yang 004 (ICML, 2024)

LitePred: Transferable and Scalable Latency Prediction for Hardware-Aware Neural Architecture Search. - Chengquan Feng; Li Lyna Zhang; Yuanchi Liu; Jiahang Xu; Chengruidong Zhang; Zhiyuan Wang; Ting Cao; Mao Yang 004; Haisheng Tan (NSDI, 2024)

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone. - Marah I Abdin; Sam Ade Jacobs; Ammar Ahmad Awan; Jyoti Aneja; Ahmed Awadallah 001; Hany Awadalla; Nguyen Bach; Amit Bahree; Arash Bakhtiari; Harkirat S. Behl; Alon Benhaim; Misha Bilenko; et al. (CoRR, 2024)

Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers. - Zhenting Qi; Mingyuan Ma; Jiahang Xu; Li Lyna Zhang; Fan Yang 024; Mao Yang 004 (CoRR, 2024)

Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solver. - Zhenting Qi; Mingyuan Ma; Jiahang Xu; Li Lyna Zhang; Fan Yang 024; Mao Yang 004 (ICLR, 2025)

rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking. - Xinyu Guan; Li Lyna Zhang; Yifei Liu; Ning Shang; Youran Sun; Yi Zhu; Fan Yang 024; Mao Yang 004 (CoRR, 2025)

Beyond Prompt Content: Enhancing LLM Performance via Content-Format Integrated Prompt Optimization. - Yuanye Liu; Jiahang Xu; Li Lyna Zhang; Qi Chen 009; Xuan Feng; Yang Chen; Zhongxin Guo; Yuqing Yang 001; Peng Cheng 005 (CoRR, 2025)

LongRoPE2: Near-Lossless LLM Context Window Scaling. - Ning Shang; Li Lyna Zhang; Siyuan Wang; Gaokai Zhang; Gilsinia Lopez; Fan Yang 024; Weizhu Chen; Mao Yang 004 (CoRR, 2025)

Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs. - Abdelrahman Abouelenin; Atabak Ashfaq; Adam Atkinson; Hany Awadalla; Nguyen Bach; Jianmin Bao; Alon Benhaim; Martin Cai; Vishrav Chaudhary; Congcong Chen; Dong Chen 003; Dongdong Chen 001; et al. (CoRR, 2025)

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset. - Yifei Liu; Li Lyna Zhang; Yi Zhu; Bingcheng Dong; Xudong Zhou; Ning Shang; Fan Yang 024; Mao Yang 004 (CoRR, 2025)