Li Lyna Zhang

Orcid: 0000-0002-4465-1628

According to our database1, Li Lyna Zhang authored at least 27 papers between 2017 and 2024.

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Bibliography

2024
Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers.
CoRR, 2024

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.
CoRR, 2024

LitePred: Transferable and Scalable Latency Prediction for Hardware-Aware Neural Architecture Search.
Proceedings of the 21st USENIX Symposium on Networked Systems Design and Implementation, 2024

LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Fewer is More: Boosting Math Reasoning with Reinforced Context Pruning.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023
Boosting LLM Reasoning: Push the Limits of Few-shot Learning with Reinforced In-Context Pruning.
CoRR, 2023

Compresso: Structured Pruning with Collaborative Prompting Learns Compact Large Language Models.
CoRR, 2023

LUT-NN: Towards Unified Neural Network Inference by Table Lookup.
CoRR, 2023

On Modular Learning of Distributed Systems for Predicting End-to-End Latency.
Proceedings of the 20th USENIX Symposium on Networked Systems Design and Implementation, 2023

LUT-NN: Empower Efficient Neural Network Inference with Centroid Learning and Table Lookup.
Proceedings of the 29th Annual International Conference on Mobile Computing and Networking, 2023

Constraint-aware and Ranking-distilled Token Pruning for Efficient Transformer Inference.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Accurate and Structured Pruning for Efficient Automatic Speech Recognition.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

SpaceEvo: Hardware-Friendly Search Space Design for Efficient INT8 Inference.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

ElasticViT: Conflict-aware Supernet Training for Deploying Fast Vision Transformer on Diverse Mobile Devices.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Towards efficient vision transformer inference: a first study of transformers on mobile devices.
Proceedings of the HotMobile '22: The 23rd International Workshop on Mobile Computing Systems and Applications, Tempe, Arizona, USA, March 9, 2022

SwiftPruner: Reinforced Evolutionary Pruning for Efficient Ad Relevance.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
nn-METER: Towards Accurate Latency Prediction of DNN Inference on Diverse Edge Devices.
GetMobile Mob. Comput. Commun., 2021

AceNAS: Learning to Rank Ace Neural Architectures with Weak Supervision of Weight Sharing.
CoRR, 2021

nn-Meter: towards accurate latency prediction of deep-learning model inference on diverse edge devices.
Proceedings of the MobiSys '21: The 19th Annual International Conference on Mobile Systems, Applications, and Services, Virtual Event, Wisconsin, USA, 24 June, 2021

Boosting Mobile CNN Inference through Semantic Memory.
Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

To Bridge Neural Network Design and Real-World Performance: A Behaviour Study for Neural Networks.
Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

2020
Fast Hardware-Aware Neural Architecture Search.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Hardware-aware One-Shot Neural Architecture Search in Coordinate Ascent Framework.
CoRR, 2019

2018
Characterizing Privacy Risks of Mobile Apps with Sensitivity Analysis.
IEEE Trans. Mob. Comput., 2018

2017
Towards A Contextual and Scalable Automated-testing Service for Mobile Apps.
Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications, 2017

Systematically testing background services of mobile apps.
Proceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering, 2017


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