Min Li

Affiliations:
  • Chinese University of Hong Kong, CURE Lab, Hong Kong


According to our database1, Min Li authored at least 25 papers between 2019 and 2024.

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Bibliography

2024
DeepGate3: Towards Scalable Circuit Representation Learning.
CoRR, 2024

VerilogReader: LLM-Aided Hardware Test Generation.
CoRR, 2024

The Dawn of AI-Native EDA: Promises and Challenges of Large Circuit Models.
CoRR, 2024

AssertLLM: Generating and Evaluating Hardware Verification Assertions from Design Specifications via Multi-LLMs.
CoRR, 2024

AsymSAT: Accelerating SAT Solving with Asymmetric Graph-Based Model Prediction.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024

2023
Addressing Variable Dependency in GNN-based SAT Solving.
CoRR, 2023

DeepSeq: Deep Sequential Circuit Learning.
CoRR, 2023

DeepGate2: Functionality-Aware Circuit Representation Learning.
Proceedings of the IEEE/ACM International Conference on Computer Aided Design, 2023

SATformer: Transformer-Based UNSAT Core Learning.
Proceedings of the IEEE/ACM International Conference on Computer Aided Design, 2023

On EDA-Driven Learning for SAT Solving.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022
SATformer: Transformers for SAT Solving.
CoRR, 2022

DeepSAT: An EDA-Driven Learning Framework for SAT.
CoRR, 2022

DeepTPI: Test Point Insertion with Deep Reinforcement Learning.
Proceedings of the IEEE International Test Conference, 2022

T-WaveNet: A Tree-Structured Wavelet Neural Network for Time Series Signal Analysis.
Proceedings of the Tenth International Conference on Learning Representations, 2022

DeepGate: learning neural representations of logic gates.
Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

2021
Representation Learning of Logic Circuits.
CoRR, 2021

Skimming and Scanning for Untrimmed Video Action Recognition.
CoRR, 2021

TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Testability-Aware Low Power Controller Design with Evolutionary Learning.
Proceedings of the IEEE International Test Conference, 2021

AppealNet: An Efficient and Highly-Accurate Edge/Cloud Collaborative Architecture for DNN Inference.
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

Skimming and Scanning for Efficient Action Recognition in Untrimmed Videos.
Proceedings of the 14th International Congress on Image and Signal Processing, 2021

2020
On Configurable Defense against Adversarial Example Attacks.
Proceedings of the GLSVLSI '20: Great Lakes Symposium on VLSI 2020, 2020

DeepDyve: Dynamic Verification for Deep Neural Networks.
Proceedings of the CCS '20: 2020 ACM SIGSAC Conference on Computer and Communications Security, 2020

2019
Lightweight prediction based big/little design for efficient neural network inference.
Proceedings of the 4th ACM/IEEE Symposium on Edge Computing, 2019

D2NN: a fine-grained dual modular redundancy framework for deep neural networks.
Proceedings of the 35th Annual Computer Security Applications Conference, 2019


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