Korea University Efficient Machine Intelligence Lab Korea University · School of Electrical Engineering
Publications

Publications

For the complete and most up-to-date list, please see Google Scholar. * denotes equal contribution.

Conference Papers

  • 2026
    Block Recursive Transformers for Structured Parameter Sharing Findings
    Josep Marques, HyunYoung Cho, Youngeun Kim, Youjia Zhang, Aecheon Jung, Kyuhong Shim, Sungeun Hong
    EMNLP 2026 Findings
  • 2026
    Real-Time Visual Attribution Streaming in Thinking Model Spotlight
    S Kang, W Han, J Kim, J Kim, Y Kim, SJ Hwang
    ICML 2026
  • 2026
    VisRef: Visual Refocusing while Thinking Improves Test-Time Scaling in Multi-Modal Large Reasoning Models
    SS Ghosal*, Y Kim*, Z Li, R Chaudhry, L Xu, H Zhang, J Zablocki, Y Xing, Q Zhang
    CVPR 2026
  • 2026
  • 2026
    MD-SNN: Membrane Potential-aware Distillation on Quantized Spiking Neural Network
    D Lee, A Moitra, Y Kim, R Yin, P Panda
    DATE 2026
  • 2025
    Backpropagation-Free Test-Time Adaptation via Probabilistic Gaussian Alignment
    Y Zhang, Y Kim, YG Choi, H Kim, H Liu, S Hong
    NeurIPS 2025
  • 2025
    Task Vector Quantization for Memory-Efficient Model Merging
    Y Kim, S Lee, A Jung, B Ryu, S Hong
    ICCV 2025
  • 2025
    Spiking Transformer with Spatial-Temporal Attention
    D Lee, Y Li, Y Kim, S Xiao, P Panda
    CVPR 2025
  • 2024
    Open-World Dynamic Prompt and Continual Visual Representation Learning
    Y Kim, J Fang, Q Zhang, Z Cai, Y Shen, R Duggal, DS Raychaudhuri, Z Tu, et al.
    ECCV 2024
  • 2024
    One-stage Prompt-based Continual Learning
    Y Kim, Y Li, P Panda
    ECCV 2024
  • 2024
    GenQ: Quantization in Low Data Regimes with Generative Synthetic Data
    Y Li, Y Kim, D Lee, S Kundu, P Panda
    ECCV 2024
  • 2024
    LoAS: Fully Temporal-Parallel Dataflow for Dual-Sparse Spiking Neural Networks
    R Yin, Y Kim, D Wu, P Panda
    MICRO 2024
  • 2024
    TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training
    D Lee, R Yin, Y Kim, A Moitra, Y Li, P Panda
    DATE 2024
  • 2023
    SEENN: Towards Temporal Spiking Early-Exit Neural Networks
    Y Li, T Geller, Y Kim, P Panda
    NeurIPS 2023
  • 2023
    Exploring Temporal Information Dynamics in Spiking Neural Networks
    Y Kim, Y Li, H Park, Y Venkatesha, A Hambitzer, P Panda
    AAAI 2023
  • 2023
  • 2023
  • 2022
    Exploring Lottery Ticket Hypothesis in Spiking Neural Networks Oral
    Y Kim, Y Li, H Park, Y Venkatesha, R Yin, P Panda
    ECCV 2022
  • 2022
    Neural Architecture Search for Spiking Neural Networks
    Y Kim, Y Li, H Park, Y Venkatesha, P Panda
    ECCV 2022
  • 2022
    Neuromorphic Data Augmentation for Training Spiking Neural Networks
    Y Li, Y Kim, H Park, T Geller, P Panda
    ECCV 2022
  • 2022
    PrivateSNN: Privacy-Preserving Spiking Neural Networks
    Y Kim, Y Venkatesha, P Panda
    AAAI 2022
  • 2022
    Rate Coding or Direct Coding: Which One is Better for Accurate, Robust, and Energy-efficient Spiking Neural Networks?
    Y Kim, H Park, A Moitra, A Bhattacharjee, Y Venkatesha, P Panda
    ICASSP 2022
  • 2022
    Examining the Robustness of Spiking Neural Networks on Non-ideal Memristive Crossbars Best Paper
    A Bhattacharjee, Y Kim, A Moitra, P Panda
    ISLPED 2022
  • 2022
    Gradient-based Bit Encoding Optimization for Noise-robust Binary Memristive Crossbar
    Y Kim, H Kim, S Kim, SJ Kim, P Panda
    DATE 2022
  • 2020
    Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification
    S Choi, S Lee, Y Kim, T Kim, C Kim
    CVPR 2020
  • 2020
    Combinational Class Activation Maps for Weakly Supervised Object Localization
    S Yang, Y Kim, Y Kim, C Kim
    WACV 2020
  • 2020
    RPM-Net: Robust Pixel-Level Matching Networks for Self-Supervised Video Object Segmentation
    Y Kim, H Lee, S Choi, T Kim, C Kim
    WACV 2020
  • 2020
    Reinforcement Learning-based Layer-wise Quantization for Lightweight Deep Neural Networks
    J Jung, J Kim, Y Kim, C Kim
    ICIP 2020
  • 2020
    Self-training of Graph Neural Networks using Similarity Reference for Robust Training with Noisy Labels
    H Park, M Jeong, Y Kim, C Kim
    ICIP 2020
  • 2019
    CNN-based Semantic Segmentation using Level Set Loss
    Y Kim, S Kim, T Kim, C Kim
    WACV 2019
  • 2019
    Bilinear Siamese Networks with Background Suppression for Visual Object Tracking
    H Lee, S Choi, Y Kim, C Kim
    BMVC 2019
  • 2018
    Weakly Supervised Semantic Segmentation Using Color Adjacency Loss
    Y Kim, T Kim, S Kim, C Kim
    VCIP 2018

Journal Papers

  • 2025
    CAT-TPT: Class-Agnostic Text-based Test-time Prompt Tuning for Vision-Language Models
    Y Zhang, H Liu, Y Kim, S Hong
    International Journal of Computer Vision (IJCV) 2025
  • 2025
    Artificial to Spiking Neural Networks Conversion with Calibration in Scientific Machine Learning
    Q Zhang, C Wu, A Kahana, GE Karniadakis, Y Kim, Y Li, P Panda
    SIAM Journal on Scientific Computing 2025
  • 2025
    ReSpike: Residual Frames-based Hybrid Spiking Neural Networks for Efficient Action Recognition
    S Xiao, Y Li, Y Kim, D Lee, P Panda
    Neuromorphic Computing and Engineering 2025
  • 2024
    Rethinking Skip Connections in Spiking Neural Networks with Time-To-First-Spike Coding
    Y Kim, A Kahana, R Yin, Y Li, P Stinis, G Karniadakis, P Panda
    Frontiers in Neuroscience 2024
  • 2024
    TReX: Reusing Vision Transformer's Attention for Efficient Xbar-Based Computing
    A Moitra, A Bhattacharjee, Y Kim, P Panda
    IEEE Transactions on Emerging Topics in Computing 2024
  • 2024
    Workload-Balanced Pruning for Sparse Spiking Neural Networks
    R Yin, Y Kim, Y Li, A Moitra, N Satpute, A Hambitzer, P Panda
    IEEE Transactions on Emerging Topics in Computational Intelligence 2024
  • 2024
    Do We Really Need a Large Number of Visual Prompts?
    Y Kim, Y Li, A Moitra, R Yin, P Panda
    Neural Networks 2024
  • 2024
    When In-Memory Computing Meets Spiking Neural Networks — A Perspective on Device–Circuit–System-and-Algorithm Co-Design
    A Moitra, A Bhattacharjee, Y Li, Y Kim, P Panda
    Applied Physics Reviews 2024
  • 2023
    Uncovering the Representation of Spiking Neural Networks Trained with Surrogate Gradient
    Y Li, Y Kim, H Park, P Panda
    Transactions on Machine Learning Research (TMLR) 2023
  • 2023
    TL-ADA: Transferable Loss-based Active Domain Adaptation
    K Han, Y Kim, D Han, H Lee, S Hong
    Neural Networks 2023
  • 2023
    Divide-and-Conquer the NAS Puzzle in Resource Constrained Federated Learning Systems
    Y Venkatesha, Y Kim, H Park, P Panda
    Neural Networks 2023
  • 2023
    Sharing Leaky-Integrate-and-Fire Neurons for Memory-Efficient Spiking Neural Networks
    Y Kim, Y Li, A Moitra, R Yin, P Panda
    Frontiers in Neuroscience 2023
  • 2023
    RobustEdge: Low Power Adversarial Detection for Cloud-Edge Systems
    A Moitra, A Bhattacharjee, Y Kim, P Panda
    IEEE Transactions on Emerging Topics in Computational Intelligence 2023
  • 2023
    Efficient Human Activity Recognition with Spatio-Temporal Spiking Neural Networks
    Y Li, R Yin, Y Kim, P Panda
    Frontiers in Neuroscience 2023
  • 2022
    2022 Roadmap on Neuromorphic Computing and Engineering
    DV Christensen, R Dittmann, B Linares-Barranco, A Sebastian, et al. (incl. Y Kim)
    Neuromorphic Computing and Engineering 2022
  • 2022
    SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks
    R Yin, A Moitra, A Bhattacharjee, Y Kim, P Panda
    IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 2022
  • 2022
    Beyond Classification: Directly Training Spiking Neural Networks for Semantic Segmentation
    Y Kim, J Chough, P Panda
    Neuromorphic Computing and Engineering 2022
  • 2021
    Revisiting Batch Normalization for Training Low-Latency Deep Spiking Neural Networks from Scratch
    Y Kim, P Panda
    Frontiers in Neuroscience 2021
  • 2021
    Optimizing Deeper Spiking Neural Networks for Dynamic Vision Sensing
    Y Kim, P Panda
    Neural Networks 2021
  • 2021
    Visual Explanations from Spiking Neural Networks using Inter-Spike Intervals
    Y Kim, P Panda
    Scientific Reports 2021
  • 2021
    Federated Learning with Spiking Neural Networks
    Y Venkatesha, Y Kim, L Tassiulas, P Panda
    IEEE Transactions on Signal Processing 2021
  • 2021
    Domain Adaptation without Source Data
    Y Kim, D Cho, K Han, P Panda, S Hong
    IEEE Transactions on Artificial Intelligence 2021
  • 2021
    Adaptive Graph Adversarial Networks for Partial Domain Adaptation
    Y Kim, S Hong
    IEEE Transactions on Circuits and Systems for Video Technology 2021
  • 2021
    NEAT: Nonlinearity Aware Training for Accurate, Energy-Efficient, and Robust Implementation of Neural Networks on 1T-1R Crossbars
    A Bhattacharjee, L Bhatnagar, Y Kim, P Panda
    IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 2021
  • 2020
    Towards Privacy-Preserving Domain Adaptation
    Y Kim, D Cho, S Hong
    IEEE Signal Processing Letters 2020

Preprints