Yuhong Chou

Orcid: 0009-0003-7788-7287

According to our database1, Yuhong Chou authored at least 16 papers between 2023 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2025
Scaling Linear Attention with Sparse State Expansion.
CoRR, July, 2025

IML-Spikeformer: Input-aware Multi-Level Spiking Transformer for Speech Processing.
CoRR, July, 2025

A Systematic Analysis of Hybrid Linear Attention.
CoRR, July, 2025

A Survey on Latent Reasoning.
CoRR, July, 2025

ZeCO: Zero Communication Overhead Sequence Parallelism for Linear Attention.
CoRR, July, 2025

Scaling Spike-Driven Transformer With Efficient Spike Firing Approximation Training.
IEEE Trans. Pattern Anal. Mach. Intell., April, 2025

MMDEND: Dendrite-Inspired Multi-Branch Multi-Compartment Parallel Spiking Neuron for Sequence Modeling.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Efficient 3D Recognition with Event-driven Spike Sparse Convolution.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
Scalable Autoregressive Image Generation with Mamba.
CoRR, 2024

MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

RSC-SNN: Exploring the Trade-off Between Adversarial Robustness and Accuracy in Spiking Neural Networks via Randomized Smoothing Coding.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

High-Performance Temporal Reversible Spiking Neural Networks with O(L) Training Memory and O(1) Inference Cost.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Integer-Valued Training and Spike-Driven Inference Spiking Neural Network for High-Performance and Energy-Efficient Object Detection.
Proceedings of the Computer Vision - ECCV 2024, 2024

Gated Attention Coding for Training High-Performance and Efficient Spiking Neural Networks.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Probabilistic Modeling: Proving the Lottery Ticket Hypothesis in Spiking Neural Network.
CoRR, 2023

Deep Directly-Trained Spiking Neural Networks for Object Detection.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023


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