Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training | Paper Citation Record

Observation 3b7e9f08-66c9-4690-8177-c1712e9b3eda · outbound

This paper cites Towards spike-based machine intelligence with neuromorphic computing,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Towards spike-based machine intelligence with neuromorphic computing,

Reference 1

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Observation 2a714023-f636-4c81-bc9f-a663c55e3a83 · outbound

This paper cites Opportunities for neuromorphic computing algorithms and applications,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Opportunities for neuromorphic computing algorithms and applications,

Reference 2

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This paper cites Networks of spiking neurons: The third generation of neural network models,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Networks of spiking neurons: The third generation of neural network models,

Reference 3

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This paper cites A million spiking-neuron integrated circuit with a scalable communication network and interface,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training A million spiking-neuron integrated circuit with a scalable communication network and interface,

Reference 4

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Observation a034df24-5bca-4e15-9e4b-6dde3906b881 · outbound

This paper cites Loihi: A neuromorphic manycore processor with on-chip learning,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Loihi: A neuromorphic manycore processor with on-chip learning,

Reference 5

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This paper cites Towards artificial general intelligence with hybrid tianjic chip architecture,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Towards artificial general intelligence with hybrid tianjic chip architecture,

Reference 6

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This paper cites Accurate and efficient time- domain classification with adaptive spiking recurrent neural networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Accurate and efficient time- domain classification with adaptive spiking recurrent neural networks,

Reference 7

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This paper cites A long short-term memory for ai applications in spike-based neuromorphic hard- ware,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training A long short-term memory for ai applications in spike-based neuromorphic hard- ware,

Reference 8

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Observation c96bafd0-31c8-49d3-890a-4bdd5ee7fd5c · outbound

This paper cites Neurozoom: Denoising and super resolving neuromor- phic events and spikes,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Neurozoom: Denoising and super resolving neuromor- phic events and spikes,

Reference 9

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Observation e60f4f10-bb2f-4e7a-b3db-41a213f78777 · outbound

This paper cites Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip,

Reference 10

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This paper cites Spiking deep residual networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Spiking deep residual networks,

Reference 11

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Observation 2b13d8ef-e26e-430f-9021-a154efbc001e · outbound

This paper cites Enabling deep spiking neural networks with hybrid conversion and spike tim- ing dependent backpropagation,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Enabling deep spiking neural networks with hybrid conversion and spike tim- ing dependent backpropagation,

Reference 12

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This paper cites Progressive tandem learning for pattern recognition with deep spiking neural networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Progressive tandem learning for pattern recognition with deep spiking neural networks,

Reference 14

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Observation ea7b2b7c-9f86-49ab-8973-62db8c72e3f8 · outbound

This paper cites Masked spiking transformer,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Masked spiking transformer,

Reference 15

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This paper cites Spatio-temporal backpropagation for training high-performance spiking neural networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Spatio-temporal backpropagation for training high-performance spiking neural networks,

Reference 16

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Observation e29c1b0a-0d60-4af0-a114-e03f8b608a24 · outbound

This paper cites Training spiking neural networks using lessons from deep learning,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Training spiking neural networks using lessons from deep learning,

Reference 17

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Observation 61b4a0fd-bd00-49db-a3e4-25abe9d17a9c · outbound

This paper cites Deep residual learning in spiking neural networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Deep residual learning in spiking neural networks,

Reference 18

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This paper cites Going deeper with directly-trained larger spiking neural networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Going deeper with directly-trained larger spiking neural networks,

Reference 19

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Observation 16c05708-d557-491c-a78d-85f1938f4f0d · outbound

This paper cites Vtsnn: a virtual temporal spiking neural net- work,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Vtsnn: a virtual temporal spiking neural net- work,

Reference 20

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Observation c7e30397-0ed9-4a67-87d0-f7d2d29786da · outbound

This paper cites Attention spiking neural networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Attention spiking neural networks,

Reference 21

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Observation b94d0e6e-d908-4e00-af24-1fbc0dc93ca4 · outbound

This paper cites Tensor decomposition based attention module for spiking neu- ral networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Tensor decomposition based attention module for spiking neu- ral networks,

Reference 22

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Observation 0d4eca94-e7bb-48f4-aa3a-d15c10cdde28 · outbound

This paper cites Rsc- snn: Exploring the trade-off between adversarial robustness and accuracy in spiking neural networks via randomized smoothing coding,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Rsc- snn: Exploring the trade-off between adversarial robustness and accuracy in spiking neural networks via randomized smoothing coding,

Reference 23

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This paper cites Integer-Valued Training and Spike-Driven Inference Spiking Neural Network for High-performance and Energy-efficient Object Detection.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Integer-Valued Training and Spike-Driven Inference Spiking Neural Network for High-performance and Energy-efficient Object Detection

Reference 24

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This paper cites Spikingjelly: An open- source machine learning infrastructure platform for spike-based intelligence,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Spikingjelly: An open- source machine learning infrastructure platform for spike-based intelligence,

Reference 25

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This paper cites Im-loss: information maximization loss for spiking neural net- works,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Im-loss: information maximization loss for spiking neural net- works,

Reference 26

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Observation e46206ec-75f7-47f7-9101-82f7a388b2ef · outbound

This paper cites Rethinking the performance comparison between snns and anns,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Rethinking the performance comparison between snns and anns,

Reference 27

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This paper cites Spike-driven transformer v2: Meta spiking neural network ar- chitecture inspiring the design of next-generation neuromorphic chips,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Spike-driven transformer v2: Meta spiking neural network ar- chitecture inspiring the design of next-generation neuromorphic chips,

Reference 28

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This paper cites Spike- driven transformer,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Spike- driven transformer,

Reference 29

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Observation e85213c8-0cd5-4ad6-a195-c9d99f0b0283 · outbound

This paper cites Masked autoencoders are scalable vision learners,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Masked autoencoders are scalable vision learners,

Reference 30

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This paper cites Designing bert for convolutional networks: Sparse and hierarchical masked FOR REVIEW 16 modeling,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Designing bert for convolutional networks: Sparse and hierarchical masked FOR REVIEW 16 modeling,

Reference 31

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This paper cites Imagenet: A large-scale hierarchical image database,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Imagenet: A large-scale hierarchical image database,

Reference 32

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This paper cites Microsoft coco: Common objects in context,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Microsoft coco: Common objects in context,

Reference 33

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This paper cites Scene parsing through ade20k dataset,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Scene parsing through ade20k dataset,

Reference 34

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This paper cites Hardvs: Revisiting human activity recognition with dynamic vision sensors,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Hardvs: Revisiting human activity recognition with dynamic vision sensors,

Reference 35

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This paper cites Online training through time for spiking neural networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Online training through time for spiking neural networks,

Reference 36

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This paper cites Towards memory-and time-efficient backpropagation for train- ing spiking neural networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Towards memory-and time-efficient backpropagation for train- ing spiking neural networks,

Reference 37

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This paper cites Rethinking pretraining as a bridge from anns to snns,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Rethinking pretraining as a bridge from anns to snns,

Reference 38

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This paper cites Memory-efficient reversible spiking neural networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Memory-efficient reversible spiking neural networks,

Reference 39

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This paper cites High-Performance Temporal Reversible Spiking Neural Networks with $O(L)$ Training Memory and $O(1)$ Inference Cost.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training High-Performance Temporal Reversible Spiking Neural Networks with $O(L)$ Training Memory and $O(1)$ Inference Cost

Reference 40

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Observation 96ddadff-63ce-4da0-8d83-1ea84a736d89 · outbound

This paper cites Towards ultra low latency spiking neural networks for vision and sequential tasks using temporal pruning,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Towards ultra low latency spiking neural networks for vision and sequential tasks using temporal pruning,

Reference 41

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This paper cites Seenn: Towards temporal spiking early exit neural networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Seenn: Towards temporal spiking early exit neural networks,

Reference 42

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Observation 6d5b8d96-fd7d-445c-a3f6-3aa1b87a1114 · outbound

This paper cites Deep residual learning for image recognition,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Deep residual learning for image recognition,

Reference 43

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This paper cites Identity mappings in deep residual networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Identity mappings in deep residual networks,

Reference 44

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This paper cites Advancing spiking neural networks toward deep residual learning,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Advancing spiking neural networks toward deep residual learning,

Reference 45

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Observation 4ae8243c-ac8d-4e52-a021-651614715a89 · outbound

This paper cites Attention is all you need,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Attention is all you need,

Reference 46

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This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 47

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Observation ed49572b-a06c-4e72-9aac-378926ebb799 · outbound

This paper cites Spike transformer: Monocular depth estimation for spiking camera,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Spike transformer: Monocular depth estimation for spiking camera,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:43.829844Z

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Observation c1c4f324-03ad-4928-9bbd-404f8fb6b88e · outbound

This paper cites Com- plex dynamic neurons improved spiking transformer network for efficient automatic speech recognition,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Com- plex dynamic neurons improved spiking transformer network for efficient automatic speech recognition,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:43.790925Z

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Observation 236e1ed8-8b97-4fa5-a4b8-6aceed68ba8c · outbound

This paper cites Spikformer: When spiking neural network meets transformer,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Spikformer: When spiking neural network meets transformer,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:43.625914Z

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This paper cites Metaformer is actually what you need for vision,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Metaformer is actually what you need for vision,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:43.531168Z

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Observation ea7ae1e9-417a-4d10-95ed-6b7e0ab67049 · outbound

This paper cites MetaLA: Unified optimal linear approximation to softmax attention map,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training MetaLA: Unified optimal linear approximation to softmax attention map,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:43.490525Z

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Observation 64971b10-bc5e-4fbb-be2c-f82476a3e68b · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 53

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This paper cites BEiT: BERT Pre-Training of Image Transformers.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training BEiT: BERT Pre-Training of Image Transformers

Reference 54

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Observation bd548946-8982-4d5d-8d08-7150e229b256 · outbound

This paper cites Image bert pre-training with online tokenizer,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Image bert pre-training with online tokenizer,

Reference 55

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Observation d4ceb99c-f61b-4494-bf30-c596843fdc18 · outbound

This paper cites Masked feature prediction for self-supervised visual pre- training,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Masked feature prediction for self-supervised visual pre- training,

Reference 56

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Mcmae: Masked convolution meets masked autoencoders,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:43.385777Z

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Convnext v2: Co-designing and scaling convnets with masked autoencoders,

Reference 58

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This paper cites Surrogate gradient learning in spiking neural networks: Bringing the power of gradient-based optimization to spiking neural networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Surrogate gradient learning in spiking neural networks: Bringing the power of gradient-based optimization to spiking neural networks,

Reference 59

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Gerstner, W

Reference 60

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This paper cites Neuromorphic silicon neuron cir- cuits,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Neuromorphic silicon neuron cir- cuits,

Reference 61

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This paper cites Parallel spiking neurons with high efficiency and ability to learn long-term dependencies,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Parallel spiking neurons with high efficiency and ability to learn long-term dependencies,

Reference 62

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Spiking neural networks with im- proved inherent recurrence dynamics for sequential learning,

Reference 63

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This paper cites Is Conventional SNN Really Efficient? A Perspective from Network Quantization.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Is Conventional SNN Really Efficient? A Perspective from Network Quantization

Reference 64

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Liaf-net: Leaky integrate and analog fire network for lightweight and ef- ficient spatiotemporal information processing,

Reference 65

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This paper cites Direct training for spiking neural networks: Faster, larger, better,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Direct training for spiking neural networks: Faster, larger, better,

Reference 66

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This paper cites Diet-snn: A low-latency spiking neural network with direct input encoding and leakage and threshold optimization,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Diet-snn: A low-latency spiking neural network with direct input encoding and leakage and threshold optimization,

Reference 67

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Event-Driven Learning for Spiking Neural Networks

Reference 68

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This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Mobilenetv2: Inverted residuals and linear bottlenecks,

Reference 69

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This paper cites Batch normalization: Accelerating deep network training by reducing internal covariate shift,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Batch normalization: Accelerating deep network training by reducing internal covariate shift,

Reference 70

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Xception: Deep learning with depthwise separable convolutions,

Reference 71

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Observation 43c1d982-c743-4fb4-8622-2268d7aad3f0 · outbound

This paper cites EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction

Reference 72

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input Features

Reference 73

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Rethinking mobile block for efficient attention-based models,

Reference 74

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Training data-efficient image transformers & distil- lation through attention,

Reference 75

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training How mask matters: Towards theoretical understandings of masked autoencoders,

Reference 76

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Pyramid vision transformer: A versatile backbone for dense prediction without convolutions,

Reference 77

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 78

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This paper cites Metaformer baselines for vision,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Metaformer baselines for vision,

Reference 79

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This paper cites Tokens-to-token vit: Training vision transformers from scratch on imagenet,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Tokens-to-token vit: Training vision transformers from scratch on imagenet,

Reference 80

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Observation d66ec072-8351-47c5-86fd-b63c1ccf08c2 · outbound

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Scaling up your kernels to 31x31: Revisiting large kernel design in cnns,

Reference 81

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Focal Self-attention for Local-Global Interactions in Vision Transformers

Reference 82

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training A convnet for the 2020s,

Reference 83

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Bottleneck transformers for visual recognition,

Reference 84

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This paper cites Crossformer++: A versatile vision transformer hinging on cross-scale attention,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Crossformer++: A versatile vision transformer hinging on cross-scale attention,

Reference 85

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This paper cites Opti- mal ann-snn conversion for high-accuracy and ultra-low-latency spiking neural networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Opti- mal ann-snn conversion for high-accuracy and ultra-low-latency spiking neural networks,

Reference 86

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This paper cites Fast-snn: Fast spiking neural network by converting quantized ann,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Fast-snn: Fast spiking neural network by converting quantized ann,

Reference 87

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This paper cites Toward high-accuracy and low-latency spiking neural networks with two-stage optimization,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Toward high-accuracy and low-latency spiking neural networks with two-stage optimization,

Reference 88

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Observation f24b3ef4-2d7d-4f99-b1d7-846158547ea7 · outbound

This paper cites Temporal efficient training of spiking neural network via gradient re-weighting,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Temporal efficient training of spiking neural network via gradient re-weighting,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:42.114783Z

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This paper cites Training high-performance low-latency spiking neural networks by differentiation on spike representation,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Training high-performance low-latency spiking neural networks by differentiation on spike representation,

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:42.040723Z

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Gated attention coding for training high-performance and efficient spik- ing neural networks,

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:41.887208Z

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This paper cites Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN Ticket.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN Ticket

Reference 92

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This paper cites Cifar10-dvs: an event- stream dataset for object classification,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Cifar10-dvs: an event- stream dataset for object classification,

Reference 93

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This paper cites Deformable detr: Deformable transformers for end-to-end object detection,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Deformable detr: Deformable transformers for end-to-end object detection,

Reference 94

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Spiking-yolo: Spiking neural network for energy-efficient object detection,

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:41.788842Z

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Observation dcb9da41-9c5a-4068-b0dc-a032143f4b64 · outbound

This paper cites Spike Calibration: Fast and Accurate Conversion of Spiking Neural Network for Object Detection and Segmentation.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Spike Calibration: Fast and Accurate Conversion of Spiking Neural Network for Object Detection and Segmentation

Reference 96

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Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Direct training high-performance spiking neural networks for object recognition and detection,

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:41.756623Z

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Observation bca708fe-7559-4a19-bbd9-a567f196c63e · outbound

This paper cites Deep directly-trained spiking neural networks for object detection,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Deep directly-trained spiking neural networks for object detection,

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:41.733761Z

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Observation cc83297c-6b7a-4b49-b83a-7c5ea261c74f · outbound

This paper cites Internimage: Exploring large-scale vision foundation models with deformable convolutions,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Internimage: Exploring large-scale vision foundation models with deformable convolutions,

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:41.702640Z

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Observation 91e92d0a-649f-433a-a05b-49661d3ea276 · outbound

This paper cites Resnest: Split-attention networks,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Resnest: Split-attention networks,

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:41.648693Z

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Observation a5904492-56e4-45ed-a427-a98896c597ba · outbound

This paper cites Slowfast networks for video recognition,.

Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training Slowfast networks for video recognition,

Reference 101

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