Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients | Paper Citation Record

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This paper cites Deep residual learning for image recognition.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Deep residual learning for image recognition

Reference 1

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Observation c046613f-876e-437a-b7a8-b1a4d891566f · outbound

This paper cites Speech-transformer: a no-recurrence sequence-to-sequence model for speech recognition,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Speech-transformer: a no-recurrence sequence-to-sequence model for speech recognition,

Reference 3

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This paper cites End-to-end model-free reinforcement learning for urban driving using implicit affordances.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients End-to-end model-free reinforcement learning for urban driving using implicit affordances

Reference 4

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

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Networks of spiking neurons: the third generation of neural network models

Reference 5

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Observation 4c05e9a5-c4c4-4ab8-9768-3dccd8bbd2f6 · outbound

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

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Towards artificial general intelligence with hybrid tianjic chip architecture

Reference 6

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Observation a702ff3b-5c19-43d5-ace0-456bfaf28a8d · outbound

This paper cites Truenorth: Accelerating from zero to 64 million neurons in 10 years,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Truenorth: Accelerating from zero to 64 million neurons in 10 years,

Reference 7

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Observation 4c5a6534-0e1e-4a65-9d86-3efba01f34f3 · outbound

This paper cites Competitive hebbian learn- ing through spike-timing-dependent synaptic plasticity,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Competitive hebbian learn- ing through spike-timing-dependent synaptic plasticity,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.364498Z

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Observation 7202b7a2-a410-42a5-8e82-4680e72ff65b · outbound

This paper cites Spiking deep convolutional neural networks for energy-efficient object recognition,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Spiking deep convolutional neural networks for energy-efficient object recognition,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.394262Z

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Observation 6068f8e0-efff-4150-97bd-be33e59964c1 · outbound

This paper cites Backpropagation through time: what it does and how to do it.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Backpropagation through time: what it does and how to do it

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.289079Z

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Observation 12fe0d2e-824f-4eb2-b763-5a10c11dceb3 · outbound

This paper cites Construct- ing accurate and efficient deep spiking neural networks with double- threshold and augmented schemes,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Construct- ing accurate and efficient deep spiking neural networks with double- threshold and augmented schemes,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.277757Z

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Observation aedd2d06-7cfe-4679-a299-7b1c3f360d57 · outbound

This paper cites Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-06-30T20:05:04.804433Z

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Observation 41aed248-ddef-4e36-9a26-508f49c580f0 · outbound

This paper cites Rmp-snn: Residual membrane potential neuron for enabling deeper high-accuracy and low-latency spiking neural network.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Rmp-snn: Residual membrane potential neuron for enabling deeper high-accuracy and low-latency spiking neural network

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.298182Z

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Observation b3fd5d6d-0239-44c8-87e6-d602ecbbd10a · outbound

This paper cites A free lunch from ann: Towards efficient, accurate spiking neural networks calibration.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients A free lunch from ann: Towards efficient, accurate spiking neural networks calibration

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.340014Z

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Observation 3cfc9cdf-4ea2-4670-a76d-c0c4b1f9896c · outbound

This paper cites Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-06-30T20:05:04.808245Z

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Observation ea6c23c8-5bed-4c76-a7de-b9f37b751099 · outbound

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

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Surrogate gradient learning in spiking neural networks: Bringing the power of gradient-based optimization to spiking neural networks,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.375136Z

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Observation c08195ed-5591-4dab-b2e7-589f4aa65b0a · outbound

This paper cites Training deep spiking neural networks using backpropagation,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Training deep spiking neural networks using backpropagation,

Reference 17

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Observation 70a24dac-ab1f-49bc-a5d7-82c642ccf5ff · outbound

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

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Spatio-temporal backpropa- gation for training high-performance spiking neural networks,

Reference 18

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Observation b01e75ce-af37-4326-ae0a-82c064eb6d5a · outbound

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

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Going deeper with directly-trained larger spiking neural networks,

Reference 19

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Observation 73b5f130-09f1-4938-8463-2f0b389824e4 · outbound

This paper cites Deep residual learning in spiking neural networks.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Deep residual learning in spiking neural networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.262592Z

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Observation c731a84c-7d44-4d12-8c69-ddcb4253466c · outbound

This paper cites Incorporating learnable membrane time constant to enhance learning of spiking neural networks,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Incorporating learnable membrane time constant to enhance learning of spiking neural networks,

Reference 21

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Observation df94e17e-0949-46de-9132-c4d8b7d76d37 · outbound

This paper cites Multi-level firing with spiking ds-resnet: Enabling better and deeper directly-trained spiking neural networks,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Multi-level firing with spiking ds-resnet: Enabling better and deeper directly-trained spiking neural networks,

Reference 22

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This paper cites Im-loss: Information maximization loss for spiking neural networks,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Im-loss: Information maximization loss for spiking neural networks,

Reference 23

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Observation 9f03fe4a-35a4-483f-b930-eb19e7e3813b · outbound

This paper cites Rmp-loss: Regularizing membrane potential distribution for spiking neural networks,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Rmp-loss: Regularizing membrane potential distribution for spiking neural networks,

Reference 24

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Observation d83d0dce-a52d-46f2-9863-97cea985ca74 · outbound

This paper cites Ternary spike: Learning ternary spikes for spiking neural networks,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Ternary spike: Learning ternary spikes for spiking neural networks,

Reference 25

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This paper cites Tab: Temporal accumulated batch normalization in spiking neural networks,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Tab: Temporal accumulated batch normalization in spiking neural networks,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.350144Z

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This paper cites Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting

Reference 27

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Observation 0f0414fa-1234-4f8f-bad2-181f2c830a09 · outbound

This paper cites Neuronal Competition Groups with Supervised STDP for Spike-Based Classification.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Neuronal Competition Groups with Supervised STDP for Spike-Based Classification

Reference 28

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Observation 8219632e-03ce-43b2-b10a-00c991f18dbc · outbound

This paper cites First-spike-based visual categorization using reward- modulated stdp,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients First-spike-based visual categorization using reward- modulated stdp,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.356986Z

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Observation 63e1f4a4-473c-4e4b-a7fb-0ed3c7bcf2b8 · outbound

This paper cites SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN

Reference 30

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Observation 16740c3c-e754-4c55-9fd2-134a9f20f1a5 · outbound

This paper cites Spatio-temporal approximation: A training-free snn conversion for transformers,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Spatio-temporal approximation: A training-free snn conversion for transformers,

Reference 31

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Observation fcf3cc19-83fa-4b40-beed-00a676e469de · outbound

This paper cites Spikedattention: Training-free and fully spike-driven transformer-to-snn conversion with winner-oriented spike shift for softmax operation,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Spikedattention: Training-free and fully spike-driven transformer-to-snn conversion with winner-oriented spike shift for softmax operation,

Reference 32

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Observation b3c5bd65-8b08-4d3a-a1d7-3d1167117a4a · outbound

This paper cites Revisiting batch normalization for training low-latency deep spiking neural networks from scratch,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Revisiting batch normalization for training low-latency deep spiking neural networks from scratch,

Reference 33

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Observation 1988613a-fdd7-47b8-a487-b1510f8e1d1a · outbound

This paper cites Membrane potential batch normalization for spiking neural networks,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Membrane potential batch normalization for spiking neural networks,

Reference 34

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Observation 0eb92a78-3196-4453-af0c-16fdee61374e · outbound

This paper cites Temporal effective batch normalization in spiking neural networks,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Temporal effective batch normalization in spiking neural networks,

Reference 35

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Observation af9a6353-92dd-4148-90e6-18e5c4533456 · outbound

This paper cites Learnable surrogate gradient for direct training spiking neural networks.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Learnable surrogate gradient for direct training spiking neural networks

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.221605Z

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Observation f1f17c2c-cc69-4123-83d5-eadeabb653e4 · outbound

This paper cites Directly training temporal spiking neural network with sparse surrogate gradient,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Directly training temporal spiking neural network with sparse surrogate gradient,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.217724Z

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Observation 01410a33-5173-4309-b2f0-fb5a3bf08005 · outbound

This paper cites Adaptive smoothing gradient learning for spiking neural networks.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Adaptive smoothing gradient learning for spiking neural networks

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.327773Z

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Observation be5a3932-4fd3-45ed-9f89-8f96f5195faf · outbound

This paper cites Ltmd: Learning improvement of spiking neural networks with learnable thresholding neurons and moderate dropout,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Ltmd: Learning improvement of spiking neural networks with learnable thresholding neurons and moderate dropout,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.334028Z

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Observation caefacab-0ee8-42c6-bce4-4b921e2aa9f8 · outbound

This paper cites DIET-SNN: Direct Input Encoding With Leakage and Threshold Optimization in Deep Spiking Neural Networks.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients DIET-SNN: Direct Input Encoding With Leakage and Threshold Optimization in Deep Spiking Neural Networks

Reference 40

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Observation 0931d230-d7f8-41f4-9f28-be68965a5300 · outbound

This paper cites Glif: A unified gated leaky integrate-and-fire neuron for spiking neural networks,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Glif: A unified gated leaky integrate-and-fire neuron for spiking neural networks,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.336894Z

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Observation c6728217-4605-4e63-817c-ce00856fc89a · outbound

This paper cites Tc-lif: A two- compartment spiking neuron model for long-term sequential modelling,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Tc-lif: A two- compartment spiking neuron model for long-term sequential modelling,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.343418Z

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Observation b2387653-9305-4a55-8990-d4377cd05b39 · outbound

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

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Parallel spiking neurons with high efficiency and ability to learn long-term dependencies,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.229171Z

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Observation ac4163c6-d458-4016-b6b6-b3be50a16770 · outbound

This paper cites A progressive training framework for spiking neural networks with learnable multi- hierarchical model.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients A progressive training framework for spiking neural networks with learnable multi- hierarchical model

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.236893Z

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Observation 4e3a47f4-c3d8-4a54-afb1-000202d06ea2 · outbound

This paper cites LM-HT SNN: Enhancing the Performance of SNN to ANN Counterpart through Learnable Multi-hierarchical Threshold Model.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients LM-HT SNN: Enhancing the Performance of SNN to ANN Counterpart through Learnable Multi-hierarchical Threshold Model

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-06-30T20:05:04.813105Z

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Observation 1a12a8a0-1013-4c99-8448-b6c39bb6f77b · outbound

This paper cites Spikformer: When Spiking Neural Network Meets Transformer.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Spikformer: When Spiking Neural Network Meets Transformer

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-06-30T20:05:04.816274Z

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Observation d3c10cdb-5e89-4b45-bed1-e2211904935e · outbound

This paper cites Qkformer: Hierarchical spiking transformer using qk attention,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Qkformer: Hierarchical spiking transformer using qk attention,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.319235Z

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Observation 832ef55d-8b76-4a1a-b85a-c2ac1978cd4c · outbound

This paper cites Biologically inspired dynamic thresholds for spiking neural networks,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Biologically inspired dynamic thresholds for spiking neural networks,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.321884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 42ec6e75-fcba-4341-81a5-a0fea2940092 · outbound

This paper cites An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.258716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f98535e5-7436-4e4b-8ae3-1aaa44480f2d · outbound

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

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Direct training for spiking neural networks: Faster, larger, better,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.301552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fbd8fc9f-d7ff-42ca-a11e-0aea310b4cd2 · outbound

This paper cites An overview of gradient descent optimization algorithms,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients An overview of gradient descent optimization algorithms,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.309400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 377b923e-872e-4425-a2b8-4b3784a2a8fb · outbound

This paper cites An overview of gradient descent optimization algorithms.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients An overview of gradient descent optimization algorithms

Reference 52

Resolution: metadata mismatch; local_arxiv, observed 2026-06-30T20:05:04.773683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8c958ded-77b6-4bcb-8858-cb2cf346192e · outbound

This paper cites Long short-term memory and learning-to-learn in networks of spiking neurons,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Long short-term memory and learning-to-learn in networks of spiking neurons,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.313199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 10a7b2ca-5313-4152-bd78-2ef00b1f3fcb · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 54

Resolution: verified exact; local_arxiv, observed 2026-06-30T20:05:04.776264Z

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Observation d69c5070-326c-4906-ae14-e1ca577ccc31 · outbound

This paper cites Learning multiple layers of features from tiny images.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Learning multiple layers of features from tiny images

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.304699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4e80738e-51ef-4656-a902-0addd4d9702d · outbound

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

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Imagenet: A large-scale hierarchical image database

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.316764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation db863a8c-7d0a-4a03-8020-8a6aa00e9462 · outbound

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

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Cifar10-dvs: an event-stream dataset for object classification,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.324641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6b69daea-1b67-4975-9523-abe33e083803 · outbound

This paper cites Synaptic plasticity dynamics for deep continuous local learning (decolle),.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Synaptic plasticity dynamics for deep continuous local learning (decolle),

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.346678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 958e5c8a-a752-43da-ad03-3c2ce44eae53 · outbound

This paper cites Recursive deep models for semantic compositionality over a sentiment treebank.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Recursive deep models for semantic compositionality over a sentiment treebank

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.284816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 685ebef5-62de-47b4-90f2-72f44f35995b · outbound

This paper cites Tactilesgnet: A spiking graph neural network for event-based tactile object recognition,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Tactilesgnet: A spiking graph neural network for event-based tactile object recognition,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.274724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d60fa007-ab00-4d79-8d9f-46215537f879 · outbound

This paper cites Spiking transformer with experts mixture,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Spiking transformer with experts mixture,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.368455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 76b46fc8-4307-496d-9b86-d119e28d5c42 · outbound

This paper cites Training spiking neural networks with local tandem learning.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Training spiking neural networks with local tandem learning

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.182079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 880b3d4b-acdf-4888-92bf-f9a94b4af7a3 · outbound

This paper cites Neuromorphic data augmentation for training spiking neural networks,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Neuromorphic data augmentation for training spiking neural networks,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.206660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6665df13-7897-4b51-8852-0cb99df56b95 · outbound

This paper cites Spiking convolutional neural networks for text classification,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Spiking convolutional neural networks for text classification,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.186657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 001d9020-2d8e-4196-8492-ce8375408b7e · outbound

This paper cites Convolutional Neural Networks for Sentence Classification.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Convolutional Neural Networks for Sentence Classification

Reference 65

Resolution: verified exact; local_arxiv, observed 2026-06-30T20:05:04.780857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4e0d86a4-bce1-4bbb-bfbb-7247cbc983a3 · outbound

This paper cites Eventmix: An efficient data augmenta- tion strategy for event-based learning,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Eventmix: An efficient data augmenta- tion strategy for event-based learning,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.233043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 68c769f4-938f-4c8f-add5-f873d20e35d3 · outbound

This paper cites Eventrpg: event data augmentation with relevance propagation guidance. arxiv,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Eventrpg: event data augmentation with relevance propagation guidance. arxiv,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.210351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 20ec38b0-5985-405b-998f-809387bce8b6 · outbound

This paper cites Tcja- snn: Temporal-channel joint attention for spiking neural networks,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Tcja- snn: Temporal-channel joint attention for spiking neural networks,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.254921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 228c3ded-a198-45c3-86df-d3f54d0866f0 · outbound

This paper cites Tactilegcn: A graph convolutional network for predicting grasp stability with tactile sensors,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Tactilegcn: A graph convolutional network for predicting grasp stability with tactile sensors,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.248111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5a16b8f2-b99b-46d0-b786-e46dfb121e7f · outbound

This paper cites Slayer: Spike layer error reassignment in time,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Slayer: Spike layer error reassignment in time,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.251768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 430f86d6-1ab6-4661-a78e-7d89e56dc50f · outbound

This paper cites Spiking deep residual networks,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Spiking deep residual networks,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.240246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fc457faa-f7b3-48ef-a5b9-b4fc3e647584 · outbound

This paper cites Neuromorphic architectures for spiking deep neural networks,.

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients Neuromorphic architectures for spiking deep neural networks,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T22:04:08.244074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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