Paper Citation Record · LEDGER

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers

As of 8 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2601.18274.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2601.18274 v3

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T08:05:01.815952Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

verified exact0
verified fuzzy0
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0fe38e3f-214d-47c0-a370-c105470deef2 · outbound

This paper cites Spiking Vision Transformer with Saccadic Attention.

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers Spiking Vision Transformer with Saccadic Attention

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T08:05:00.459161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fbd03ea-04f1-4513-bdb1-ddb61657f26c · outbound

This paper cites DISTA: Denoising Spiking Transformer with intrinsic plasticity and spatiotemporal attention.

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers DISTA: Denoising Spiking Transformer with intrinsic plasticity and spatiotemporal attention

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T08:05:00.651092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d3ac597-8657-4d9f-9b9b-2695c697935f · outbound

This paper cites DS2TA: Denoising Spiking Transformer with Attenuated Spatiotemporal Attention.

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers DS2TA: Denoising Spiking Transformer with Attenuated Spatiotemporal Attention

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T08:05:00.822750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab499be8-991d-4464-86be-051713d34263 · outbound

This paper cites Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips.

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T08:05:00.989398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98e80dd3-f31f-4cce-ae92-bf6719b8f518 · outbound

This paper cites Spikingformer: Spike-driven residual learn- ing for transformer-based spiking neural network.arXiv preprint arXiv:2304.11954,.

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers Spikingformer: Spike-driven residual learn- ing for transformer-based spiking neural network.arXiv preprint arXiv:2304.11954,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T08:05:01.162198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a672317f-b8c9-4bdc-a3c8-83102c54deb3 · outbound

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

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers Spikformer: When Spiking Neural Network Meets Transformer

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T08:05:01.310676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d5352c1-37c4-4216-b309-85748d333996 · outbound

This paper cites Spiking Graph Convolutional Networks.

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers Spiking Graph Convolutional Networks

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T08:05:01.529512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0841746b-5764-4bba-a324-9c8b23555389 · outbound

This paper cites Robustness among Size All size-related experiments were conducted under identical conditions.

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers Robustness among Size All size-related experiments were conducted under identical conditions

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T08:05:01.711829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fedf456e-3de5-46f1-9adf-9e3b137e5719 · outbound

This paper cites an unresolved cited work.

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T08:05:01.815952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76cad01a-bd2b-4463-88ca-1df093a89ed6 · outbound

This paper cites TIM: An Efficient Temporal Interaction Module for Spiking Transformer.

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers TIM: An Efficient Temporal Interaction Module for Spiking Transformer

Reference 2004

Resolution: unresolved; no resolver link, observed 2026-08-03T08:05:00.177494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4e211f8-af38-49f2-bc3e-dd0524671fef · outbound

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

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers DIET-SNN: Direct Input Encoding With Leakage and Threshold Optimization in Deep Spiking Neural Networks

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-03T08:05:00.095767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d11b8bc-be9a-40ed-80b6-010afc92a343 · outbound

This paper cites Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network.

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-03T08:04:59.739523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6d70447-5c50-40fb-a198-8252e3568dca · outbound

This paper cites Spiking Deep Networks with LIF Neurons.

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers Spiking Deep Networks with LIF Neurons

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-03T08:04:59.850524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7659b19b-e329-49d6-9583-302bc6e826a5 · outbound

This paper cites Spiking transformer with experts mixture.Advances in Neural Information Processing Systems, 37:10036–10059, 2024b.

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers Spiking transformer with experts mixture.Advances in Neural Information Processing Systems, 37:10036–10059, 2024b

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-03T08:05:01.432573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d18dcdd5-9e7f-4e20-8dd0-216fd5013e09 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-03T08:04:59.588676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e75f2dba-f86e-4346-bd02-3055d6b1f79e · outbound

This paper cites Step: A unified spiking transformer eval- uation platform for fair and reproducible benchmarking.

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers Step: A unified spiking transformer eval- uation platform for fair and reproducible benchmarking

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T08:05:00.286939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c630f97b-ac71-43f1-acaf-c6ad86e043a0 · outbound

This paper cites and Vishwanath, S.

TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers and Vishwanath, S

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T08:04:59.970441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.