Paper Citation Record · LEDGER

Enhancing compact convolutional transformers with super attention

As of 7 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2508.18960.

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

pith.paper-citation-record.v1
2508.18960 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:06:14.458362Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

14 of 14 outbound references displayed

verified exact0
verified fuzzy1
unresolved11
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ef8e7f9b-7ebc-4014-a6d5-e324f47afdb4 · outbound

This paper cites Escaping the Big Data Paradigm with Compact Transformers.

Enhancing compact convolutional transformers with super attention Escaping the Big Data Paradigm with Compact Transformers

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:14.398738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fe19501-ef97-4b5d-bdaa-df3de26baa2e · outbound

This paper cites doi: 10.18653/v1/ 2022.findings-emnlp.99.

Enhancing compact convolutional transformers with super attention doi: 10.18653/v1/ 2022.findings-emnlp.99

Reference 5

Resolution: malformed identifier; no resolver link, observed 2026-08-05T16:06:14.404401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64ad2ad0-021c-44ab-a671-194a217a42ed · outbound

This paper cites Cost-Effective Attention Mechanisms for Low Resource Settings: Necessity & Sufficiency of Linear Transformations.

Enhancing compact convolutional transformers with super attention Cost-Effective Attention Mechanisms for Low Resource Settings: Necessity & Sufficiency of Linear Transformations

Reference 7

Resolution: metadata mismatch; local_arxiv, observed 2026-08-05T16:06:14.685538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 464ad2bf-1c83-4c53-ae92-5278ebe1acc9 · outbound

This paper cites doi: https://doi.org/10.1016/j.neucom.2023.127063.

Enhancing compact convolutional transformers with super attention doi: https://doi.org/10.1016/j.neucom.2023.127063

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:14.436260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 342d9fec-7898-4ea9-95be-6a72925cb26a · outbound

This paper cites CvT: Introducing Convolutions to Vision Transformers.

Enhancing compact convolutional transformers with super attention CvT: Introducing Convolutions to Vision Transformers

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:14.447164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77667219-add1-41bf-ad91-3d62c193366b · outbound

This paper cites Exact solutions to the nonlinear dynamics of learning in deep linear neural networks.

Enhancing compact convolutional transformers with super attention Exact solutions to the nonlinear dynamics of learning in deep linear neural networks

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:14.422608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7016da55-e739-4284-b39f-5450aca25335 · outbound

This paper cites Haiping Wu, Bin Xiao, Noel Codella, Mengchen Liu, Xiyang Dai, Lu Yuan, and Lei Zhang.

Enhancing compact convolutional transformers with super attention Haiping Wu, Bin Xiao, Noel Codella, Mengchen Liu, Xiyang Dai, Lu Yuan, and Lei Zhang

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:06:14.772291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 71035cb2-abc0-4f23-a82b-6351aeee45da · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Enhancing compact convolutional transformers with super attention mixup: Beyond Empirical Risk Minimization

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:14.458362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a0494e5-daa6-470f-8828-76e349d8abaf · outbound

This paper cites CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features.

Enhancing compact convolutional transformers with super attention CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:14.452828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 044f5c52-6736-4b19-92c1-876c51cb8275 · outbound

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

Enhancing compact convolutional transformers with super attention An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:14.393248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 907e4757-36ba-4359-a650-e6c9f1287ac8 · outbound

This paper cites an unresolved cited work.

Enhancing compact convolutional transformers with super attention Unresolved cited work

Reference 2022

Resolution: unresolved; raw_fallback, observed 2026-08-05T16:06:14.790009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 81cad6fe-7339-4e3f-bcf8-472a4132a060 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Enhancing compact convolutional transformers with super attention Gaussian Error Linear Units (GELUs)

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:14.410154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab679388-0a74-4ee0-97ca-0309649c3202 · outbound

This paper cites FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision.

Enhancing compact convolutional transformers with super attention FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:14.428458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d041d17a-9a10-418e-8133-0e08fe6e8f56 · outbound

This paper cites DeepSeek-V3 Technical Report.

Enhancing compact convolutional transformers with super attention DeepSeek-V3 Technical Report

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:14.387738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.