Paper Citation Record · LEDGER

Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2105.02723.

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

pith.paper-citation-record.v1
2105.02723 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:07:43.800368Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T22:36:36.169056Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0de57c2a-44bd-4e4b-a2e4-6b7f515bb1e0 · inbound

Flopping for FLOPs: Leveraging equivariance for computational efficiency cites this paper.

Flopping for FLOPs: Leveraging equivariance for computational efficiency Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-08T20:07:43.800368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 278d1f03-fc35-40eb-ae22-7c2807cd36f0 · inbound

FW-GAN: Frequency-Driven Handwriting Synthesis with Wave-Modulated MLP Generator cites this paper.

FW-GAN: Frequency-Driven Handwriting Synthesis with Wave-Modulated MLP Generator Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-05T14:41:43.849918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfa77d50-add5-4891-9d42-be652194cc17 · inbound

Toeplitz MLP Mixers are Low Complexity, Information-Rich Sequence Models cites this paper.

Toeplitz MLP Mixers are Low Complexity, Information-Rich Sequence Models Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:45:56.375147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d26049c8-b031-49d2-9021-4a641826cf92 · inbound

SpiS-GAN: Spiral-Modulated Handwriting Synthesis with Star Operation cites this paper.

SpiS-GAN: Spiral-Modulated Handwriting Synthesis with Star Operation Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-07-09T22:36:36.170391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c1c3903f-c926-4992-af99-9e931913f734 · inbound

FastTPS: An Optimized Method for LLM Token Phase for AI accelerators cites this paper.

FastTPS: An Optimized Method for LLM Token Phase for AI accelerators Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet

Reference 56

Resolution: unresolved; no resolver link, observed 2026-07-14T06:16:09.070414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3aaa3980-de17-46d6-8bb3-7a8a5122332b · inbound

ST-LoRA: Single Trajectory LoRA Ensemble for Uncertainty Aware Agricultural Segmentation cites this paper.

ST-LoRA: Single Trajectory LoRA Ensemble for Uncertainty Aware Agricultural Segmentation Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet

Reference 180

Resolution: unresolved; no resolver link, observed 2026-08-06T00:10:40.057069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.