Paper Citation Record · LEDGER

When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2106.01548.

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

pith.paper-citation-record.v1
2106.01548 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 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 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:15:47.098749Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

103
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 8febaff3-2ab2-4aa5-b1d0-617cdeb1442c · inbound

TDVE-Assessor: Benchmarking and Evaluating the Quality of Text-Driven Video Editing with LMMs cites this paper.

TDVE-Assessor: Benchmarking and Evaluating the Quality of Text-Driven Video Editing with LMMs When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T14:15:47.098749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7300abd-98b4-4076-8181-07c453209977 · inbound

ReMem: Mutual Information-Aware Fine-tuning of Pretrained Vision Transformers for Effective Knowledge Distillation cites this paper.

ReMem: Mutual Information-Aware Fine-tuning of Pretrained Vision Transformers for Effective Knowledge Distillation When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-06T21:59:02.184937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b51d2024-dffd-4dff-8b70-f427e1b6211f · inbound

Underwater Monocular Metric Depth Estimation: Real-World Benchmarks and Synthetic Fine-Tuning with Vision Foundation Models cites this paper.

Underwater Monocular Metric Depth Estimation: Real-World Benchmarks and Synthetic Fine-Tuning with Vision Foundation Models When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T20:40:33.571364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cc95c6e-bf02-4d29-ba3f-3dfaeaf754c0 · inbound

Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and Physics cites this paper.

Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and Physics When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T20:29:56.985625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29ed7f32-3fd8-434c-a9c0-0bbfff544124 · inbound

Attributing Data for Sharpness-Aware Minimization cites this paper.

Attributing Data for Sharpness-Aware Minimization When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T20:02:06.057895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f4c89bb-98de-41ad-b10d-a61cb51e2ee9 · inbound

Learning from Limited and Imperfect Data cites this paper.

Learning from Limited and Imperfect Data When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T13:09:54.209778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ffa1025-c933-45f4-bda9-2d1b764a115a · inbound

Enhancing Wireless Networks for IoT with Large Vision Models: Foundations and Applications cites this paper.

Enhancing Wireless Networks for IoT with Large Vision Models: Foundations and Applications When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T10:06:13.965784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0ceef31-6d69-43dc-b878-6967439755f9 · inbound

Flat Minima and Generalization: Insights from Stochastic Convex Optimization cites this paper.

Flat Minima and Generalization: Insights from Stochastic Convex Optimization When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T23:59:02.427514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7e19917-a178-4957-ba1d-f7716ae620ea · inbound

Wolkowicz-Styan Upper Bound on the Hessian Eigenspectrum for Cross-Entropy Loss in Nonlinear Smooth Neural Networks cites this paper.

Wolkowicz-Styan Upper Bound on the Hessian Eigenspectrum for Cross-Entropy Loss in Nonlinear Smooth Neural Networks When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-10T16:15:34.065014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cb6142c0-8d28-413f-ab03-78dc60ab646c · inbound

How to Scale Mixture-of-Experts: From muP to the Maximally Scale-Stable Parameterization cites this paper.

How to Scale Mixture-of-Experts: From muP to the Maximally Scale-Stable Parameterization When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations

Reference 106

Resolution: verified exact; arxiv_id, observed 2026-05-15T04:49:44.900630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1e29f58b-9674-498e-891f-516f10c5eb79 · inbound

Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges cites this paper.

Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-03T01:27:30.972478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bef03c63-4ce6-4426-b0e2-e15f61550f8d · inbound

Closed-Form Steepest Descent Direction toward Flat Minima: Reducing Upper Bounds on the Loss Hessian Eigenspectrum in Neural Networks cites this paper.

Closed-Form Steepest Descent Direction toward Flat Minima: Reducing Upper Bounds on the Loss Hessian Eigenspectrum in Neural Networks When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-06-30T09:44:36.910529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f98f0b6f-896d-4d96-959a-165cf170f97d · inbound

Sharpness-Aware Minimization and Muon: Robustness under the Spectral Norm cites this paper.

Sharpness-Aware Minimization and Muon: Robustness under the Spectral Norm When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T00:57:38.332324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.