Paper Citation Record · LEDGER

Leaner Transformers: More Heads, Less Depth

As of 22 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2505.20802.

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

pith.paper-citation-record.v1
2505.20802 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:53:13.305354Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

45 of 45 outbound references displayed

verified exact0
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unresolved13
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aa05ce8e-8208-4cdb-91a9-9f0d85dfee56 · outbound

This paper cites A deep conditioning treatment of neural networks.

Leaner Transformers: More Heads, Less Depth A deep conditioning treatment of neural networks

Reference 1

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Observation 01750a21-676d-4050-b7cd-1a2ce70de4ec · outbound

This paper cites Xcit: Cross-covariance image transformers.

Leaner Transformers: More Heads, Less Depth Xcit: Cross-covariance image transformers

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:19.156179Z

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Observation 622a335c-181c-42a2-be4b-66791f259c5f · outbound

This paper cites On the op- timization of deep networks: Implicit acceleration by over- parameterization.

Leaner Transformers: More Heads, Less Depth On the op- timization of deep networks: Implicit acceleration by over- parameterization

Reference 3

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Observation 3d4441ca-1002-4665-9104-6606be01699b · outbound

This paper cites End-to- end object detection with transformers.

Leaner Transformers: More Heads, Less Depth End-to- end object detection with transformers

Reference 4

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Observation 832261df-1c02-4e3d-9e0e-6dc5476c78b7 · outbound

This paper cites Rethinking attention with performers.

Leaner Transformers: More Heads, Less Depth Rethinking attention with performers

Reference 5

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Observation a1419588-3169-40f8-ad3a-796f240d693b · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Leaner Transformers: More Heads, Less Depth BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 6

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Observation 980b9ea1-4735-4fe4-986c-45f30d8d05f2 · outbound

This paper cites Davit: Dual attention vision transform- ers.

Leaner Transformers: More Heads, Less Depth Davit: Dual attention vision transform- ers

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:18.551570Z

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Observation 93c57150-92b7-43bf-bdaf-4e2adab4804a · outbound

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

Leaner Transformers: More Heads, Less Depth An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 8

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Observation ef95e9bf-f52e-4ea4-ad23-0d8c634941a0 · outbound

This paper cites TinyStories: How Small Can Language Models Be and Still Speak Coherent English?.

Leaner Transformers: More Heads, Less Depth TinyStories: How Small Can Language Models Be and Still Speak Coherent English?

Reference 9

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Observation c2f8fbce-d0ed-46bb-ae0b-cc288c2dc65a · outbound

This paper cites Drive like a human: Rethinking au- tonomous driving with large language models.

Leaner Transformers: More Heads, Less Depth Drive like a human: Rethinking au- tonomous driving with large language models

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:18.332722Z

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Observation 4076683d-2bb3-46c1-844a-813c4778f542 · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

Leaner Transformers: More Heads, Less Depth The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 11

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Observation 94949c45-019d-4f6a-8097-fccfe740ac80 · outbound

This paper cites Cramming.

Leaner Transformers: More Heads, Less Depth Cramming

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:18.181276Z

Source-reported events for the cited work

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Observation 8122e36f-47df-4a41-b51d-88980b3c09d1 · outbound

This paper cites Cramming: Training a language model on a single gpu in one day.

Leaner Transformers: More Heads, Less Depth Cramming: Training a language model on a single gpu in one day

Reference 13

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Observation d44dec49-3d12-4736-8a91-3f0a003c6f62 · outbound

This paper cites Transformer in transformer.

Leaner Transformers: More Heads, Less Depth Transformer in transformer

Reference 14

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Source-reported events for the cited work

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Observation a817ca96-d9b8-4b60-b04e-993a1772915f · outbound

This paper cites Neu- ral tangent kernel: Convergence and generalization in neural networks.

Leaner Transformers: More Heads, Less Depth Neu- ral tangent kernel: Convergence and generalization in neural networks

Reference 15

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Observation d4433458-c758-451a-b672-a7cd124caa67 · outbound

This paper cites On the size of convolutional neural networks and generalization per- formance.

Leaner Transformers: More Heads, Less Depth On the size of convolutional neural networks and generalization per- formance

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:17.540790Z

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Observation 28f6b77f-0022-4929-9d0e-ccb0d27f4a67 · outbound

This paper cites Re- former: The efficient transformer.

Leaner Transformers: More Heads, Less Depth Re- former: The efficient transformer

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:17.374388Z

Source-reported events for the cited work

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Observation 8c440c53-4fd6-4377-88bc-30bded8e3cc9 · outbound

This paper cites The Depth-to-Width Interplay in Self-Attention.

Leaner Transformers: More Heads, Less Depth The Depth-to-Width Interplay in Self-Attention

Reference 18

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Source-reported events for the cited work

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Observation a4656912-f2d7-4c95-9724-11c96f5988fe · outbound

This paper cites Limits to depth efficiencies of self-attention.

Leaner Transformers: More Heads, Less Depth Limits to depth efficiencies of self-attention

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:17.164882Z

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Observation 8bcb3d35-6155-4a67-adfa-a7f17636c20f · outbound

This paper cites On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond.

Leaner Transformers: More Heads, Less Depth On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond

Reference 20

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Observation 424b5107-c515-41ca-ab89-a6e7104cf9e4 · outbound

This paper cites Loss land- scapes and optimization in over-parameterized non-linear systems and neural networks.

Leaner Transformers: More Heads, Less Depth Loss land- scapes and optimization in over-parameterized non-linear systems and neural networks

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:16.915596Z

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Observation 4b3b603c-76cd-40f3-89ff-27477b4cdb5b · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Leaner Transformers: More Heads, Less Depth Swin transformer: Hierarchical vision transformer using shifted windows

Reference 22

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Observation ed0b4e89-b93e-4d38-b190-339e79bcc449 · outbound

This paper cites The expressive power of neural networks: A view from the width.

Leaner Transformers: More Heads, Less Depth The expressive power of neural networks: A view from the width

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:16.716353Z

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Observation 721e7453-42f3-4eeb-9e84-7b01e24dea3b · outbound

This paper cites Transfusion: Multi-modal fusion network for semantic segmentation.

Leaner Transformers: More Heads, Less Depth Transfusion: Multi-modal fusion network for semantic segmentation

Reference 24

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Observation 8bf7a85e-954d-44b9-934e-6add32e88502 · outbound

This paper cites Numerical optimiza- tion.

Leaner Transformers: More Heads, Less Depth Numerical optimiza- tion

Reference 25

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Observation afafbf8c-2619-4c9a-be87-d9271319f90d · outbound

This paper cites The impact of depth and width on transformer language model generalization.

Leaner Transformers: More Heads, Less Depth The impact of depth and width on transformer language model generalization

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:16.267841Z

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Observation fc66014d-698a-487f-b293-a4faf56edf7e · outbound

This paper cites Exponential expressivity in deep neural networks through transient chaos.

Leaner Transformers: More Heads, Less Depth Exponential expressivity in deep neural networks through transient chaos

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:16.130245Z

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Observation adb98fdc-43f3-4d81-bbe6-48334022aafa · outbound

This paper cites Tiny-stories-gpt.

Leaner Transformers: More Heads, Less Depth Tiny-stories-gpt

Reference 28

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Observation 4e46a6c6-03c5-4f7f-a075-8794bc32805f · outbound

This paper cites Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data.

Leaner Transformers: More Heads, Less Depth Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data

Reference 29

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This paper cites Representational strengths and limitations of transformers.

Leaner Transformers: More Heads, Less Depth Representational strengths and limitations of transformers

Reference 30

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Observation 1985930e-d536-4375-a2b6-5680575faf4e · outbound

This paper cites Real analysis: measure theory, integration, and Hilbert spaces.

Leaner Transformers: More Heads, Less Depth Real analysis: measure theory, integration, and Hilbert spaces

Reference 31

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This paper cites How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers.

Leaner Transformers: More Heads, Less Depth How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 32

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This paper cites Long Range Arena: A Benchmark for Efficient Transformers.

Leaner Transformers: More Heads, Less Depth Long Range Arena: A Benchmark for Efficient Transformers

Reference 33

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This paper cites Training data-efficient image transformers & distillation through at- tention.

Leaner Transformers: More Heads, Less Depth Training data-efficient image transformers & distillation through at- tention

Reference 34

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Observation 5849d952-ba2b-4f5b-be49-8e315ee16638 · outbound

This paper cites Width is less important than depth in relu neural networks.

Leaner Transformers: More Heads, Less Depth Width is less important than depth in relu neural networks

Reference 35

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This paper cites Attention is all you need.

Leaner Transformers: More Heads, Less Depth Attention is all you need

Reference 36

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Observation 80c06c48-fc80-4a8e-8931-33c6daf085a9 · outbound

This paper cites High-dimensional probability: An intro- duction with applications in data science.

Leaner Transformers: More Heads, Less Depth High-dimensional probability: An intro- duction with applications in data science

Reference 37

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This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

Leaner Transformers: More Heads, Less Depth GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 38

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Leaner Transformers: More Heads, Less Depth Linformer: Self-attention with linear complex- ity

Reference 39

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This paper cites Github repository, 2021.

Leaner Transformers: More Heads, Less Depth Github repository, 2021

Reference 40

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This paper cites Nystr¨omformer: A nystr¨om-based algorithm for approximat- ing self-attention.

Leaner Transformers: More Heads, Less Depth Nystr¨omformer: A nystr¨om-based algorithm for approximat- ing self-attention

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:14.156866Z

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Leaner Transformers: More Heads, Less Depth V olo: Vision outlooker for visual recog- nition

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:14.014039Z

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Observation 73f1affc-3c99-4491-a8f3-2d1395b2a604 · outbound

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Leaner Transformers: More Heads, Less Depth cosformer: rethinking softmax in attention

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:13.848094Z

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This paper cites Understanding generalization and optimization performance of deep cnns.

Leaner Transformers: More Heads, Less Depth Understanding generalization and optimization performance of deep cnns

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:13.683260Z

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Observation edd4c23a-d92b-4435-82b4-51a4a181152e · outbound

This paper cites A robustly optimized bert pre-training approach with post-training.

Leaner Transformers: More Heads, Less Depth A robustly optimized bert pre-training approach with post-training

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:53:13.523878Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.