Paper Citation Record · LEDGER

Towards Distributed Neural Architectures

As of 7 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2506.22389.

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

pith.paper-citation-record.v1
2506.22389 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:14:20.461704Z

measured 31 of 31 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

31 of 31 outbound references displayed

verified exact0
verified fuzzy9
unresolved21
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b0975920-8ccb-4fc5-bfeb-2264c07accdc · outbound

This paper cites GPT-4 Technical Report.

Towards Distributed Neural Architectures GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:18.370267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2482fa62-7024-41dd-992c-ebe0d7109451 · outbound

This paper cites Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei.

Towards Distributed Neural Architectures Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:18.796382Z

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Observation 280f67af-b0b0-4421-a7a3-b66c0271f621 · outbound

This paper cites Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach.

Towards Distributed Neural Architectures Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:18.944144Z

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Observation 1ca5aea9-79ea-4d95-a551-6c355c8775e5 · outbound

This paper cites This may be because we are not considering a setting with high sparsity.

Towards Distributed Neural Architectures This may be because we are not considering a setting with high sparsity

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:21.567025Z

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 16ee2b9c-a491-44bb-b343-14df6bd663b4 · outbound

This paper cites DeepSeek-V3 Technical Report.

Towards Distributed Neural Architectures DeepSeek-V3 Technical Report

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:19.357714Z

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Observation b37c74e1-eadf-4001-8422-2a432370ff72 · outbound

This paper cites DARTS: Differentiable Architecture Search.

Towards Distributed Neural Architectures DARTS: Differentiable Architecture Search

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:19.416905Z

Source-reported events for the cited work

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Observation 45d82e4b-be64-4207-a54c-5c5bbec99369 · outbound

This paper cites Fineweb-edu: the finest collection of educational content, 2024.https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu.

Towards Distributed Neural Architectures Fineweb-edu: the finest collection of educational content, 2024.https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:22.111671Z

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 691fbcff-885e-4b63-9d50-80ac488b6cdc · outbound

This paper cites Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws.

Towards Distributed Neural Architectures Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:19.596966Z

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Observation d1811a32-701b-46bc-9a0f-716da38d2905 · outbound

This paper cites Deep Information Propagation.

Towards Distributed Neural Architectures Deep Information Propagation

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:19.643965Z

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Observation b3c29bac-d4fe-4df1-bc35-eb61e82108aa · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

Towards Distributed Neural Architectures Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:19.690467Z

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Observation 2a4618a6-8bc6-4de1-82ac-58aa2f2a9a07 · outbound

This paper cites Dropout: a simple way to prevent neural networks from overfitting.The journal of machine learning research, 15(1):1929–1958,.

Towards Distributed Neural Architectures Dropout: a simple way to prevent neural networks from overfitting.The journal of machine learning research, 15(1):1929–1958,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:22.010935Z

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 66a3de26-abb7-40ef-a9d7-45045dcee1bd · outbound

This paper cites torchtune: Pytorch’s finetuning library, April 2024.https//github.com/ pytorch/torchtune.

Towards Distributed Neural Architectures torchtune: Pytorch’s finetuning library, April 2024.https//github.com/ pytorch/torchtune

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:21.905199Z

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 9c6aa4a5-2d58-45df-9390-c1ea56231cb4 · outbound

This paper cites Neural Architecture Search with Reinforcement Learning.

Towards Distributed Neural Architectures Neural Architecture Search with Reinforcement Learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:19.952473Z

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Observation 126d581e-3eb2-482f-8a24-b3638f6ea7a0 · outbound

This paper cites an unresolved cited work.

Towards Distributed Neural Architectures Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:14:21.820871Z

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 ba1c9cb3-de61-4bc8-baaf-a7e2e568a5b4 · outbound

This paper cites B Module Usage and Load Balancing We plot the module usage distribution for all DNA models used in the main text in Fig.

Towards Distributed Neural Architectures B Module Usage and Load Balancing We plot the module usage distribution for all DNA models used in the main text in Fig

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:21.678283Z

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 6395a7bd-f507-47d1-b607-48576b07aec8 · outbound

This paper cites The random noise is per-pixel zero-mean, and has a linearly decaying variance, starting at 1 and ending at 0 by the end of the optimization procedure.

Towards Distributed Neural Architectures The random noise is per-pixel zero-mean, and has a linearly decaying variance, starting at 1 and ending at 0 by the end of the optimization procedure

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:21.382742Z

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 bbb959d7-42ec-4192-bbe4-8f53e54d3e56 · outbound

This paper cites 3, we find that the patches following the same path in a randomly initialized model share much greater visual similarities.

Towards Distributed Neural Architectures 3, we find that the patches following the same path in a randomly initialized model share much greater visual similarities

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:21.216489Z

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 08fb4c44-9031-43fa-a905-51093eb1bc92 · outbound

This paper cites 9 is a zoomed-in version of those two figures.

Towards Distributed Neural Architectures 9 is a zoomed-in version of those two figures

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:21.112995Z

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 88848d09-fc48-4bfe-9fbd-977fbd2abc37 · outbound

This paper cites Scaling Laws for Neural Language Models.

Towards Distributed Neural Architectures Scaling Laws for Neural Language Models

Reference 1991

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:19.232811Z

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Observation 5161ef2f-64d8-456b-9d59-5bfba7bd16c5 · outbound

This paper cites RACE: Large-scale ReAding comprehension dataset from examinations.

Towards Distributed Neural Architectures RACE: Large-scale ReAding comprehension dataset from examinations

Reference 2012

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:22.229680Z

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 e9f46559-0637-4498-a104-7320a4abcc83 · outbound

This paper cites LLM Pretraining with Continuous Concepts.

Towards Distributed Neural Architectures LLM Pretraining with Continuous Concepts

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:19.808871Z

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Observation 99607442-268c-4eac-9c9c-65012a38d471 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Towards Distributed Neural Architectures Distilling the Knowledge in a Neural Network

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:19.192043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d627122-77c7-40cc-9e44-a97146762004 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

Towards Distributed Neural Architectures PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 2017

Resolution: malformed identifier; no resolver link, observed 2026-08-06T22:14:19.516841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2f7d93b-bee0-48bd-bfb2-1abc51917bee · outbound

This paper cites Do language models use their depth efficiently? arXiv preprint arXiv:2505.13898,.

Towards Distributed Neural Architectures Do language models use their depth efficiently? arXiv preprint arXiv:2505.13898,

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:18.721573Z

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Observation e1b911b4-b597-4b18-8395-38a785d1ba97 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Towards Distributed Neural Architectures Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:18.635699Z

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Observation ef8483eb-53bc-4772-9926-b0885c75eb1e · outbound

This paper cites FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance.

Towards Distributed Neural Architectures FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:18.547802Z

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Observation 9122c42c-cc6e-464e-84c7-8063b72564ae · outbound

This paper cites LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding.

Towards Distributed Neural Architectures LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:18.881708Z

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Observation 538acbe2-ac9c-413a-928f-44ade83f4014 · outbound

This paper cites The Llama 3 Herd of Models.

Towards Distributed Neural Architectures The Llama 3 Herd of Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:19.055624Z

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Observation 1e1d56b4-b56f-412e-8ea8-f24089f2cff0 · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

Towards Distributed Neural Architectures Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:18.461421Z

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Observation a0a084e5-e6ef-4663-85d2-3565f95c0be8 · outbound

This paper cites The Unreasonable Ineffectiveness of the Deeper Layers.

Towards Distributed Neural Architectures The Unreasonable Ineffectiveness of the Deeper Layers

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:19.114883Z

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Observation 98349d3c-4cf6-4b1e-bfa9-44ccd5c843da · outbound

This paper cites What do Vision Transformers Learn? A Visual Exploration.

Towards Distributed Neural Architectures What do Vision Transformers Learn? A Visual Exploration

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:19.008165Z

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Pith citing papers

No inbound Pith citation observations are available.