Paper Citation Record · LEDGER

Simple Convergence Proof of Adam From a Sign-like Descent Perspective

As of 9 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 2 inbound Pith citation observations for arXiv:2507.05966.

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

pith.paper-citation-record.v1
2507.05966 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:25:24.982987Z

measured 57 of 57 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T09:08:41.993925Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:09:44.606239Z

Reference resolution

55 of 55 outbound references displayed

verified exact0
verified fuzzy32
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External citation measurements

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Outbound references

Observation 35277eaa-d935-45a7-a922-e10106887638 · outbound

This paper cites Lower bounds for non-convex stochastic optimization.Mathematical Programming, 199(1-2):165–214, 2023.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Lower bounds for non-convex stochastic optimization.Mathematical Programming, 199(1-2):165–214, 2023

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.658393Z

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 96dffac1-f544-44e4-86e9-98d132fd80ab · outbound

This paper cites SGD with AdaGrad stepsizes: Full adaptivity with high probability to unknown parameters, unbounded gradients and affine variance.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective SGD with AdaGrad stepsizes: Full adaptivity with high probability to unknown parameters, unbounded gradients and affine variance

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.648432Z

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 705886f5-1206-4618-877e-504f020888e5 · outbound

This paper cites Dissecting Adam: The sign, magnitude and variance of stochastic gradients.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Dissecting Adam: The sign, magnitude and variance of stochastic gradients

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.637157Z

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 d6b50d4e-acfd-4e70-9c5e-bdbee63f31c4 · outbound

This paper cites signSGD: Compressed optimisation for non-convex problems.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective signSGD: Compressed optimisation for non-convex problems

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.627021Z

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

Observation 4fd4a7bd-b944-42a2-8ba6-9538afd26af6 · outbound

This paper cites Gradient convergence in gradient methods with errors.SIAM Journal on Optimization, 10(3):627–642, 2000.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Gradient convergence in gradient methods with errors.SIAM Journal on Optimization, 10(3):627–642, 2000

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.789519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1448b4a-3e5b-4cff-96dd-c0c1f9f44b13 · outbound

This paper cites Optimization methods for large-scale machine learning.SIAM review, 60(2):223–311, 2018.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Optimization methods for large-scale machine learning.SIAM review, 60(2):223–311, 2018

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.794447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74849577-cce8-4e77-9b24-b06173cb34f3 · outbound

This paper cites Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901, 2020.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901, 2020

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.798716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc0b04f6-4ce8-412b-aecb-1d4f532ff784 · outbound

This paper cites Towards practical Adam: Non-convexity, convergence theory, and mini-batch acceleration.Journal of Machine Learning Research, 23(229):1–47, 2022.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Towards practical Adam: Non-convexity, convergence theory, and mini-batch acceleration.Journal of Machine Learning Research, 23(229):1–47, 2022

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.598173Z

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 11d3e333-4110-4097-84c0-8327c374b3d8 · outbound

This paper cites Lion Secretly Solves Constrained Optimization: As Lyapunov Predicts.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Lion Secretly Solves Constrained Optimization: As Lyapunov Predicts

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.805241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 559654b5-1189-44e8-8fa5-21b20f5338ab · outbound

This paper cites Symbolic Discovery of Optimization Algorithms.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Symbolic Discovery of Optimization Algorithms

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.809707Z

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Observation 3a3bebb0-c25d-427c-b034-75336438fa83 · outbound

This paper cites On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.814261Z

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Observation 94fadaeb-e8fe-4cfa-9c53-c40e5704f401 · outbound

This paper cites PaLM: Scaling language modeling with pathways.Journal of Machine Learning Research, 24(240):1– 113, 2023.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective PaLM: Scaling language modeling with pathways.Journal of Machine Learning Research, 24(240):1– 113, 2023

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.588146Z

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 a8cafaca-0910-411d-9072-79e42d722862 · outbound

This paper cites Ro- bustness to unbounded smoothness of generalized signSGD.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Ro- bustness to unbounded smoothness of generalized signSGD

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.577020Z

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 e6719adf-27b9-470a-b54b-92e36ae55226 · outbound

This paper cites A Simple Convergence Proof of Adam and Adagrad.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective A Simple Convergence Proof of Adam and Adagrad

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.824358Z

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Observation d9a34d3d-ac87-4bec-91d1-98ccb4585ba9 · outbound

This paper cites The Llama 3 Herd of Models.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective The Llama 3 Herd of Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.828053Z

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Unavailable: canonical work link unavailable.

Observation d07053c8-09ea-4b27-a942-b074b378a25f · outbound

This paper cites Beyond uniform smoothness: A stopped analysis of adaptive SGD.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Beyond uniform smoothness: A stopped analysis of adaptive SGD

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.566367Z

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 5b93e733-4e24-4a03-aed9-f8f51bc75240 · outbound

This paper cites The power of adaptivity in SGD: Self-tuning step sizes with unbounded gradients and affine variance.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective The power of adaptivity in SGD: Self-tuning step sizes with unbounded gradients and affine variance

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.556055Z

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 6ea988f4-e523-4dcb-ab6c-2eef37107b2c · outbound

This paper cites Deep residual learning for image recognition.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Deep residual learning for image recognition

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.545996Z

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 d96d8d6a-9d75-4bb4-962d-b3334ba293a4 · outbound

This paper cites Neural networks for machine learning lecture 6a overview of mini-batch gradient descent.Cited on, 14(8):2, 2012.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Neural networks for machine learning lecture 6a overview of mini-batch gradient descent.Cited on, 14(8):2, 2012

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.536142Z

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 41b284f3-d020-4db4-bb2f-7fdd13288949 · outbound

This paper cites High Probability Convergence of Adam Under Unbounded Gradients and Affine Variance Noise.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective High Probability Convergence of Adam Under Unbounded Gradients and Affine Variance Noise

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.845097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a4893c6-141d-457a-bd52-17523901a20d · outbound

This paper cites On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.849410Z

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Unavailable: canonical work link unavailable.

Observation 59423576-3cf6-4779-a3d6-1b4818115798 · outbound

This paper cites Parameter-agnostic optimization under relaxed smoothness.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Parameter-agnostic optimization under relaxed smoothness

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.853400Z

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Observation 4398f761-50bc-4597-900c-36f816439481 · outbound

This paper cites Non-convex distributionally robust optimization: Non-asymptotic analysis.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Non-convex distributionally robust optimization: Non-asymptotic analysis

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.518589Z

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 ce223768-7387-4808-95b4-27633856fca0 · outbound

This paper cites Linear convergence of gradient and proximal- gradient methods under the polyak-łojasiewicz condition.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Linear convergence of gradient and proximal- gradient methods under the polyak-łojasiewicz condition

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.507326Z

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

Observation e83368b9-7540-46fa-acf7-1dc72d1cee52 · outbound

This paper cites Adam: A method for stochastic optimization.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Adam: A method for stochastic optimization

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.864941Z

Source-reported events for the cited work

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Observation 5859ac37-9c0d-49ab-a7e2-6da17c984bb0 · outbound

This paper cites Segment Anything.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Segment Anything

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.868543Z

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Observation aa74ad19-d0b2-4daa-9cd1-f9cf1252fe95 · outbound

This paper cites Imagenet classification with deep convolutional neural networks.Communications of the ACM, 60(6):84–90, 2017.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Imagenet classification with deep convolutional neural networks.Communications of the ACM, 60(6):84–90, 2017

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.872541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e6c8338-7d86-4ed5-b889-518367398210 · outbound

This paper cites Noise Is Not the Main Factor Behind the Gap Between SGD and Adam on Transformers, but Sign Descent Might Be.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Noise Is Not the Main Factor Behind the Gap Between SGD and Adam on Transformers, but Sign Descent Might Be

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.877360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 695b4b05-6208-440c-9b30-0ffb1201aa38 · outbound

This paper cites Heavy-Tailed Class Imbalance and Why Adam Outperforms Gradient Descent on Language Models.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Heavy-Tailed Class Imbalance and Why Adam Outperforms Gradient Descent on Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.881398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98eeaa30-7d20-440d-a490-6ffef12a0cfc · outbound

This paper cites Convergence of Adam under relaxed assumptions.Advances in Neural Information Processing Systems, 36, 2023.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Convergence of Adam under relaxed assumptions.Advances in Neural Information Processing Systems, 36, 2023

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.457726Z

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

Observation 78af7bd9-1972-4135-a700-1b1379f29afd · outbound

This paper cites An improved analysis of stochastic gradient descent with momentum.Advances in Neural Information Processing Systems, 33:18261–18271, 2020.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective An improved analysis of stochastic gradient descent with momentum.Advances in Neural Information Processing Systems, 33:18261–18271, 2020

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.427096Z

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 c666a50c-643a-4d26-8eb0-611140135ec0 · outbound

This paper cites A convnet for the 2020s.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective A convnet for the 2020s

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.892988Z

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Observation b2dafb9f-2064-482c-b675-e4896ba17cf1 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Learning transferable visual models from natural language supervision

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.896430Z

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Observation 5c97f269-0659-4efb-8d09-95bc73b6f490 · outbound

This paper cites On the convergence of Adam and beyond.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective On the convergence of Adam and beyond

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.391718Z

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

Observation db976a6c-0f1f-4376-8762-6ef03e8dba9f · outbound

This paper cites A direct adaptive method for faster backpropagation learning: The rprop algorithm.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective A direct adaptive method for faster backpropagation learning: The rprop algorithm

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.378687Z

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 614c7d1e-603f-4da3-99db-ef483b1037b1 · outbound

This paper cites 1-bit stochastic gradient descent and its application to data-parallel distributed training of speech DNNs.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective 1-bit stochastic gradient descent and its application to data-parallel distributed training of speech DNNs

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.366565Z

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

Observation 6f05deac-e38b-45e5-9550-8b886c97128f · outbound

This paper cites RMSProp converges with proper hyperparameter.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective RMSProp converges with proper hyperparameter

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.353974Z

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

Observation 0bdee0cc-0e89-4cf3-b983-c3ef9374b9ab · outbound

This paper cites Scalable distributed DNN training using commodity GPU cloud computing.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Scalable distributed DNN training using commodity GPU cloud computing

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.341132Z

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 5d694ec4-c544-4ced-a699-313f53c5b24a · outbound

This paper cites Momentum ensures convergence of signSGD under weaker assumptions.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Momentum ensures convergence of signSGD under weaker assumptions

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.328991Z

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 ba6d9a05-1f48-4624-948d-73fb7e46fc11 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective LLaMA: Open and Efficient Foundation Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.920766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99f1e25a-dc36-4a05-93ce-c647c55d7089 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.924812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccbd7f88-9575-47e9-a65b-adb19b0da7d4 · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.928366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f263129-d093-4f15-ad2a-a9d38abc9478 · outbound

This paper cites Convergence of AdaGrad for non-convex objectives: Simple proofs and relaxed assumptions.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Convergence of AdaGrad for non-convex objectives: Simple proofs and relaxed assumptions

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.303573Z

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 111bb916-7cb6-42ba-9e6a-69d9dd5519d7 · outbound

This paper cites Convergence of AdaGrad for non-convex objectives: Simple proofs and relaxed assumptions.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Convergence of AdaGrad for non-convex objectives: Simple proofs and relaxed assumptions

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.287400Z

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 c5effdbe-3f6a-4a2d-9c96-7e692818b58a · outbound

This paper cites On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.940732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d6c6492-c62e-493a-a3cf-bed39aa2fb0f · outbound

This paper cites Provable adaptivity of Adam under non-uniform smoothness.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Provable adaptivity of Adam under non-uniform smoothness

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.272498Z

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 4988bcb3-deb1-4289-acc9-0879ce3e95a6 · outbound

This paper cites Convnext v2: Co-designing and scaling convnets with masked autoencoders.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Convnext v2: Co-designing and scaling convnets with masked autoencoders

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.257319Z

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 7c6d03a7-2de4-4203-a7a9-4740bcf55b6a · outbound

This paper cites Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:24.952647Z

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Observation 656af517-df00-4701-a41e-20165d37edcf · outbound

This paper cites Improved analysis of clipping algorithms for non-convex optimization.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Improved analysis of clipping algorithms for non-convex optimization

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.241972Z

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 016ddfac-a4f9-48b5-a061-a9d4439b32e2 · outbound

This paper cites Why gradient clipping accelerates training: A theoretical justification for adaptivity.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Why gradient clipping accelerates training: A theoretical justification for adaptivity

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.227076Z

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 d2556d20-38d5-4809-95ac-bed2b40ba918 · outbound

This paper cites Adam can converge without any modification on update rules.Advances in neural information processing systems, 35:28386–28399, 2022.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Adam can converge without any modification on update rules.Advances in neural information processing systems, 35:28386–28399, 2022

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.212572Z

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 9d9bc7e9-2622-4c46-8652-5032f800f01d · outbound

This paper cites Recently, [20] provably demonstrate the convergence rate of vanilla Adam in high probability perspective, but it only works with the stronger coordinate-wise affine variance.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective Recently, [20] provably demonstrate the convergence rate of vanilla Adam in high probability perspective, but it only works with the stronger coordinate-wise affine variance

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.196991Z

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 4c749ebe-f963-4b3d-bde8-d55404ebc44e · outbound

This paper cites [49] posits that it is also equivalent to an affine form of the gradient norm for the first-order differentiable function.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective [49] posits that it is also equivalent to an affine form of the gradient norm for the first-order differentiable function

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.183411Z

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 8f602a4d-d4a5-4547-9308-c1a510dc039f · outbound

This paper cites [30] further extended the linear (L0, L1)-smooth to the generalized polynomial version, and proved that Adam will converged to O poly(lnT) T 1/4 with the weaker assumption.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective [30] further extended the linear (L0, L1)-smooth to the generalized polynomial version, and proved that Adam will converged to O poly(lnT) T 1/4 with the weaker assumption

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.170475Z

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 ff9b11ab-3777-4ba9-b2ff-005f85315eb2 · outbound

This paper cites tX k=1 βt−k 1 (gk − ∇F(xk)) 2 # | {z } T2 + 1 T T−1X t=0 E.

Simple Convergence Proof of Adam From a Sign-like Descent Perspective tX k=1 βt−k 1 (gk − ∇F(xk)) 2 # | {z } T2 + 1 T T−1X t=0 E

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:25:25.155585Z

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.

Pith citing papers

Observation 0ac89055-0f85-475c-a8c2-d8c0a1c99366 · inbound

When and Why SignSGD Outperforms SGD: A Theoretical Study Based on $\ell_1$-norm Lower Bounds cites this paper.

When and Why SignSGD Outperforms SGD: A Theoretical Study Based on $\ell_1$-norm Lower Bounds Simple Convergence Proof of Adam From a Sign-like Descent Perspective

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:21:07.519300Z

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 17e2f267-9e45-466b-a6e2-68fe92e9bd80 · inbound

Open Problem: Is AdamW Effective Under Heavy-Tailed Noise? cites this paper.

Open Problem: Is AdamW Effective Under Heavy-Tailed Noise? Simple Convergence Proof of Adam From a Sign-like Descent Perspective

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-04T10:09:44.608129Z

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.