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Paper Citation Record · LEDGER

From Gradient Clipping to Normalization for Heavy Tailed SGD

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2410.13849.

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

pith.paper-citation-record.v1
2410.13849 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 2026-08-08T11:35:29.654217Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T18:35:00.430824Z

Reference resolution

0 of 0 outbound references displayed

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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 753df5e4-3ce7-4448-a215-f3f8b3a16286 · inbound

Sign Operator for Coping with Heavy-Tailed Noise in Non-Convex Optimization: High Probability Bounds Under $(L_0, L_1)$-Smoothness cites this paper.

Sign Operator for Coping with Heavy-Tailed Noise in Non-Convex Optimization: High Probability Bounds Under $(L_0, L_1)$-Smoothness From Gradient Clipping to Normalization for Heavy Tailed SGD

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-08T11:35:29.654217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:35:29.654217Z digest=sha256:d4f750b6830eade1f822f65c8e574189db2630bf31521cc4eb896c7a89229d4b

Observation 5468bc0c-abd7-49c1-b202-5728332833de · inbound

Decentralized Nonconvex Optimization under Heavy-Tailed Noise: Normalization and Optimal Convergence cites this paper.

Decentralized Nonconvex Optimization under Heavy-Tailed Noise: Normalization and Optimal Convergence From Gradient Clipping to Normalization for Heavy Tailed SGD

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-22T15:51:45.753467Z

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.

source=pdf_text observed=2026-05-22T15:49:07.709952Z digest=sha256:acfeafa47731569cf02739793f14943d98059b2ed6af0b142d1858e470446ccc

Observation ba16768c-c791-4cc8-be36-3f5870e83707 · inbound

Lions and Muons: Optimization via Stochastic Frank-Wolfe under Heavy-Tailed Noise cites this paper.

Lions and Muons: Optimization via Stochastic Frank-Wolfe under Heavy-Tailed Noise From Gradient Clipping to Normalization for Heavy Tailed SGD

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T10:58:32.169406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:58:32.169406Z digest=sha256:1e6f9bf5ff7c35a36bb4016300dcdfd1096ec4daeb1df4e6770df5360add2a77

Observation 39ec6762-ae3f-4735-816b-33ca7b420d91 · inbound

Nonconvex Decentralized Stochastic Bilevel Optimization under Heavy-Tailed Noise cites this paper.

Nonconvex Decentralized Stochastic Bilevel Optimization under Heavy-Tailed Noise From Gradient Clipping to Normalization for Heavy Tailed SGD

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-04T16:23:18.824746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:23:18.824746Z digest=sha256:26b1b94543e0599a5dc25321388758c736368390a83bee278de4d01e3910aac4

Observation 2154049b-a439-416f-aeca-f6ac9a30c33b · inbound

Learnability Window in Gated Recurrent Neural Networks cites this paper.

Learnability Window in Gated Recurrent Neural Networks From Gradient Clipping to Normalization for Heavy Tailed SGD

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-03T18:25:44.354196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T18:25:44.354196Z digest=sha256:df6612adbfb8bfb71fa79d0883e1f254aeca87cd8a96638164fd16718458df1d

Observation 04336962-c00f-477f-add2-29e5097a96d0 · inbound

Muon with Nesterov Momentum: Heavy-Tailed Noise and (Randomized) Inexact Polar Decomposition cites this paper.

Muon with Nesterov Momentum: Heavy-Tailed Noise and (Randomized) Inexact Polar Decomposition From Gradient Clipping to Normalization for Heavy Tailed SGD

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:00:56.684325Z

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.

source=pdf_text observed=2026-05-11T00:54:23.683013Z digest=sha256:1c10fb33916d38b98157288584e873bf0120742166964faa83bdc70b6c7c40fd

Observation 6b8863db-28e3-4a2f-9095-4301299e4698 · inbound

Gradient Clipping Beyond Vector Norms: A Spectral Approach for Matrix-Valued Parameters cites this paper.

Gradient Clipping Beyond Vector Norms: A Spectral Approach for Matrix-Valued Parameters From Gradient Clipping to Normalization for Heavy Tailed SGD

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:02:27.367185Z

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.

source=pdf_text observed=2026-05-13T07:01:37.086159Z digest=sha256:f081c72355fa6ebfe2a49b91d6da6158837aa780e5c20085cb8f0903f6aaaa25

Observation 90a8ccb5-bad9-409a-8195-9e6cadc88313 · inbound

Stochastic Zeroth-Order Optimization Under Heavy-Tailed Noise cites this paper.

Stochastic Zeroth-Order Optimization Under Heavy-Tailed Noise From Gradient Clipping to Normalization for Heavy Tailed SGD

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-19T23:22:52.348267Z

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.

source=arxiv_source observed=2026-05-19T23:20:51.410042Z digest=sha256:e0594670bc556d795b3c947109bae2b33c6149037a4abe78f58ea89b53833e51

Observation d8b71b57-ca33-48e4-9cd7-24c5be332308 · inbound

LionMuon: Alternating Spectral and Sign Descent for Efficient Training cites this paper.

LionMuon: Alternating Spectral and Sign Descent for Efficient Training From Gradient Clipping to Normalization for Heavy Tailed SGD

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-20T07:28:06.799388Z

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.

source=pdf_text observed=2026-05-20T07:24:55.516803Z digest=sha256:396bbf13da60ca196e4ae664be645ed6d74d01ecc8d145ca996ba55eb31a232c

Observation 808b4a2a-c5db-43dd-bab0-47b2db711773 · inbound

LionMuon: Alternating Spectral and Sign Descent for Efficient Training cites this paper.

LionMuon: Alternating Spectral and Sign Descent for Efficient Training From Gradient Clipping to Normalization for Heavy Tailed SGD

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-06-30T18:35:00.432272Z

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.

source=pdf_text observed=2026-06-30T18:30:51.719396Z digest=sha256:a11b37fe98dada4730ed5d5825724730a5e7c712f075e8106353d166067a176c

Observation 36095914-1a82-4cdb-9d35-81583ff40c36 · inbound

Zeroth-Order Nonconvex Nonsmooth Optimization with Heavy-Tailed Noise cites this paper.

Zeroth-Order Nonconvex Nonsmooth Optimization with Heavy-Tailed Noise From Gradient Clipping to Normalization for Heavy Tailed SGD

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-06-30T15:04:46.160972Z

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.

source=pdf_text observed=2026-06-30T15:04:30.204185Z digest=sha256:ebe577c4e3906222907d434fecf172ec4b52ede8c376d0d1f8b3705c10692f5f

Observation 79e0caf0-3e15-4331-9627-3ec3c849d026 · inbound

Can Entry-Wise Clipping Give Spectral Control of Stochastic Gradients? cites this paper.

Can Entry-Wise Clipping Give Spectral Control of Stochastic Gradients? From Gradient Clipping to Normalization for Heavy Tailed SGD

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-06-29T18:33:50.879941Z

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.

source=pdf_text observed=2026-06-29T18:26:25.456607Z digest=sha256:b363e4d0d4d1552471d4ce88d46168c2d2eea7c235e18366981b4b257e243ba0

Observation 56c0fa79-fa91-4e10-b6e9-854043afef10 · inbound

Quantum Speedups for Stochastic Optimization with Heavy-Tailed Noise cites this paper.

Quantum Speedups for Stochastic Optimization with Heavy-Tailed Noise From Gradient Clipping to Normalization for Heavy Tailed SGD

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-01T02:25:02.765656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T02:25:02.765656Z digest=sha256:d732ad2c1795469235aa1066e61ecfdffd7332543c50b35ad10aff0db02ab6ae