Paper Citation Record · LEDGER

Methods for Convex $(L_0,L_1)$-Smooth Optimization: Clipping, Acceleration, and Adaptivity

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2409.14989.

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

pith.paper-citation-record.v1
2409.14989 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T12:38:55.256221Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T20:20:34.589270Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

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 72115b05-738f-407a-ae44-a5cd7453e73a · inbound

Why Do We Need Warm-up? A Theoretical Perspective cites this paper.

Why Do We Need Warm-up? A Theoretical Perspective Methods for Convex $(L_0,L_1)$-Smooth Optimization: Clipping, Acceleration, and Adaptivity

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T12:38:55.256221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54a3ba8c-e914-46b8-a265-e9fb59c12825 · inbound

Frank-Wolfe Algorithms for (L0, L1)-smooth functions cites this paper.

Frank-Wolfe Algorithms for (L0, L1)-smooth functions Methods for Convex $(L_0,L_1)$-Smooth Optimization: Clipping, Acceleration, and Adaptivity

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-18T06:20:58.642480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 45d2dbd3-e2bf-4861-a21a-3007e45b8621 · inbound

Frank-Wolfe Algorithms for (L0, L1)-smooth functions cites this paper.

Frank-Wolfe Algorithms for (L0, L1)-smooth functions Methods for Convex $(L_0,L_1)$-Smooth Optimization: Clipping, Acceleration, and Adaptivity

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-21T20:20:34.591793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1cda66cf-d77e-4585-b2ab-91139169f005 · inbound

Non-Euclidean SGD for Structured Optimization: Unified Analysis and Improved Rates cites this paper.

Non-Euclidean SGD for Structured Optimization: Unified Analysis and Improved Rates Methods for Convex $(L_0,L_1)$-Smooth Optimization: Clipping, Acceleration, and Adaptivity

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T22:20:05.519647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cce0ba99-4083-49dd-8a86-f826b2647637 · inbound

Stochastic Non-Smooth Convex Optimization with Unbounded Gradients cites this paper.

Stochastic Non-Smooth Convex Optimization with Unbounded Gradients Methods for Convex $(L_0,L_1)$-Smooth Optimization: Clipping, Acceleration, and Adaptivity

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T15:17:39.271516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b775a862-dceb-4b67-95f1-2c412ac17a3a · inbound

Normalized First-Order Methods for Convex (L0, L1)-Smooth Optimization with Inexact Gradients cites this paper.

Normalized First-Order Methods for Convex (L0, L1)-Smooth Optimization with Inexact Gradients Methods for Convex $(L_0,L_1)$-Smooth Optimization: Clipping, Acceleration, and Adaptivity

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-30T15:28:01.796584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.