Pith. sign in

Paper Citation Record · LEDGER

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems

As of 9 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 2 inbound Pith citation observations for arXiv:2506.07397.

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

pith.paper-citation-record.v1
2506.07397 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:47:48.461194Z

measured 16 of 16 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 2026-08-04T13:26:10.160510Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T23:35:45.700681Z

Reference resolution

14 of 14 outbound references displayed

  • verified exact0
  • verified fuzzy7
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f6dd03d9-b49c-4088-aa2f-13671e20fb52 · outbound

This paper cites Arjovsky, S.

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems Arjovsky, S

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:48.630608Z

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=2026-08-07T05:47:48.413834Z digest=sha256:45fd4e81ffa155c62b946fcf7d8c8abd5cda185a1c51d18c4a558b8e70ccd39a

Observation a18d2de5-355e-44f9-a6d5-1d4f4b2a5c67 · outbound

This paper cites Mertikopoulos, B.

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems Mertikopoulos, B

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:48.545795Z

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=2026-08-07T05:47:48.450969Z digest=sha256:02281ad5b135dce5ac96cc7b7cbbf13ad01ffb70f44a0d849e85df106a208ae6

Observation b74ac8cb-6b30-4979-86b8-d01b10c84598 · outbound

This paper cites Pethick, P.

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems Pethick, P

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:48.524114Z

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=2026-08-07T05:47:48.457875Z digest=sha256:2c5978494caabb8968a76f0ba8b8061ba108d37d429744b58628dcd412ddda01

Observation 106c810d-eefe-4e42-aded-95ff0c461096 · outbound

This paper cites Our analysis builds on the framework developed in Li et al.

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems Our analysis builds on the framework developed in Li et al

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:48.513283Z

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=2026-08-07T05:47:48.461194Z digest=sha256:c4219f027247cea91dcff276a00dbcc1d48fc5340e5355fdbc17d8ccc4cee4c9

Observation 5c18e3b5-f4b4-4934-8083-b9e28a69986e · outbound

This paper cites Cai and W.

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems Cai and W

Reference 2007

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:48.620468Z

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=2026-08-07T05:47:48.422295Z digest=sha256:4c1501aec09bf6eafa566afb6cbaeefbb7c8bbdc764fe06d90d0dfc503e85375

Observation f10d63d4-ae13-4530-9468-73ec43c8265e · outbound

This paper cites Distributionally Robust Optimization and Robust Statistics.

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems Distributionally Robust Optimization and Robust Statistics

Reference 2011

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:48.418275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:48.418275Z digest=sha256:4ec5a6d77b352510c6b5db1adb30d8b080285a1098c8cc0fce458e78ec7b36fa

Observation 51e34206-7baa-450c-adb1-933512e24fdc · outbound

This paper cites Daskalakis, A.

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems Daskalakis, A

Reference 2018

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:48.582804Z

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=2026-08-07T05:47:48.436833Z digest=sha256:45793532560e938fcffaae1d05355d1be5bf2d98db98f81f2488c943c65f1204

Observation d44b1f98-d78a-4617-a327-42d4755c686d · outbound

This paper cites Omidshafiei, J.

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems Omidshafiei, J

Reference 2019

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:48.534319Z

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=2026-08-07T05:47:48.454319Z digest=sha256:64775d496e49678fd3bd95953cf57b22ca5e6a5076622f08a173aef9dedb8f07

Observation ecef488f-d6e8-4ff9-901e-9e5db05503c3 · outbound

This paper cites an unresolved cited work.

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems Unresolved cited work

Reference 2020

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:48.571001Z

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=2026-08-07T05:47:48.440522Z digest=sha256:143f5bbf25675e09da6c038c11e08d245ad24143b32747748e953f4a302855e9

Observation be2178d8-adf2-49b6-851f-1c9dac2ba3b8 · outbound

This paper cites an unresolved cited work.

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems Unresolved cited work

Reference 2021

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:48.591967Z

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=2026-08-07T05:47:48.433294Z digest=sha256:1ad01d77497fb1b33688b778810b91a7c3688739da5e9af5af338d55b83b191b

Observation 14dc68f0-aa57-4b1b-9146-227decf26f12 · outbound

This paper cites an unresolved cited work.

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems Unresolved cited work

Reference 2022

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:48.611183Z

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=2026-08-07T05:47:48.425784Z digest=sha256:1e53392d11982b74dfe519a2e2dcb7b548cd81d5370222fe2127f55ac35301fa

Observation f5cc70dc-0d36-4145-8f53-32d7a6ce41a8 · outbound

This paper cites an unresolved cited work.

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems Unresolved cited work

Reference 2023

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:48.557441Z

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=2026-08-07T05:47:48.447633Z digest=sha256:e3914f8ad2daad576e26aff99eb7fc54524a7992cb4a7a51f3a78a30abc326c7

Observation 88e99d37-a87e-43fc-8239-d8f1928de6cd · outbound

This paper cites an unresolved cited work.

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems Unresolved cited work

Reference 2024

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:48.601569Z

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=2026-08-07T05:47:48.429689Z digest=sha256:1fe4a5a085405d841b5fe3c5e53fe04237e0fb0b85363901be4a9a2a6d4f204e

Observation b5c63562-f318-4e1e-afc2-981cd77cfa44 · outbound

This paper cites A simple uniformly optimal method without line search for convex optimization.

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems A simple uniformly optimal method without line search for convex optimization

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:48.443882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:48.443882Z digest=sha256:93cfd9379daa8624c3fb366d3b8a119f953a9ba692142cb8eaf105578a291de6

Pith citing papers

Observation 39da8e40-05a9-4de9-8440-72ba9e30b388 · inbound

A first-order method for nonconvex-nonconcave minimax problems under a local Kurdyka-Lojasiewicz condition cites this paper.

A first-order method for nonconvex-nonconcave minimax problems under a local Kurdyka-Lojasiewicz condition Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-21T23:35:45.703541Z

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=2026-05-21T23:35:03.424607Z digest=sha256:3364b129567fbd0ec2d361ca8ede89efcf57ff10c1f85fea50f7850b1d3410de

Observation 3c025f5c-85b7-4b98-bfd3-9427ed298f5b · inbound

A first-order method for constrained nonconvex-nonconcave minimax optimization cites this paper.

A first-order method for constrained nonconvex-nonconcave minimax optimization Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-04T13:26:10.160510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:26:10.160510Z digest=sha256:eef7f26dee6400df938809d0d45e32db422efb4c1f74a8c6a914e1e7b2c3bbe5