Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T20:52:17.128139Z
Paper Citation Record · LEDGER
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition
As of 19 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2509.08300.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
21 of 21 outbound references displayed
- verified exact2
- verified fuzzy12
- unresolved7
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 9bd5d6a9-a39a-4747-8c97-569b50883dff · outbound
This paper cites Data-driven deep learning for automatic modulation recognition in cognitive radios,.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Data-driven deep learning for automatic modulation recognition in cognitive radios,
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T20:52:17.027540Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1d401c1c-79a4-48ef-b6b9-3233ec148679 · outbound
This paper cites Adversarial attacks in modulation recognition with convolutional neural networks,.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Adversarial attacks in modulation recognition with convolutional neural networks,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T20:52:17.513165Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 24cb4a40-8787-47fc-8b70-8e9e07644ac0 · outbound
This paper cites Radio machine learning dataset generation with gnu radio,.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Radio machine learning dataset generation with gnu radio,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T20:52:17.496410Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2c277366-917e-4595-a7ab-85916e7b7784 · outbound
This paper cites Over-the-air deep learning based radio signal classification,.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Over-the-air deep learning based radio signal classification,
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-08-04T20:52:17.312361Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 230d8e84-3f5d-4718-9c59-18166bf579de · outbound
This paper cites Signet: A novel deep learning framework for radio signal classification,.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Signet: A novel deep learning framework for radio signal classification,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T20:52:17.479564Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d062bcce-fa73-41d5-afd4-4aaf95e972dc · outbound
This paper cites Active Learning for Convolutional Neural Networks: A Core-Set Approach.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Active Learning for Convolutional Neural Networks: A Core-Set Approach
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T20:52:17.054259Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8d130aeb-efe9-4e5a-92a8-0d243f006f56 · outbound
This paper cites Active Learning by Acquiring Contrastive Examples.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Active Learning by Acquiring Contrastive Examples
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T20:52:17.060118Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e44a7ccc-6cda-4365-8430-0ea617bd0324 · outbound
This paper cites Deep learning on a data diet: Finding important examples early in training,.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Deep learning on a data diet: Finding important examples early in training,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T20:52:17.463031Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation b8b60e54-06ed-4144-8a94-1255c97f0775 · outbound
This paper cites An Empirical Study of Example Forgetting during Deep Neural Network Learning.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition An Empirical Study of Example Forgetting during Deep Neural Network Learning
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T20:52:17.069935Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00c380c8-fdcc-473e-ac3e-e3aea9be556f · outbound
This paper cites Moderate coreset: A universal method of data selection for real-world data-efficient deep learning,.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Moderate coreset: A universal method of data selection for real-world data-efficient deep learning,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T20:52:17.446748Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 05344427-234e-4ccd-bf77-86282b8aff22 · outbound
This paper cites Dataset Distillation Meets Provable Subset Selection.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Dataset Distillation Meets Provable Subset Selection
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T20:52:17.080176Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4de10110-13f2-4611-8ad9-686e2bc499f8 · outbound
This paper cites Online Coreset Selection for Rehearsal-based Continual Learning.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Online Coreset Selection for Rehearsal-based Continual Learning
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T20:52:17.085382Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation be8261b8-699d-410f-a00c-c3edfb26205a · outbound
This paper cites Non-uniform class-wise coreset selection: Characterizing category difficulty for data- efficient transfer learning,.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Non-uniform class-wise coreset selection: Characterizing category difficulty for data- efficient transfer learning,
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-08-04T20:52:17.196490Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 114295a2-be03-49c9-bfe8-21e8459043ea · outbound
This paper cites Deepcore: A comprehensive library for coreset selection in deep learning,.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Deepcore: A comprehensive library for coreset selection in deep learning,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T20:52:17.431644Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 60e0bc50-68ed-482d-ab4d-7aa343b6cdd3 · outbound
This paper cites Rk-core: An established methodology for exploring the hierarchical structure within datasets,.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Rk-core: An established methodology for exploring the hierarchical structure within datasets,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T20:52:17.416172Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e79eaa26-2d31-4153-a109-de2edacc3116 · outbound
This paper cites Coreset selection for object detection,.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Coreset selection for object detection,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T20:52:17.398103Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 469f679b-d532-4ac4-b483-0e86661eeaf6 · outbound
This paper cites Fedcs: Coreset selection for federated learning,.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Fedcs: Coreset selection for federated learning,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T20:52:17.381174Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ad78632a-aaec-45a8-b7f2-7ec65178b25a · outbound
This paper cites Contextual diversity for active learning,.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Contextual diversity for active learning,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T20:52:17.364188Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 6d7a690e-cc96-465f-a080-0a76ed20590f · outbound
This paper cites Herding dynamical weights to learn,.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Herding dynamical weights to learn,
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T20:52:17.345775Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d45470b6-49f9-471e-bb24-8cff51dcf920 · outbound
This paper cites Selection via Proxy: Efficient Data Selection for Deep Learning.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Selection via Proxy: Efficient Data Selection for Deep Learning
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T20:52:17.122937Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2c424574-a559-4913-a54c-db887161ce23 · outbound
This paper cites Iqformer: A novel transformer-based model with multi-modality fusion for automatic mod- ulation recognition,.
\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition Iqformer: A novel transformer-based model with multi-modality fusion for automatic mod- ulation recognition,
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-04T20:52:17.329039Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Pith citing papers
No inbound Pith citation observations are available.