Paper Citation Record · LEDGER

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning

As of 22 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2504.18348.

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

pith.paper-citation-record.v1
2504.18348 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:22:26.414470Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

verified exact1
verified fuzzy22
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ed6bd029-3c05-479d-b2b0-10d77d0e95e0 · outbound

This paper cites Automatic steganographic distortion learning using a generative adversarial network.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Automatic steganographic distortion learning using a generative adversarial network

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.733032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 59f5d4dd-3424-48de-abb9-fb9740a46cb3 · outbound

This paper cites Acgis: Adversarial cover generator for image steganography with noise residuals features-preserving.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Acgis: Adversarial cover generator for image steganography with noise residuals features-preserving

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.721690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cadf8bb3-3da3-4de6-b774-cc5658bcd3c1 · outbound

This paper cites Hinet: Deep image hiding by invertible network.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Hinet: Deep image hiding by invertible network

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.710642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 54392960-d8bc-430a-b2ff-d261e57e52b5 · outbound

This paper cites Robust invertible image steganography.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Robust invertible image steganography

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.699997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 86f8c1bf-273e-41f5-abd3-fe1e77b6e041 · outbound

This paper cites Generative adversarial networks for image steganogra- phy.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Generative adversarial networks for image steganogra- phy

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.689511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6e77927a-e1fd-4dae-a317-db37ae80d765 · outbound

This paper cites An improved steganography without embedding based on attention gan.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning An improved steganography without embedding based on attention gan

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.678981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 78596e40-846c-462f-a540-ea4849c9b32e · outbound

This paper cites Gan-based spatial image steganography with cross feedback mechanism.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Gan-based spatial image steganography with cross feedback mechanism

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.669013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5b190db3-b965-423a-b4e9-6ad864c3e3cc · outbound

This paper cites Gan-based image steganography for enhancing security via adversarial attack and pixel-wise deep fusion.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Gan-based image steganography for enhancing security via adversarial attack and pixel-wise deep fusion

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.657381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d72118ff-628e-4c6a-b4fb-ee56939ceb1d · outbound

This paper cites Stegastylegan: towards generic and practical generative image steganography.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Stegastylegan: towards generic and practical generative image steganography

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.645008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 67c82c42-7953-47e2-bfd2-6cc4f2f9da66 · outbound

This paper cites Generating steganographic images via adversarial training.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Generating steganographic images via adversarial training

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.634723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 86ae5b31-42d3-4733-bc2b-560c43a82d18 · outbound

This paper cites SteganoGAN: High Capacity Image Steganography with GANs.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning SteganoGAN: High Capacity Image Steganography with GANs

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T10:22:26.359735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65bf1740-dab9-4eb2-8318-66649249ac2f · outbound

This paper cites Image steganography with deep orthogonal fusion of multi-scale channel attention.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Image steganography with deep orthogonal fusion of multi-scale channel attention

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.623316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0427caf1-35b9-4a33-bd7f-9518a79a2928 · outbound

This paper cites High invisibility image steganography with wavelet transform and generative adversarial network.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning High invisibility image steganography with wavelet transform and generative adversarial network

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.612102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ced738a7-21ab-4e96-bb79-aad57caec682 · outbound

This paper cites Image hide with invertible network and swin transformer.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Image hide with invertible network and swin transformer

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.601205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d3eb1ed6-dd3d-41e6-860e-f1c5fdf46c1f · outbound

This paper cites iscmis: Spatial-channel attention based deep invertible network for multi-image steganography.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning iscmis: Spatial-channel attention based deep invertible network for multi-image steganography

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.591115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e828d07f-6057-4de1-ac62-5be7a781f5b4 · outbound

This paper cites Invisible steganography via generative adversarial networks.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Invisible steganography via generative adversarial networks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.581102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a02d8d59-bb94-4dde-9324-9a5bee3b62ea · outbound

This paper cites Analysis of deep steganography robustness using various loss functions.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Analysis of deep steganography robustness using various loss functions

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.569769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 95593f53-429e-4995-a0b8-48c227edae6b · outbound

This paper cites Multi-task learning using uncertainty to weigh losses for scene geometry and semantics.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Multi-task learning using uncertainty to weigh losses for scene geometry and semantics

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T10:22:26.383484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47dc0533-fe9b-4003-81c8-d3a3a77f17b6 · outbound

This paper cites Dynamic task prioritization for multitask learning.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Dynamic task prioritization for multitask learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.552514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6082b48a-a3a7-47cd-af4f-402d99788736 · outbound

This paper cites Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.540139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f8489540-0d23-4617-b142-13120194fd00 · outbound

This paper cites End-to-end multi-task learning with attention.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning End-to-end multi-task learning with attention

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T10:22:26.393205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e70d75b8-86c7-4019-87df-4ce3a73a004c · outbound

This paper cites Debiased contrastive curriculum learning for progressive generalizable person re-identification.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Debiased contrastive curriculum learning for progressive generalizable person re-identification

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.522224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a5bc87da-39ce-4d33-9acf-b4a19b845bf6 · outbound

This paper cites Curriculum learning for goal-oriented semantic communications with a common language.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Curriculum learning for goal-oriented semantic communications with a common language

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.509551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6d0eac3d-60d3-4f0b-89b6-94838bdcd260 · outbound

This paper cites Recrecnet: Rectangling rectified wide- angle images by thin-plate spline model and dof-based curriculum learning.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Recrecnet: Rectangling rectified wide- angle images by thin-plate spline model and dof-based curriculum learning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.497452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 25891af1-7a16-487b-9643-5c9cc7195a73 · outbound

This paper cites Curriculum learning of multiple tasks.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Curriculum learning of multiple tasks

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:22:26.485774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7bf47ad3-ae93-4227-a707-6965cba3f4fb · outbound

This paper cites Curriculum Pre-training for End-to-End Speech Translation.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Curriculum Pre-training for End-to-End Speech Translation

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-16T10:22:26.462486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation eda8eef3-8edc-4588-b0fa-17ea217116d2 · outbound

This paper cites Progressive Growing of GANs for Improved Quality, Stability, and Variation.

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning Progressive Growing of GANs for Improved Quality, Stability, and Variation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T10:22:26.414470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.