Paper Citation Record · LEDGER

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training

As of 18 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2412.01958.

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

pith.paper-citation-record.v1
2412.01958 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:06:11.422051Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

21 of 21 outbound references displayed

verified exact1
verified fuzzy9
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cd3e11f9-d282-49b8-8ae8-56720786035b · outbound

This paper cites Towards improving robustness of deep neural networks to adversarial perturbations.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Towards improving robustness of deep neural networks to adversarial perturbations

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T00:06:11.325245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 585a7f8e-2db5-4975-9485-c80913e07038 · outbound

This paper cites MixMatch: A Holistic Approach to Semi-Supervised Learning.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training MixMatch: A Holistic Approach to Semi-Supervised Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T00:06:11.329999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33cb80c4-305d-4357-aaf3-46ee7f9e74b1 · outbound

This paper cites Machine learning robustness: A primer, 2024.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Machine learning robustness: A primer, 2024

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:06:11.732664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b4922a18-2ae6-4676-8c23-abbb27cccaca · outbound

This paper cites Use of Metamorphic Relations as Knowledge Carriers to Train Deep Neural Networks.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Use of Metamorphic Relations as Knowledge Carriers to Train Deep Neural Networks

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-12T00:06:11.538058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c068605d-6af6-4d0b-abc6-df13e7846740 · outbound

This paper cites Boosting semi-supervised learning by exploiting all unlabeled data, 2023.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Boosting semi-supervised learning by exploiting all unlabeled data, 2023

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:06:11.716142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation af73afe4-bedf-499b-a638-a5a57f0302c0 · outbound

This paper cites Certified Adversarial Robustness via Randomized Smoothing.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Certified Adversarial Robustness via Randomized Smoothing

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T00:06:11.350311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cff76247-0036-4f65-99cf-1ea3dcafbead · outbound

This paper cites The mnist database of handwritten digit images for machine learning research.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training The mnist database of handwritten digit images for machine learning research

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T00:06:11.356156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26f58e9b-8a3b-4932-866d-476ca8abbf9f · outbound

This paper cites Onnx runtime.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Onnx runtime

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:06:11.691628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5fa721dd-83c2-43d1-845a-53104124c05a · outbound

This paper cites On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T00:06:11.365873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57793fd4-c942-4815-b814-3f0c4e14fcda · outbound

This paper cites Robust semi-supervised learning when not all classes have labels.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Robust semi-supervised learning when not all classes have labels

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:06:11.676313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c9e9fb03-3701-46f5-9208-e510095f758f · outbound

This paper cites Deep residual learning for image recognition, 2015.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Deep residual learning for image recognition, 2015

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T00:06:11.376148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d371edf-9301-4a4c-9a43-cc11f850a93d · outbound

This paper cites Learning multiple layers of features from tiny images.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Learning multiple layers of features from tiny images

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T00:06:11.380683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af9674d9-4992-4dea-9157-1506707807c5 · outbound

This paper cites Fully convolutional networks for semantic segmentation.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Fully convolutional networks for semantic segmentation

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:06:11.642028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3cee81ac-37ee-48ee-b7fb-8d7450a9939b · outbound

This paper cites Towards deep learning models resistant to adversarial attacks, 2019.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Towards deep learning models resistant to adversarial attacks, 2019

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T00:06:11.390044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19806adb-d52b-4bca-b359-8f198e34a03c · outbound

This paper cites Leveraging mutants for automatic prediction of metamorphic relations using machine learning, 08 2019.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Leveraging mutants for automatic prediction of metamorphic relations using machine learning, 08 2019

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:06:11.617472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 807abc9d-4d83-46fc-9de5-c736a857d303 · outbound

This paper cites Optimism in the face of adversity: Un- derstanding and improving deep learning through adversarial robustness.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Optimism in the face of adversity: Un- derstanding and improving deep learning through adversarial robustness

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:06:11.600076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 422a39d1-c68f-4669-8ee3-4c74145be156 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T00:06:11.402566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 170e8383-0ffa-4724-89dd-2233a0ac6b44 · outbound

This paper cites FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T00:06:11.407081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation babfeb0f-5ad4-48b0-9bfd-0ad1fc16469c · outbound

This paper cites Apress, Berkeley, CA, 2020.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Apress, Berkeley, CA, 2020

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:06:11.584774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6664f2bc-ecaa-451d-aced-b2b91082b7ba · outbound

This paper cites FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T00:06:11.416976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e91e5d33-0d97-431a-9111-588e124c53a8 · outbound

This paper cites Zhang, Mark Harman, Lei Ma, and Yang Liu.

Enhancing Deep Learning Model Robustness through Metamorphic Re-Training Zhang, Mark Harman, Lei Ma, and Yang Liu

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:06:11.569856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

No inbound Pith citation observations are available.