Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T05:20:41.324035Z
Paper Citation Record · LEDGER
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations
As of 16 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2506.08240.
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 2026-08-16T06:30:59.297886+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
50 of 50 outbound references displayed
- verified exact2
- verified fuzzy32
- unresolved16
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 97c0a8d3-0d8b-42fc-9907-092f65c0e8ed · outbound
This paper cites Domain generalization by rejecting extreme augmentations.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Domain generalization by rejecting extreme augmentations
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:42.084764Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation deb0e74e-9048-4bba-86ed-cf1538d60a02 · outbound
This paper cites A data- augmentation is worth a thousand samples: Analytical mo- ments and sampling-free training.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations A data- augmentation is worth a thousand samples: Analytical mo- ments and sampling-free training
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:42.065968Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4e0f8ea4-f2f0-4407-8f43-1026604a9adc · outbound
This paper cites Recognition in terra incognita, 2018.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Recognition in terra incognita, 2018
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:42.045387Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f336a42b-fd42-49be-9ac9-ffefb78e9c7a · outbound
This paper cites On tiny episodic memories in continual learning.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations On tiny episodic memories in continual learning
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:42.029650Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 50e2f8fd-cd20-4c51-9a52-700507b44304 · outbound
This paper cites Just pick a sign: Optimizing deep multitask models with gradi- ent sign dropout.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Just pick a sign: Optimizing deep multitask models with gradi- ent sign dropout
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:42.013858Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9f8e494f-04eb-431a-b1e2-4fd4d60c648f · outbound
This paper cites Peer pressure: Model-to-model regularization for single source domain generalization.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Peer pressure: Model-to-model regularization for single source domain generalization
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.998291Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation be654222-563a-47e2-bee9-bc090982539c · outbound
This paper cites AutoAugment: Learning Augmentation Policies from Data.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations AutoAugment: Learning Augmentation Policies from Data
Reference 7
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b5d68009-ab02-43fe-9b13-ab5a32f058c1 · outbound
This paper cites Randaugment: Practical automated data augmentation with a reduced search space.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Randaugment: Practical automated data augmentation with a reduced search space
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.982967Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e591855e-9c0c-41eb-8df4-bb56dbb2b6dc · outbound
This paper cites The mnist database of handwritten digit images for machine learning research.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations The mnist database of handwritten digit images for machine learning research
Reference 9
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9996a419-059c-46c5-826a-db239035d5dc · outbound
This paper cites Craft- ing distribution shifts for validation and training in single source domain generalization, 2024.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Craft- ing distribution shifts for validation and training in single source domain generalization, 2024
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.956063Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9047a7af-a843-45ae-a90f-934dfd1ccb61 · outbound
This paper cites Adversarially adaptive normal- ization for single domain generalization.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Adversarially adaptive normal- ization for single domain generalization
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.940522Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4c6828c1-9c20-4371-ae88-81ebde1b1ec0 · outbound
This paper cites Unbiased met- ric learning: On the utilization of multiple datasets and web images for softening bias.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Unbiased met- ric learning: On the utilization of multiple datasets and web images for softening bias
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.925567Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c9a66a76-8dd4-4a33-8d3a-b223c38f795a · outbound
This paper cites Unsupervised domain adaptation by backpropagation.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Unsupervised domain adaptation by backpropagation
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.910157Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4c44bf4a-8e19-444a-9d33-05ddc02de24f · outbound
This paper cites Domain-adversarial training of neural networks.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Domain-adversarial training of neural networks
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.895096Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 28f039fc-f575-4c5a-840f-8ed168ea6fe1 · outbound
This paper cites How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization
Reference 15
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7f46c11b-096e-4b6d-adb1-64a3483775ef · outbound
This paper cites An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks
Reference 16
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0b15be08-7b9f-460a-9846-54def2da9957 · outbound
This paper cites Goodfellow, Jonathon Shlens, and Christian Szegedy.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Goodfellow, Jonathon Shlens, and Christian Szegedy
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:20:41.170313Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e1e5fd02-b545-4bba-94b1-9e577f0b9556 · outbound
This paper cites Out-of-distribution forgetting: vulnerability of continual learning to intra-class distribution shift.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Out-of-distribution forgetting: vulnerability of continual learning to intra-class distribution shift
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T05:20:41.455781Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6d4533b1-8be2-4628-b9e5-8f0f605f3df9 · outbound
This paper cites Deep residual learning for image recognition.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Deep residual learning for image recognition
Reference 19
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 824285b5-84ea-4804-a20c-f50d7ef77497 · outbound
This paper cites Data augmentation revisited: Rethinking the distribution gap between clean and augmented data, 2019.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Data augmentation revisited: Rethinking the distribution gap between clean and augmented data, 2019
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.860437Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1eb6784b-9335-43dc-a4a5-eb76f67b95fb · outbound
This paper cites Averaging Weights Leads to Wider Optima and Better Generalization.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Averaging Weights Leads to Wider Optima and Better Generalization
Reference 21
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1566ccb9-f25f-4881-ad6a-0a048fdd112c · outbound
This paper cites Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.845875Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 533ae5d9-533b-4d8f-bf72-295ed0917ebd · outbound
This paper cites Similarity of neural network representations revisited.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Similarity of neural network representations revisited
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.831189Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation faa1ff00-8da5-4e22-879c-5746b0e30c61 · outbound
This paper cites Continual learning with weight interpo- lation.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Continual learning with weight interpo- lation
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.817055Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e93f0255-e435-4a5f-afa7-53af09698ffe · outbound
This paper cites Im- agenet classification with deep convolutional neural networks.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Im- agenet classification with deep convolutional neural networks
Reference 25
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 730d0bbd-b4b5-4aed-83cc-0fea449c7f62 · outbound
This paper cites Le Cun, B.
Reference 26
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ffbb0a81-5b7f-498d-ab87-6b1cc5b1ae7d · outbound
This paper cites Deeper, broader and artier domain generaliza- tion.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Deeper, broader and artier domain generaliza- tion
Reference 27
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 002bcd1f-4cb0-47bc-8829-8fab613bb55b · outbound
This paper cites Domain generalization for medical imaging classification with linear-dependency regularization.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Domain generalization for medical imaging classification with linear-dependency regularization
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.766138Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0a1f1916-0729-4ecd-8a28-4c1da5b1d3fc · outbound
This paper cites an unresolved cited work.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Unresolved cited work
Reference 29
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7b5cc1cd-77a5-4635-add8-718ad339fe0f · outbound
This paper cites Gradient episodic memory for continual learning.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Gradient episodic memory for continual learning
Reference 30
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7504551f-b66a-43bd-a665-59b02dd5a7cf · outbound
This paper cites Continual federated learning based on knowledge distillation.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Continual federated learning based on knowledge distillation
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.723170Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 65afe5a5-ea5e-41f1-bed0-b66e88bfffbb · outbound
This paper cites Weighted Ensemble Models Are Strong Continual Learners.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Weighted Ensemble Models Are Strong Continual Learners
Reference 32
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a18a0fdc-081c-4a04-9e3b-e1a21d91fcd1 · outbound
This paper cites an unresolved cited work.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Unresolved cited work
Reference 33
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 74a231bb-ae4f-4787-926e-d883718edfc9 · outbound
This paper cites Learning to learn single domain generalization.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Learning to learn single domain generalization
Reference 34
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1e45781c-9b2d-41c3-a441-aa47016eae8e · outbound
This paper cites Diverse weight averaging for out-of-distribution generaliza- tion.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Diverse weight averaging for out-of-distribution generaliza- tion
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.685041Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c43632c8-b6a3-48e9-9db2-abaebe5f0b91 · outbound
This paper cites Experience replay for continual learning.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Experience replay for continual learning
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.671670Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 06de9898-a994-4f89-adf2-5d56213ac243 · outbound
This paper cites Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay
Reference 37
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T05:20:41.401045Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f6972925-56d8-4c90-9bbf-1b62c17dc8b4 · outbound
This paper cites Continual learning with scaled gradient projection.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Continual learning with scaled gradient projection
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.658470Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3c7330d6-b904-47bb-85ef-a6125d430138 · outbound
This paper cites Deep hashing network for unsupervised domain adaptation.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Deep hashing network for unsupervised domain adaptation
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.645035Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 98e32e49-db39-4bef-a46f-da0f457fc9db · outbound
This paper cites Generalizing to unseen domains via adversarial data augmentation.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Generalizing to unseen domains via adversarial data augmentation
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.631899Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation fbc2b3fe-3928-415f-b2db-73140435e043 · outbound
This paper cites Meta convolutional neural networks for single domain generalization.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Meta convolutional neural networks for single domain generalization
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.617954Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation afa812c6-7158-489b-8e47-3b48f1ecb34b · outbound
This paper cites FOSTER: Feature Boosting and Compression for Class-Incremental Learning.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations FOSTER: Feature Boosting and Compression for Class-Incremental Learning
Reference 42
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 78991926-8a40-4d47-be57-cb2dd70f66b8 · outbound
This paper cites A Comprehensive Survey of Continual Learning: Theory, Method and Application.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations A Comprehensive Survey of Continual Learning: Theory, Method and Application
Reference 43
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 35dd531a-a104-45d1-984a-258f61c9a92c · outbound
This paper cites Learning to diversify for single domain generalization.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Learning to diversify for single domain generalization
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.604295Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 694271ae-2211-4a6e-a5f0-f92810d59192 · outbound
This paper cites Learning structured sparsity in deep neural networks,.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Learning structured sparsity in deep neural networks,
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.589476Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c25f5da0-9d80-458d-b5fa-3bbbd1b69dcf · outbound
This paper cites an unresolved cited work.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Unresolved cited work
Reference 46
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T05:20:41.574210Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 09dba457-4231-401a-90dc-161434c4e582 · outbound
This paper cites Simde: A simple domain expansion approach for single-source domain generalization.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Simde: A simple domain expansion approach for single-source domain generalization
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.560164Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2ff225ab-a0f6-4423-b3fc-5a1ea74323f6 · outbound
This paper cites Gradient surgery for multi- task learning.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Gradient surgery for multi- task learning
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.545336Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3882d9c6-c0e7-428f-96c5-4542027daf67 · outbound
This paper cites Maximum-entropy adversarial data augmentation for im- proved generalization and robustness.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Maximum-entropy adversarial data augmentation for im- proved generalization and robustness
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.530376Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation abb4fdba-2deb-460e-8c67-d2750c32101d · outbound
This paper cites Advst: Revisiting data augmentations for single domain generaliza- tion.
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Advst: Revisiting data augmentations for single domain generaliza- tion
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:20:41.516334Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
No inbound Pith citation observations are available.