Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:38:53.728980Z
Paper Citation Record · LEDGER
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training
As of 12 August 2026, this Paper Citation Record lists 80 of 80 outbound references and 0 inbound Pith citation observations for arXiv:2507.07768.
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 2026-08-12T06:34:41.77262+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
80 of 80 outbound references displayed
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- verified fuzzy51
- unresolved27
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation b2183f06-6e0f-43b1-9661-2a4207104c6a · outbound
This paper cites Deep residual learning for image recognition.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Deep residual learning for image recognition
Reference 1
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation a14c2290-24e2-46b3-9720-574256ec9b8c · outbound
This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training An image is worth 16x16 words: Transformers for image recognition at scale
Reference 2
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation ad6690c1-decc-4d87-a4c3-6333aa89a8f8 · outbound
This paper cites Bert: Pre-training of deep bidi- rectional transformers for language understanding.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Bert: Pre-training of deep bidi- rectional transformers for language understanding
Reference 3
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation c9f47ec2-011d-4cab-8983-b489b14c07a4 · outbound
This paper cites Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, et al.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, et al
Reference 4
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 18b176b0-f721-4b73-ad02-8e7ab30f0852 · outbound
This paper cites Mastering the game of go without human knowledge.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Mastering the game of go without human knowledge
Reference 5
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 34cd1b8f-5e76-4bbb-89b6-18ce9ad237f9 · outbound
This paper cites Intriguing properties of neural networks.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Intriguing properties of neural networks
Reference 6
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 48e40c40-2724-42c8-b5f1-db59ce92977d · outbound
This paper cites Explaining and harnessing adversarial examples.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Explaining and harnessing adversarial examples
Reference 7
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 89356537-1b5f-48b9-8a8b-01f835a419aa · outbound
This paper cites To- wards deep learning models resistant to adversarial attacks.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training To- wards deep learning models resistant to adversarial attacks
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:39:11.579301Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 69e2a7aa-1060-4ef1-a881-9e815530c24a · outbound
This paper cites Adversarial examples in the physical world.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Adversarial examples in the physical world
Reference 9
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 268e0cb2-b50a-4b79-b284-7b6a763dbedd · outbound
This paper cites Towards evaluating the robustness of neural networks.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Towards evaluating the robustness of neural networks
Reference 10
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8a996f5c-42f8-4fce-b3fd-424039bbbbdf · outbound
This paper cites Semsegbench & detecbench: Benchmarking reliability and generalization beyond classification, 2025.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Semsegbench & detecbench: Benchmarking reliability and generalization beyond classification, 2025
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:39:11.192352Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 64b98c0b-8e08-4d2c-bf96-9c92da2f862e · outbound
This paper cites Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples
Reference 12
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 328dd6d3-28fc-42a1-b53b-17533a72662c · outbound
This paper cites Improving adver- sarial robustness requires revisiting misclassified examples.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Improving adver- sarial robustness requires revisiting misclassified examples
Reference 13
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d01dd828-2951-4a2f-83ce-d93f9081a763 · outbound
This paper cites Prior-guided adversarial initialization for fast adversarial training.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Prior-guided adversarial initialization for fast adversarial training
Reference 14
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 42cf0e2b-345b-4319-b13c-caa4eeed8055 · outbound
This paper cites Improving feature stability during upsampling – spectral artifacts and the importance of spatial context.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Improving feature stability during upsampling – spectral artifacts and the importance of spatial context
Reference 15
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f5f0dd2f-68d3-493f-b573-3675135dd1bf · outbound
This paper cites CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasks.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasks
Reference 16
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation a617c41d-af5e-4183-afbc-ac2bcb773fcd · outbound
This paper cites On the unreasonable vulnerability of transformers for image restoration-and an easy fix.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training On the unreasonable vulnerability of transformers for image restoration-and an easy fix
Reference 17
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation d3f99baa-77b6-4ffa-8ae7-770fcd777603 · outbound
This paper cites As large as it gets-studying infinitely large convolutions via neural implicit frequency filters.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training As large as it gets-studying infinitely large convolutions via neural implicit frequency filters
Reference 18
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 6139dcf3-d3a9-4704-a2ec-5b84258b3915 · outbound
This paper cites Frequencylowcut pooling - plug and play against catastrophic overfitting.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Frequencylowcut pooling - plug and play against catastrophic overfitting
Reference 19
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation cb870ec4-2901-46db-b377-8eada42569d0 · outbound
This paper cites Aliasing and adversarial robust generalization of cnns.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Aliasing and adversarial robust generalization of cnns
Reference 20
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 1f2e7817-bb87-4691-aece-906c74fa368e · outbound
This paper cites Robust models are less over-confident.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Robust models are less over-confident
Reference 21
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 34d855a3-38e1-46c2-98b4-bbefd5db22be · outbound
This paper cites Neural architecture design and robustness: A dataset.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Neural architecture design and robustness: A dataset
Reference 22
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 62b63305-7256-48dd-9296-7a36bab0913f · outbound
This paper cites Improving native cnn robustness with filter frequency regularization.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Improving native cnn robustness with filter frequency regularization
Reference 23
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation fdded5ea-0772-499f-8708-9e5895ed7f09 · outbound
This paper cites Theoretically principled trade-off between robustness and accuracy.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Theoretically principled trade-off between robustness and accuracy
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:39:05.854791Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation bcc96fee-0ffe-461f-b63c-594b81296f99 · outbound
This paper cites Robust fairness: A robust optimization framework for fair classification.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Robust fairness: A robust optimization framework for fair classification
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:39:05.342288Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 3b54b604-5dda-4c2d-bcc1-19712943f0e7 · outbound
This paper cites Dafa: Differentiated adversarial training for fairness and accuracy.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Dafa: Differentiated adversarial training for fairness and accuracy
Reference 27
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- verified fuzzy
- raw_fallback, observed 2026-08-06T18:39:05.105175Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 32017829-46bd-4c3e-9f9a-e2d6778c15e1 · outbound
This paper cites Towards class-wise robustness analysis, 2024.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Towards class-wise robustness analysis, 2024
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:39:04.828565Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation abdcbcf3-529c-4ba9-a162-cc9d4386e2c0 · outbound
This paper cites Fair-tat: Improving model fairness using targeted adversarial training.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Fair-tat: Improving model fairness using targeted adversarial training
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:39:04.495629Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 825eaf2c-8258-4b57-9608-854ef0a17456 · outbound
This paper cites Cfa: Class-wise calibrated fair adversarial training.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Cfa: Class-wise calibrated fair adversarial training
Reference 30
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- raw_fallback, observed 2026-08-06T18:39:04.297767Z
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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 01453110-2299-4752-a40c-b80628dfed74 · outbound
This paper cites Gupta and L.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Gupta and L
Reference 31
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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 2751062f-0301-48e7-8eb9-1fb7d5fafd07 · outbound
This paper cites Wat: improve the worst-class robustness in adversarial training.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Wat: improve the worst-class robustness in adversarial training
Reference 32
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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 30fbffce-5380-4241-998c-ce574a74357b · outbound
This paper cites Liu and H.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Liu and H
Reference 33
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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation cb5b0491-a39f-4ba3-91b8-c1f7a6f32c83 · outbound
This paper cites Understanding ad- versarial attacks on deep learning based medical image analysis systems.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Understanding ad- versarial attacks on deep learning based medical image analysis systems
Reference 34
- Resolution
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- raw_fallback, observed 2026-08-06T18:39:03.397834Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 94e59ca3-7170-4e2f-9490-a209fb40a449 · outbound
This paper cites Dafa: Distance- aware fair adversarial training.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Dafa: Distance- aware fair adversarial training
Reference 35
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b25ce0ce-1d5c-4ca8-9023-2dcd0097bfd2 · outbound
This paper cites On the tradeoff between robustness and fairness.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training On the tradeoff between robustness and fairness
Reference 36
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 428cab5c-2c53-4646-9365-8757675efe91 · outbound
This paper cites Improving Adversarial Robust Fairness via Anti-Bias Soft Label Distillation.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Improving Adversarial Robust Fairness via Anti-Bias Soft Label Distillation
Reference 37
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 42018d8d-b1fc-40eb-9255-d8da56b3b0b3 · outbound
This paper cites Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data
Reference 38
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- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation a18b6459-6dcd-4f9c-8eaa-53a9f3a4b4a6 · outbound
This paper cites Jordan, and Jacob Steinhardt.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Jordan, and Jacob Steinhardt
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:39:02.774338Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation fbf0c615-7628-4ea0-aeb1-742e1d2f9c1b · outbound
This paper cites Kumar and R.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Kumar and R
Reference 40
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 98d6692c-13ab-4d31-8ca9-5491bdc9f499 · outbound
This paper cites Understanding the impact of adversarial robustness on accuracy disparity.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Understanding the impact of adversarial robustness on accuracy disparity
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:39:02.292006Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 54597c53-5b80-49d8-babe-619cdbef920c · outbound
This paper cites Analysis and applications of class-wise robustness in adversarial training.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Analysis and applications of class-wise robustness in adversarial training
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:39:05.607962Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 6b62b5ec-ea06-47d5-ba92-56a2ceaead6a · outbound
This paper cites Robustness may be at odds with fairness: An empirical study on class-wise accuracy.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Robustness may be at odds with fairness: An empirical study on class-wise accuracy
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:39:02.002311Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 8c989829-1be5-4c84-a176-5b3efc03668e · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 44
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 6040edd1-b198-44bf-a843-dd141cd096b2 · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 45
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 9a68a927-66eb-4044-9186-260036f0d930 · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 46
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:39:01.209282Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 5c12745f-5570-4f65-ad5e-e2e5987f1894 · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 47
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:39:00.943164Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b717b3aa-9206-4e26-a08f-d97c683d86fa · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 48
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:39:00.633653Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 2ce154cd-f8d3-446d-a05b-10f9d19f127f · outbound
This paper cites Zhao and Q.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Zhao and Q
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:39:00.269259Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 974614ce-7efb-4ccf-89ea-e5388a94d291 · outbound
This paper cites Cifar-10 (canadian institute for advanced research).
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Cifar-10 (canadian institute for advanced research)
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:39:00.009745Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 2acafd93-c852-4fbb-ab88-9bf68e804a47 · outbound
This paper cites An analysis of single-layer networks in unsupervised feature learning.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training An analysis of single-layer networks in unsupervised feature learning
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:59.695344Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 1bc37b4f-4aca-45f8-a628-4ff0ffca347c · outbound
This paper cites Deep residual learning for image recognition.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Deep residual learning for image recognition
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:59.459049Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 8ca625c9-c95b-4666-9964-0da4fb638d10 · outbound
This paper cites Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:59.174825Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 2acae307-5ee9-490d-86df-32f133dd05b9 · outbound
This paper cites Learning multiple layers of features from tiny images.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Learning multiple layers of features from tiny images
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:58.944621Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 74f71a40-c8a2-4580-9c2a-c56c5a29b785 · outbound
This paper cites Deep residual learning for image recognition, 2015.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Deep residual learning for image recognition, 2015
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:38:51.223164Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ca6b1b53-566f-41dc-8902-47221435c835 · outbound
This paper cites Identity mappings in deep residual networks.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Identity mappings in deep residual networks
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:38:51.353969Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 58c103b9-4557-434c-99be-0648d8849b7b · outbound
This paper cites Wide Residual Networks.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Wide Residual Networks
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:38:51.493483Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b326418-e3f5-4ad7-a296-da4c9752134d · outbound
This paper cites Is robustbench/autoattack a suitable benchmark for adversarial robustness? In The AAAI-22 Workshop on Adversarial Machine Learning and Beyond, 2022.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Is robustbench/autoattack a suitable benchmark for adversarial robustness? In The AAAI-22 Workshop on Adversarial Machine Learning and Beyond, 2022
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:58.726385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 173188cc-adaa-4a30-a6f1-174127f61d9f · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 59
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:38:58.425945Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 63069c7e-33e7-4889-8add-ec0a59036317 · outbound
This paper cites Adversarial machine learning at scale, 2017.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Adversarial machine learning at scale, 2017
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:58.180180Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 81fbbebd-b141-4b6a-ba23-346243e6c38a · outbound
This paper cites Le and X.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Le and X
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:57.973215Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation e56c583f-657a-43fa-bba4-13b3c40c8c38 · outbound
This paper cites Autoaugment: Learning augmentation strategies from data.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Autoaugment: Learning augmentation strategies from data
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:57.733971Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 7b03de3a-41e6-4e32-b80f-28ce9819f0d7 · outbound
This paper cites Improved Regularization of Convolutional Neural Networks with Cutout.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Improved Regularization of Convolutional Neural Networks with Cutout
Reference 63
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:38:52.040506Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ea96a403-21d7-4634-8774-6123f6f5fc78 · outbound
This paper cites mixup: Beyond empirical risk minimization.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training mixup: Beyond empirical risk minimization
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:57.451192Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 0d6128fc-d795-4ad0-94db-cec77d25130d · outbound
This paper cites Schomaker, and Marco A.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Schomaker, and Marco A
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:57.271661Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 0abe340e-3791-4d28-aed8-491f3fcf8c2e · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 66
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:38:57.119986Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 99ec96c6-bd23-4d6a-9a56-131e8250f6f0 · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 67
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:38:56.897648Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f6f244a7-d63b-449b-a8dd-d09e2b069609 · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 68
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:38:56.644897Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 9ebde3f7-b3e5-4389-85a9-4581cafdb073 · outbound
This paper cites 6 and Appendix A.2.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training 6 and Appendix A.2
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:56.467620Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation af40e15d-b030-40b1-8462-c48a1b79ea00 · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 70
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:38:56.331038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 8fdd3cb6-2ab0-4af8-8809-e22c3b8259f5 · outbound
This paper cites 6 and Appendix A.2.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training 6 and Appendix A.2
Reference 71
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:56.108047Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation bf4a6a32-fada-46cf-b202-4fdbf32bd3e0 · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 72
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:38:55.900593Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation fb016076-131a-4706-926b-e365b85ec69b · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 73
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:38:55.748568Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 2a1d9cbe-13cb-4d5a-9d50-b1e3c4e14b3c · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 74
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:38:55.624261Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 538a02ea-9f17-4176-8cf9-55a1a7ce7dd7 · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 75
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:38:55.499809Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 21c66cc2-009d-497c-a46b-a7e722d843a5 · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 76
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:38:55.304986Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f7b5d531-0744-4e4c-88dc-3742f64d33cc · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 77
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:38:55.096589Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 9996fbc2-7d79-4c72-92d7-4d7d94637484 · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 78
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:38:54.790514Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 3ebb7c5e-3690-4fc7-8c76-1919faa7b21b · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 79
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:38:54.597018Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f0798e07-d987-4a62-a96b-50ebb4338a97 · outbound
This paper cites an unresolved cited work.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Unresolved cited work
Reference 80
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:38:54.412472Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 925bd148-7bda-4f24-b907-0abb0e434b58 · outbound
This paper cites Answer: [No] 22.
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training Answer: [No] 22
Reference 81
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:54.253397Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Pith citing papers
No inbound Pith citation observations are available.