Pith. sign in

Paper Citation Record · LEDGER

Noise-Tolerant Coreset-Based Class Incremental Continual Learning

As of 20 August 2026, this Paper Citation Record lists 67 of 67 outbound references and 0 inbound Pith citation observations for arXiv:2504.16763.

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

pith.paper-citation-record.v1
2504.16763 v1

Coverage vector

measured 67 of 67 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:02:20.773473Z

measured 67 of 67 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

67 of 67 outbound references displayed

  • verified exact1
  • verified fuzzy46
  • unresolved19
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 60188c08-ae2f-470d-a5b6-d8246dcd332c · outbound

This paper cites Brainwash: A poisoning attack to forget in continual learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Brainwash: A poisoning attack to forget in continual learning

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:22.157553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.444639Z digest=sha256:bdd1f6d520a3d6d2e925c939ebd0402807bbf16ad05b0e89083eb90b2a8882e5

Observation 2b18ea2f-92b5-44ef-9957-d29ddea406d7 · outbound

This paper cites Memory aware synapses: Learning what (not) to forget.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Memory aware synapses: Learning what (not) to forget

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:22.139874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.450665Z digest=sha256:793352e8a89a9f3d899967a27d69c8f1a533df4e1532e41c3deba120d4e35a78

Observation 37fb1e63-19f6-4dcc-9d15-f0700daebd4b · outbound

This paper cites Gradient based sample selection for online continual learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Gradient based sample selection for online continual learning

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:22.123191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.455802Z digest=sha256:365c2265c40cf08a54fd7c4d03d8273c8ca65b4b38a94e4057b5f8e6461642fc

Observation fbf86410-a93e-488d-9c79-e48cdd5be2e3 · outbound

This paper cites Tackling Online One-Class Incremental Learning by Removing Negative Contrasts.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Tackling Online One-Class Incremental Learning by Removing Negative Contrasts

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-16T11:02:21.052576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.461309Z digest=sha256:51035fe81baf3373f9b6c55ee4729bb9be3872f0017e1a5876ef97ef448e3183

Observation b9ee697b-fcac-44d6-88b6-a8db5e9018c5 · outbound

This paper cites Towards adversarially robust continual learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Towards adversarially robust continual learning

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:22.107268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.467139Z digest=sha256:63a72f44676c54be4356667523d653b96d8cd7d80ed42d8f887c52e306d3b99c

Observation 3df64fcf-29ae-46c9-866a-36434ef68919 · outbound

This paper cites Coresets via bilevel optimization for continual learning and stream- ing.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Coresets via bilevel optimization for continual learning and stream- ing

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:22.091021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.471912Z digest=sha256:f5710c720c6f075ac9e9927833ba8f9ef8d6d682d5ddb5c47638b752f64afa93

Observation 38fd26d6-3c33-4c15-8477-b97d9c493639 · outbound

This paper cites Dark experience for gen- eral continual learning: a strong, simple baseline.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Dark experience for gen- eral continual learning: a strong, simple baseline

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.477437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.477437Z digest=sha256:16d6d93a3c61b188100b8c12fe0ade583b55deb0414a045530317e9b189eb7d3

Observation fad55a2f-6cec-4597-bcf2-e66a44203a30 · outbound

This paper cites Avalanche: A pytorch li- brary for deep continual learning.Journal of Machine Learn- ing Research, 24(363):1–6, 2023.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Avalanche: A pytorch li- brary for deep continual learning.Journal of Machine Learn- ing Research, 24(363):1–6, 2023

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.943385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.482147Z digest=sha256:a45776af11b123f24cb4c68d282fed1389c1c8be4e4a3bebb76fe3f2fa9282b5

Observation 9e247fa2-62ed-42b2-8b77-575ce96699ed · outbound

This paper cites Lifelong machine learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Lifelong machine learning

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.928173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.486717Z digest=sha256:e759137f2707a3a71cf42abc2b71104cb94dcd4ffba810f639c01e27e6a4737c

Observation c3f96422-3cc2-49d1-8a01-28486be88570 · outbound

This paper cites Lifelong machine learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Lifelong machine learning

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.912033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.491996Z digest=sha256:eeaabd1eafb0cba6394108c792f29c7db9e9b873cd327d96a7d2ab919365f145

Observation 5fada0c3-bcda-442a-bc12-2f1fe28ed7a4 · outbound

This paper cites A continual learning survey: Defying for- getting in classification tasks.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning A continual learning survey: Defying for- getting in classification tasks

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.896102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.496654Z digest=sha256:6a4766ffaa0753faa38e873a0f1fedcc3275c85570497283d50672bee83f90bf

Observation f9c3fc97-8a71-4199-b5a4-0ff0f6efd7d2 · outbound

This paper cites Don't forget, there is more than forgetting: new metrics for Continual Learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Don't forget, there is more than forgetting: new metrics for Continual Learning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.501730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.501730Z digest=sha256:59ab7c9e0f0c6bca4248b31cf5c2743024aaeb01418455a6ad8851cdc8fa1779

Observation 90cfb170-a6e2-4600-8a04-f21968200285 · outbound

This paper cites Progressive learning: A deep learning framework for contin- ual learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Progressive learning: A deep learning framework for contin- ual learning

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.880723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.507145Z digest=sha256:91e707865f487e7ab9e7f1044b9cf2d3b21e048ec656a7e2c71e00cd92fbb5d9

Observation c648ce56-755f-46a2-9f1d-5765f1ffc0e3 · outbound

This paper cites Persistent Backdoor Attacks in Continual Learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Persistent Backdoor Attacks in Continual Learning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.511853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.511853Z digest=sha256:a322c238cf2f274f9fa4a1efb9a2618e778b55c3f596a7e39cfa783d04630da3

Observation 8d921feb-ddba-4626-91a2-822655559e01 · outbound

This paper cites Remind your neural net- work to prevent catastrophic forgetting.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Remind your neural net- work to prevent catastrophic forgetting

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.864675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.517016Z digest=sha256:3befb6674c2fe673c08fe502a884a076b2197588a39d6f57a3475cbc1c3976db

Observation bfb00937-c7fb-4151-bafa-e45e4af699ef · outbound

This paper cites Deep residual learning for image recognition.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Deep residual learning for image recognition

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.847317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.521519Z digest=sha256:e7eff2417218f12ae6d2566a2387899d162f29611b67c45ea8009c879c19ee4e

Observation 2ba5c7e9-587c-46dc-9588-ddedec3ecbee · outbound

This paper cites Compacting, picking and growing for unforgetting continual learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Compacting, picking and growing for unforgetting continual learning

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.830253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.525796Z digest=sha256:e1de95668ff32d73c92660e652f05d3028310c884c663886bcbcb4dd9d90db86

Observation 77d1eae4-356c-408e-baeb-1c4ee283f8c9 · outbound

This paper cites Selective experience re- play for lifelong learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Selective experience re- play for lifelong learning

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.811393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.530471Z digest=sha256:a47d9a378992ecdec8b95bf0e5a0c60d5235c4de539e8c76d2272f1bb048b3d5

Observation 6d913b60-8ec4-4c45-b96c-bce2d438f70c · outbound

This paper cites Robustness-preserving lifelong learning via dataset condensation.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Robustness-preserving lifelong learning via dataset condensation

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.794243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.534995Z digest=sha256:caa6f82018cbd0f96cd32c5ffc349240fdd747b215e6a1110535901df138d0ab

Observation 64d01015-8edb-4e97-9348-d48326b1cd42 · outbound

This paper cites Continual poi- soning of generative models to promote catastrophic forget- ting.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Continual poi- soning of generative models to promote catastrophic forget- ting

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.777560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.539699Z digest=sha256:35acb85f5da355350dcb2f417e584b02672078bfe633fc5a6bf92ce72da8bae5

Observation 024939eb-a6c9-4c71-9120-c39808d7d5bd · outbound

This paper cites Poisoning gen- erative replay in continual learning to promote forgetting.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Poisoning gen- erative replay in continual learning to promote forgetting

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.761490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.545101Z digest=sha256:c2b0dca74798b53aab185642b3526787ca51d4f31c16d54a9bb773bed18313d3

Observation 9146e8c3-731c-40a5-979c-6f2693ed51b4 · outbound

This paper cites Not all sam- ples are created equal: Deep learning with importance sam- pling.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Not all sam- ples are created equal: Deep learning with importance sam- pling

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.740797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.549826Z digest=sha256:dfaeaf36937d35fe7e678be57003fb2de2d3d6364473c40045fbc86e36f13fdb

Observation 83f173e0-e35b-4b06-95dc-2f36244d547f · outbound

This paper cites Mstar extended operating conditions: A tutorial.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Mstar extended operating conditions: A tutorial

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.719320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.555017Z digest=sha256:75a6d66c03b69e2398d886daf5e0843263783e6816a20c7e053c046ddd83f194

Observation 52e9f8e0-25d2-489e-a9a2-efd1644db096 · outbound

This paper cites Adversarially robust continual learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Adversarially robust continual learning

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.700389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.559613Z digest=sha256:d1d1132bc21f1df92bebe5af32904d6813704fb81752406665144d6861c32a8b

Observation e3ab875c-8276-4176-8f92-0190c43aca6e · outbound

This paper cites Knowledge transfer in lifelong machine learning: a system- atic literature review.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Knowledge transfer in lifelong machine learning: a system- atic literature review

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.683729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.563962Z digest=sha256:1aa4cc3a4774ee0b7f41202a27587aff5b9887fed8e0ee0d4927fa6ca889508d

Observation dd356f62-ace2-44af-8cc1-9fb63f65c79b · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Adam: A Method for Stochastic Optimization

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.568091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.568091Z digest=sha256:4daecad43c580a3273eed31c6c3039e1ad85163c4db6561b6127fdc792c6ee9c

Observation 9244605d-38a6-4f74-9562-41528eda9a69 · outbound

This paper cites Overcoming catastrophic forgetting in neu- ral networks.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Overcoming catastrophic forgetting in neu- ral networks

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.666573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.572888Z digest=sha256:3e38124aaf49d02e879c378136c297ae5d7067461332322bcd300d8d7bff98d5

Observation 894a56fc-5110-4bcb-9034-a8d7aff4266a · outbound

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

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Learning multiple layers of features from tiny images

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.577511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.577511Z digest=sha256:979640c7376e3dc30390ebf5ad9fbd448d7dc478575c151bd45a8915a7689d7b

Observation 91d48aa1-2bd9-4fea-8cfe-6d6a7b37d800 · outbound

This paper cites an unresolved cited work.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Unresolved cited work

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.582049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.582049Z digest=sha256:82e5e48ed067613de42af684ef2a6ad662889fdc49c3c6ec0b3e1395226bda75

Observation 6d3b49a6-9db8-4b9e-9ada-1cc8d5ab10cc · outbound

This paper cites Targeted data poisoning at- tacks against continual learning neural networks.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Targeted data poisoning at- tacks against continual learning neural networks

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.621110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.586856Z digest=sha256:7c31b1944229a5e3eabaecf24d29fd4dc319cb3b32e20182ed5c8a2404a79a3f

Observation 29fd012e-e1de-44e0-bd99-4cfd7aa87377 · outbound

This paper cites PACOL: Poisoning Attacks Against Continual Learners.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning PACOL: Poisoning Attacks Against Continual Learners

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.591661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.591661Z digest=sha256:ffd332c04c0e32efbfb04534da4aa2b8cc25ad4b9b0e900124309aa94e3ca4db

Observation fd9256d4-1017-463b-8ebf-d5b974e5a6f6 · outbound

This paper cites Gradient descent with early stopping is provably robust to label noise for overparameterized neural networks.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Gradient descent with early stopping is provably robust to label noise for overparameterized neural networks

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.604649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.598146Z digest=sha256:da243bde1253eed56a8ea2eb5c7d499f68a3f3a46457a424b805f456b78381a9

Observation d3ccb0a8-b32c-4ee6-a3c0-22b438e24103 · outbound

This paper cites Learn to grow: A continual structure learn- ing framework for overcoming catastrophic forgetting.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Learn to grow: A continual structure learn- ing framework for overcoming catastrophic forgetting

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.587866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.603448Z digest=sha256:38ffbc8e2f4d07a49834dbf176d0441358f583d9cd1209c01b50b44464defb14

Observation b0534661-044a-48ad-a614-a394fea0b808 · outbound

This paper cites Avalanche: an end-to-end library for contin- ual learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Avalanche: an end-to-end library for contin- ual learning

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.572294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.608071Z digest=sha256:a54f37712d0a03c6d20d4b5634f3c090009e32d9500304ce21830dd2eb46c9a3

Observation de004d84-43e8-49fb-8369-50f77b30600e · outbound

This paper cites Gradient episodic memory for continual learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Gradient episodic memory for continual learning

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.555290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.613234Z digest=sha256:af9821afb73d495d1faa13df1d473be86a0cb86a9c0dfc72b68395a61db1035e

Observation 9234419b-61b3-4bdd-ad0e-6d9141b2cc60 · outbound

This paper cites Coresets for robust training of deep neural networks against noisy labels.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Coresets for robust training of deep neural networks against noisy labels

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.535356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.619533Z digest=sha256:e890102dbef17d754870982923e622c56980e8360ea82a7cdb6fc2110784cc11

Observation 96287101-c89f-43ba-9674-b760e5b0bc43 · outbound

This paper cites Coresets- methods and history: A theoreticians design pattern for ap- proximation and streaming algorithms.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Coresets- methods and history: A theoreticians design pattern for ap- proximation and streaming algorithms

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.517230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.625064Z digest=sha256:0b783ef3ff307c216d55df3f325f56475894f42f5cc8f47eb5fc08dde50e8095

Observation 3806ea34-ed58-4a12-9abc-a86dc11057ca · outbound

This paper cites Lifelong Learning Metrics.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Lifelong Learning Metrics

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.630563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.630563Z digest=sha256:1e17adfb4018086437d319953b7225f48aa22bff8bdc5f5b46da212aa1f60b48

Observation 3e20570f-67e7-4a6b-9cf9-90f6f5aaa0c1 · outbound

This paper cites Latent replay for real-time continual learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Latent replay for real-time continual learning

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.498986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.635990Z digest=sha256:e57429df67082d852423be4aa4e1b1cf39d5ae3cdfec18bedb3155a5fb2f0a14

Observation 04d41fd9-64f7-4871-85c3-0fb356f886a3 · outbound

This paper cites icarl: Incremental classifier and representation learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning icarl: Incremental classifier and representation learning

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.482610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.640741Z digest=sha256:46166759c9cbfc51c7f88ed889f092782314fc25cbb39ee3c10dba4e2cd1c33f

Observation 8db54548-43f1-461b-a51e-8e099baa7988 · outbound

This paper cites Experience replay for continual learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Experience replay for continual learning

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.465789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.645734Z digest=sha256:386193030b6723d96044659fcd42ea55c189e342ca26290f2ac544738b9fe660

Observation 85f9fdc3-9ff1-477c-b5d8-2efdec744b93 · outbound

This paper cites Maintaining Adversarial Robustness in Continuous Learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Maintaining Adversarial Robustness in Continuous Learning

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.650433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.650433Z digest=sha256:744c59bfe8c80403f4a33335d70f978ca0a30823cfb3c1012b00008c98a2b654

Observation 37696f2e-986c-4087-bf8a-5a92703832b2 · outbound

This paper cites Progressive Neural Networks.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Progressive Neural Networks

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.656098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.656098Z digest=sha256:2aef0302e91db2e10257114e5f34bb9066950e5736b77d2c9b6a5ea624f9aeb4

Observation 308eb852-dc61-4f53-b7cb-96b012e3266f · outbound

This paper cites Hidden trigger backdoor attacks.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Hidden trigger backdoor attacks

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.449880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.662416Z digest=sha256:a60f5fee016c4ad1c42586e140860163d6874aa70dbc13ed9968cfc35adf4ea0

Observation 90970104-0f63-42e1-9d21-eed264a5676a · outbound

This paper cites Prioritized Experience Replay.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Prioritized Experience Replay

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.667079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.667079Z digest=sha256:9a236cd23cfbc23a81c13e073e85477a6bcdca08e4c73b4222aa311bc03ba5a7

Observation 4215a16b-b845-45cc-a1e1-119e040915a7 · outbound

This paper cites Continual learning with deep generative replay.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Continual learning with deep generative replay

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.432264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.672192Z digest=sha256:7944cf52400be6806820506c367f9c1175902e8e84a241b1d13cc7df300bd1c3

Observation 58cee3a1-5f41-4948-96df-9e618c9eb003 · outbound

This paper cites Efficientnet: Rethinking model scaling for convolutional neural networks.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Efficientnet: Rethinking model scaling for convolutional neural networks

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.412263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.676803Z digest=sha256:0455279881050af1a891ad9a55164c701ab99039dd71fb9e79276bf9265e4d23

Observation f8dcc596-24fa-4cc0-886e-4e1456273d1d · outbound

This paper cites Lifelong learning algorithms.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Lifelong learning algorithms

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.388074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.681404Z digest=sha256:c93596f23f8008bffe9dccc7a5b942735f3e2b56f2361b1ed120b93a95179d76

Observation 2b3d61f9-367a-4119-8107-edb8aaf1e679 · outbound

This paper cites Gcr: Gradient coreset based replay buffer selection for continual learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Gcr: Gradient coreset based replay buffer selection for continual learning

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.369437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.686148Z digest=sha256:bd20b529ba93d19b6b0302156ab05c4a6499022f7e49b835d5e93b72a348f908

Observation 79c53021-fcd3-4ba8-a437-1a8827109360 · outbound

This paper cites Adversarial targeted forgetting in regularization and generative based continual learning models.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Adversarial targeted forgetting in regularization and generative based continual learning models

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.350108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.691724Z digest=sha256:3a3e31ec16100b68abf9a9af92724fee7ab927896fb0d0ae046aadb8d74e2de4

Observation 28e25329-3fc8-49c2-9f76-9055d48a4d2d · outbound

This paper cites Adversary aware con- tinual learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Adversary aware con- tinual learning

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.333926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.697363Z digest=sha256:ccb93ccc96e8cc7a20e7260f1315d78fdc85acbc7273a98cc597ccda9f24f252

Observation 1c9ce442-74ce-4d6e-a86c-55e189d24814 · outbound

This paper cites Tar- geted forgetting and false memory formation in continual learners through adversarial backdoor attacks.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Tar- geted forgetting and false memory formation in continual learners through adversarial backdoor attacks

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.315901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.703811Z digest=sha256:239e5adec031ea97da21736c6541ffa2cf974dd45dc0c533f15c4ab134b25d0a

Observation b306259b-4f80-4de4-bf88-f936d63b5981 · outbound

This paper cites Three scenarios for continual learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Three scenarios for continual learning

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.708805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.708805Z digest=sha256:c25d5852a0584191b1b88067d6b16536a14110bba770cbbd9e0e0c083bfeba22

Observation d26ac633-c813-401d-b1ad-3658e620bb5a · outbound

This paper cites Three types of incremental learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Three types of incremental learning

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.294423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.713542Z digest=sha256:401f6cfdde741e6fef4a448a05ed42887ac35c0873cf2737923da26c2d42445e

Observation c9c1b940-b89b-4e4a-9d2e-dff85178b9a4 · outbound

This paper cites Prioritized Generative Replay.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Prioritized Generative Replay

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.718465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.718465Z digest=sha256:351ec28c3b9ddb07908b63876bd1174404d52e26d88fff7527bf001417f15f54

Observation 23c2bc3a-cc92-4624-bc3b-3379848917c7 · outbound

This paper cites Metamix: Towards corruption-robust continual learning with tempo- rally self-adaptive data transformation.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Metamix: Towards corruption-robust continual learning with tempo- rally self-adaptive data transformation

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.276211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.723244Z digest=sha256:3fda6072100a281f4a92eb37fccf0942c058a483bfabd73e466b45a9142c8f54

Observation d2ab56a2-4bbc-4580-a9de-dcf3c720065e · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.728091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.728091Z digest=sha256:8eb6faabcc4dc9718d9422d62b62f10781b180eee7e2ee86239b9417e03dad32

Observation 77b43e87-fda7-48d2-9bfe-4152e9ec5537 · outbound

This paper cites Medm- nist v2-a large-scale lightweight benchmark for 2d and 3d biomedical image classification.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Medm- nist v2-a large-scale lightweight benchmark for 2d and 3d biomedical image classification

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.732757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.732757Z digest=sha256:aaa2e9aef4f1f4f451d5486dc36fcb18bdfcf11b77c8bd61018e121755ead952

Observation 307df475-e0f0-4c76-a7c7-7dce02453dee · outbound

This paper cites Lifelong Learning with Dynamically Expandable Networks.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Lifelong Learning with Dynamically Expandable Networks

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.736941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.736941Z digest=sha256:1f6e59f404efc731bbb64f4eb29c2daaa668b3782174dc47549a2fe8e2a34d82

Observation 4472a2e6-2b80-40a1-8516-04249db76d90 · outbound

This paper cites Online coreset selection for rehearsal-based contin- 10 ual learning.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Online coreset selection for rehearsal-based contin- 10 ual learning

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.236314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.741474Z digest=sha256:7f964cca80f24c9a5d034d27dbe10fe94a077c994b611a4628b3cd3f3e164256

Observation 4994b0f8-bae7-44f9-b132-ec1937923ddb · outbound

This paper cites Contin- ual learning through synaptic intelligence.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Contin- ual learning through synaptic intelligence

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-16T11:02:20.745646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:02:20.745646Z digest=sha256:c74344a7f0641ffb88172ed340e34b8eef1d1355b5b0311060cdf9b467754a24

Observation 0e90d872-b2f2-49ef-a778-d9c30220b023 · outbound

This paper cites We first need to define subspacesS+ andS−.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning We first need to define subspacesS+ andS−

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.169392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.754597Z digest=sha256:d1df1117d143274fcac8e821a7830abddb5e42bb593628124570f606c97c1b8c

Observation 3bbf2782-38f9-4cf5-b906-32fbf50f8b37 · outbound

This paper cites an unresolved cited work.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Unresolved cited work

Reference 64

Resolution
unresolved
raw_fallback, observed 2026-08-16T11:02:21.151292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.759845Z digest=sha256:90ae865aae4b69c779acca97da70a00f543f02e3de8002062a53e14b202ea350

Observation f8d31136-fc33-46b3-b0bc-8207acbb527f · outbound

This paper cites At (e) we use the fact that∥J (WT )∥2≥α and so−∥J (WT )∥2≤−α.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning At (e) we use the fact that∥J (WT )∥2≥α and so−∥J (WT )∥2≤−α

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.131687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.764227Z digest=sha256:7ac861db6f6a447b8f1e4a91236d66a5703214cc80af5bbc59e2db447f4c4f30

Observation 1a84e953-651e-481e-976b-9e861db6109f · outbound

This paper cites splitMNIST.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning splitMNIST

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:02:21.102536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.768905Z digest=sha256:c1d67d52b8b019bae23092473414565bfbb4a190853dd848d39245844a52a695

Observation d50a810c-2e5e-43d8-a2fb-22724fc9d3c8 · outbound

This paper cites an unresolved cited work.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Unresolved cited work

Reference 67

Resolution
malformed identifier
raw_fallback, observed 2026-08-16T11:02:21.076588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.773473Z digest=sha256:1aed2e9c84af9d00b3150643e49bdd44bc8d7081472a0a9eb4780b757e7fcf54

Observation 328c6a29-f053-47fa-8abb-d12bc0f506a9 · outbound

This paper cites an unresolved cited work.

Noise-Tolerant Coreset-Based Class Incremental Continual Learning Unresolved cited work

Reference 2017

Resolution
unresolved
raw_fallback, observed 2026-08-16T11:02:21.192957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:02:20.750457Z digest=sha256:7ec4a0164d5771ace7a868aacbd63f2e485f91df963730bad422d6455e50606a

Pith citing papers

No inbound Pith citation observations are available.