Paper Citation Record · LEDGER

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning

As of 11 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2501.02198.

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

pith.paper-citation-record.v1
2501.02198 v2

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:20:51.646626Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

38 of 38 outbound references displayed

verified exact0
verified fuzzy29
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 447e50ed-5d4f-4f5b-b6d8-7561af69e908 · outbound

This paper cites Learning to prompt for continual learning.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Learning to prompt for continual learning

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.241495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9c73c7d2-062f-4241-8da3-d384c0d6aaf5 · outbound

This paper cites Dualprompt: Complementary prompting for rehearsal-free continual learning.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Dualprompt: Complementary prompting for rehearsal-free continual learning

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.226775Z

Source-reported events for the cited work

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Observation 70910829-a7ca-4733-8763-3578bdb3cd6e · outbound

This paper cites Generative feature replay for class-incremental learning.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Generative feature replay for class-incremental learning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.212161Z

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Observation 74c98818-d810-4675-b7d3-7ab705bd5cbb · outbound

This paper cites Memory-efficient incremental learning through feature adaptation.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Memory-efficient incremental learning through feature adaptation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.197957Z

Source-reported events for the cited work

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Observation df0f82e1-7d1c-4af6-8b21-602b9703b05e · outbound

This paper cites Self- sustaining representation expansion for non-exemplar class-incremental learning.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Self- sustaining representation expansion for non-exemplar class-incremental learning

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.183277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cb863f34-d1ca-435c-a556-dd7db48f08d5 · outbound

This paper cites An unconstrained layer-peeled perspective on neural collapse.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning An unconstrained layer-peeled perspective on neural collapse

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.169054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1466fb12-1587-426d-82a8-995f907e907e · outbound

This paper cites Neural collapse in deep homogeneous classifiers and the role of weight decay.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Neural collapse in deep homogeneous classifiers and the role of weight decay

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.155864Z

Source-reported events for the cited work

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Observation 321ec360-b9ad-4a02-b582-75a1b3785eba · outbound

This paper cites Prevalence of neural collapse during the terminal phase of deep learning training.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Prevalence of neural collapse during the terminal phase of deep learning training

Reference 8

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Source-reported events for the cited work

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Observation aae97f80-1c57-4887-9b4a-89c6225c2458 · outbound

This paper cites PCA versus LDA.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning PCA versus LDA

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.126668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c003f8d0-0d34-4f43-87a9-defd8cefb524 · outbound

This paper cites OrCo: Towards better generalization via orthogonality and contrast for few-shot class-incremental learning.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning OrCo: Towards better generalization via orthogonality and contrast for few-shot class-incremental learning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.112294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e09882a7-77ad-4769-a11c-7f92d28479c5 · outbound

This paper cites Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class Incremental Learning.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class Incremental Learning

Reference 11

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Source-reported events for the cited work

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Observation 118503e7-5098-4b26-a05c-f3af1776f8f2 · outbound

This paper cites Learning equi-angular representations for online continual learn- ing.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Learning equi-angular representations for online continual learn- ing

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.097796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9634e8f0-5957-4d5a-a28d-f80699a5c7f6 · outbound

This paper cites DER: Dynamically expandable representation for class incremental learning.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning DER: Dynamically expandable representation for class incremental learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.083226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9ddd7a31-cf75-4916-b17d-3417831ef44a · outbound

This paper cites Il2m: Class incremental learning with dual memory.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Il2m: Class incremental learning with dual memory

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.068122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7d14e01c-7d16-492f-a7d3-4c594c59e973 · outbound

This paper cites Class- incremental learning using diffusion model for distillation and replay.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Class- incremental learning using diffusion model for distillation and replay

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.053199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5d5e78cc-257d-4fc7-8420-e0d8e3f38834 · outbound

This paper cites PackNet: Adding multiple tasks to a single network by iterative pruning.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning PackNet: Adding multiple tasks to a single network by iterative pruning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.039040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ffcca99e-0b2d-4b41-885c-3c10b80a9bb7 · outbound

This paper cites In defense of the learning without forgetting for task incremental learning.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning In defense of the learning without forgetting for task incremental learning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.024206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0b5b0573-5238-498b-b1d9-05c04cab6aea · outbound

This paper cites Adaptive mixtures of local experts.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Adaptive mixtures of local experts

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:52.009367Z

Source-reported events for the cited work

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Observation 565a0267-c972-4e1e-af43-f0fcc84872d7 · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 20

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Source-reported events for the cited work

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Observation 2f571cfc-e549-415a-8f62-79dc72143ffc · outbound

This paper cites Fine-Grained Visual Classification of Aircraft.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Fine-Grained Visual Classification of Aircraft

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T22:20:51.563528Z

Source-reported events for the cited work

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Observation c2485b97-1b77-4e83-97f6-fb4dd212e63f · outbound

This paper cites Automated flower classification over a large number of classes.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Automated flower classification over a large number of classes

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:51.994123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 850ccd0c-f564-4c07-8b5f-099e4907306c · outbound

This paper cites Bossard, M.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Bossard, M

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:51.979272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 794b1741-be3a-4fe8-b1dd-b2ecc9ef9535 · outbound

This paper cites Vedaldi, A.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Vedaldi, A

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:51.965269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 566792a8-d4cf-42ea-8214-1cd47469b8dd · outbound

This paper cites Krause, M.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Krause, M

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4f927b37-06f0-44a3-ac72-1317dc81ecdc · outbound

This paper cites Fei-Fei, R.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Fei-Fei, R

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:51.937335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6a89aadd-fa63-444d-917f-ecab6bc4af53 · outbound

This paper cites Dytox: Transformers for continual learning with dynamic token expansion.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Dytox: Transformers for continual learning with dynamic token expansion

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:51.923379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d0805e18-d211-406a-9f31-7baf600c6fb4 · outbound

This paper cites Cimpoi, S.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Cimpoi, S

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:51.906980Z

Source-reported events for the cited work

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Observation 0924dac2-f223-4ac5-b631-7029349ec904 · outbound

This paper cites EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification

Reference 29

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Source-reported events for the cited work

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Observation 1ca04554-accc-4921-aac7-4f11cd5b22e0 · outbound

This paper cites LeCun, C.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning LeCun, C

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:51.892024Z

Source-reported events for the cited work

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Observation 8ed2814b-ce1f-47f1-ab33-60daed0a6951 · outbound

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Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:20:51.876310Z

Source-reported events for the cited work

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Observation 61fc57e9-2cd5-48a1-98a1-f2ec3e2dfb6b · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T22:20:51.617088Z

Source-reported events for the cited work

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Observation eb3d2317-70a0-47e2-9fa9-700154efc08b · outbound

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Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:20:51.859281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9f1061c0-1456-464d-a9e4-ac9a98d1557b · outbound

This paper cites Overcoming catastrophic forgetting by incremental moment matching.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Overcoming catastrophic forgetting by incremental moment matching

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:51.843501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 06da3e70-be74-4148-a235-e9e2948075db · outbound

This paper cites Don't Stop Learning: Towards Continual Learning for the CLIP Model.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Don't Stop Learning: Towards Continual Learning for the CLIP Model

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T22:20:51.629737Z

Source-reported events for the cited work

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Observation 70328fe8-d7e7-40dd-ab37-b3f6b7d06ac4 · outbound

This paper cites Robust fine-tuning of zero-shot models.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Robust fine-tuning of zero-shot models

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:51.826733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a7751a11-ba53-4121-a5a9-b51c7e353b8f · outbound

This paper cites Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-10T22:20:51.638607Z

Source-reported events for the cited work

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Observation 1cfad811-0551-4fac-ac94-11e78a49b769 · outbound

This paper cites iCaRL: Incremental classifier and representation learning.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning iCaRL: Incremental classifier and representation learning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:51.810489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fa308368-c899-4fd1-9b0a-a9e07e8a0be1 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Learning transferable visual models from natural language supervision

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:20:51.795201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

No inbound Pith citation observations are available.