Paper Citation Record · LEDGER

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning

As of 8 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2506.15720.

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

pith.paper-citation-record.v1
2506.15720 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:08:31.639750Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

47 of 47 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 24b2709e-c0b8-41c8-a185-df39ad896b7a · outbound

This paper cites Orco: To- wards better generalization via orthogonality and contrast for few-shot class-incremental learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Orco: To- wards better generalization via orthogonality and contrast for few-shot class-incremental learning

Reference 1

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Observation a4d83acb-aa9f-4fa6-aaa1-54e7be3129d4 · outbound

This paper cites Il2m: Class incremen- tal learning with dual memory.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Il2m: Class incremen- tal learning with dual memory

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:41.188045Z

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Observation 4a58f9a4-1697-4e41-a287-d50ef6dd46e8 · outbound

This paper cites Efficient Lifelong Learning with A-GEM.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Efficient Lifelong Learning with A-GEM

Reference 3

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Observation ac7ed952-2cff-4b76-b571-e0600e034a62 · outbound

This paper cites Incremental few-shot learn- ing via vector quantization in deep embedded space.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Incremental few-shot learn- ing via vector quantization in deep embedded space

Reference 4

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Observation 4a5beca0-98e3-481a-9bd1-3db2bfcc5150 · outbound

This paper cites Synthesized feature based few-shot class- incremental learning on a mixture of subspaces.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Synthesized feature based few-shot class- incremental learning on a mixture of subspaces

Reference 5

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Observation 961118f3-3fae-48d7-bf34-b9a2df3231c9 · outbound

This paper cites Metafscil: A meta-learning approach for few- shot class incremental learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Metafscil: A meta-learning approach for few- shot class incremental learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:40.445961Z

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Observation 83e60239-0746-40e5-9bf9-0c422528d711 · outbound

This paper cites Randaugment: Practical automated data augmentation with a reduced search space.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Randaugment: Practical automated data augmentation with a reduced search space

Reference 7

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Observation d439f2c0-4e15-4463-a96d-5ebc32f627b6 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Imagenet: A large-scale hierarchical image database

Reference 8

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Observation a2379891-9536-45f8-b850-ba711f4a6f44 · outbound

This paper cites Improved Regularization of Convolutional Neural Networks with Cutout.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Improved Regularization of Convolutional Neural Networks with Cutout

Reference 9

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Observation ebe1946b-47c9-4412-80f0-f9a01dec13b3 · outbound

This paper cites Ensemble methods in machine learn- ing.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Ensemble methods in machine learn- ing

Reference 10

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Source-reported events for the cited work

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Observation daf13579-6bf6-42af-b7bc-6fd52caadf8c · outbound

This paper cites Few-shot class- incremental learning via relation knowledge distillation.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Few-shot class- incremental learning via relation knowledge distillation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:39.792614Z

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Observation 91141ff4-6c69-42f2-bf2f-f74356ea1d3b · outbound

This paper cites Podnet: Pooled outputs distilla- tion for small-tasks incremental learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Podnet: Pooled outputs distilla- tion for small-tasks incremental learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:39.549903Z

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Observation 14212927-4fd7-48f3-b20d-31d72551abbd · outbound

This paper cites Neural network en- sembles.IEEE Trans.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Neural network en- sembles.IEEE Trans

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:39.388290Z

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Observation 868f7a7d-13a1-423f-a516-25c3329c346a · outbound

This paper cites Deep residual learning for image recognition.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Deep residual learning for image recognition

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:39.255436Z

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Observation dd724574-81a3-49f0-9b36-d9a68e46eaba · outbound

This paper cites Learning a unified classifier incrementally via re- balancing.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Learning a unified classifier incrementally via re- balancing

Reference 15

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Observation 628995fc-5ed2-4974-86c3-e87c0324955f · outbound

This paper cites Snapshot ensembles: Train 1, get m for free.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Snapshot ensembles: Train 1, get m for free

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:38.925551Z

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Observation 7fd0c5ee-aa28-4f33-998d-2b0d57dc9360 · outbound

This paper cites S3c: Self-supervised stochastic classifiers for few-shot class-incremental learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning S3c: Self-supervised stochastic classifiers for few-shot class-incremental learning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:38.674403Z

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Observation ebe11201-c9d1-4632-b1e0-72af68f98bb5 · outbound

This paper cites On the soft- subnetwork for few-shot class incremental learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning On the soft- subnetwork for few-shot class incremental learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:38.472661Z

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Observation 2e7dcb31-aa66-40ef-a565-341d622b33d7 · outbound

This paper cites Warping the space: Weight space rotation for class- incremental few-shot learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Warping the space: Weight space rotation for class- incremental few-shot learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:38.280980Z

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Observation 3ef83246-e8d7-41e1-9226-8602ef78813c · outbound

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

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Learning multiple layers of features from tiny images

Reference 20

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Observation 7724a589-b0de-4c36-9192-1f91fc94113d · outbound

This paper cites Imagenet classification with deep convolutional neural net- works.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Imagenet classification with deep convolutional neural net- works

Reference 21

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Observation 47b7562a-668f-476b-a2fa-96ea63f3aeb4 · outbound

This paper cites Learning without forgetting.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Learning without forgetting

Reference 22

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Observation e56eb4b1-b887-4b17-9a46-20fe281f02d0 · outbound

This paper cites Few-shot class-incremental learn- ing via entropy-regularized data-free replay.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Few-shot class-incremental learn- ing via entropy-regularized data-free replay

Reference 23

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Observation b3e25507-c60f-42ba-9b4c-6131cc4ecf98 · outbound

This paper cites Closer: Towards better representation learning for few-shot class- incremental learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Closer: Towards better representation learning for few-shot class- incremental learning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:37.451981Z

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Observation 9f114d93-465f-4ef7-a63d-58025f619d1d · outbound

This paper cites Few-shot class-incremental learning from an open- set perspective.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Few-shot class-incremental learning from an open- set perspective

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:37.204330Z

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Observation 883f920f-7458-40b7-a265-262f7f99c2fc · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Learn- ing transferable visual models from natural language super- vision

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:36.895237Z

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Observation 51eac31f-edbc-4676-8698-f04beed5e8fa · outbound

This paper cites icarl: Incremental clas- sifier and representation learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning icarl: Incremental clas- sifier and representation learning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:36.582223Z

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Observation 9fa5f04a-211c-4c02-83f5-348d6be4302a · outbound

This paper cites Experience replay for continual learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Experience replay for continual learning

Reference 28

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Observation 2e4a881a-f013-4478-b324-e684ee5ce005 · outbound

This paper cites Learning with fantasy: Semantic-aware virtual contrastive constraint for few-shot class-incremental learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Learning with fantasy: Semantic-aware virtual contrastive constraint for few-shot class-incremental learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:36.021651Z

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Observation 9d411d50-f306-43a4-a6f5-35d7f8cd21eb · outbound

This paper cites Going deeper with convolutions.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Going deeper with convolutions

Reference 30

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Observation d3b6cd0b-5ad5-43aa-8b4c-2a2b1c355196 · outbound

This paper cites Rethinking few-shot class-incremental learning: Learning from yourself.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Rethinking few-shot class-incremental learning: Learning from yourself

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:35.521105Z

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Observation a955a973-5fbc-436f-9ea9-9e075ba7d71f · outbound

This paper cites Few-shot class- incremental learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Few-shot class- incremental learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:35.302542Z

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Observation 01acb99b-e291-4d7f-9b2e-92fe08eba6fc · outbound

This paper cites Matching networks for one shot learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Matching networks for one shot learning

Reference 33

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Observation 34760fc9-a081-45fa-b985-22edee7041c5 · outbound

This paper cites The caltech-ucsd birds-200-2011 dataset.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning The caltech-ucsd birds-200-2011 dataset

Reference 34

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Observation 04e3bc49-ae73-41fb-958e-514a98977987 · outbound

This paper cites Learning to prompt for continual learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Learning to prompt for continual learning

Reference 35

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Observation e1483fbd-001f-488c-90aa-e15ea934f303 · outbound

This paper cites Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing in- ference time.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing in- ference time

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:34.455568Z

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Observation 75936821-4cd0-468a-829c-caccdd0efa80 · outbound

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

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Robust fine-tuning of zero-shot models

Reference 37

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Observation b5f48d4b-891c-4944-b872-1b9db10734c5 · outbound

This paper cites Large scale incre- mental learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Large scale incre- mental learning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:33.915053Z

Source-reported events for the cited work

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Observation 071098b1-2af5-4df2-9ca8-c39ee72da1c7 · outbound

This paper cites Der: Dynam- ically expandable representation for class incremental learn- ing.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Der: Dynam- ically expandable representation for class incremental learn- ing

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:33.725864Z

Source-reported events for the cited work

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Observation caee82e0-3cf1-45b5-a3b7-21ce7889dca0 · outbound

This paper cites Neural collapse inspired feature- classifier alignment for few-shot class incremental learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Neural collapse inspired feature- classifier alignment for few-shot class incremental learning

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:33.470985Z

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Observation 56ae5ff9-a7ff-429e-aa3f-473c2a90d416 · outbound

This paper cites Cutmix: Regu- larization strategy to train strong classifiers with localizable features.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Cutmix: Regu- larization strategy to train strong classifiers with localizable features

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:33.218099Z

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Observation dc7add48-4c94-46df-bebe-ad402177c3a4 · outbound

This paper cites Few-shot incremental learning with contin- ually evolved classifiers.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Few-shot incremental learning with contin- ually evolved classifiers

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:32.940863Z

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Observation 2d704e90-feb6-469b-97ba-d1ec9569b28f · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning mixup: Beyond Empirical Risk Minimization

Reference 43

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Source-reported events for the cited work

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Observation e6595a02-1676-46ab-a67f-b8e848c3b102 · outbound

This paper cites Maintaining discrimination and fairness in class incremental learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Maintaining discrimination and fairness in class incremental learning

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:32.673878Z

Source-reported events for the cited work

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Observation 66e7d8fb-4f94-483e-be5b-4953cfcce814 · outbound

This paper cites Few-shot class- incremental learning via class-aware bilateral distillation.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Few-shot class- incremental learning via class-aware bilateral distillation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:32.471193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 50ebdd11-f4cf-40c4-a26f-fc9c9a385a23 · outbound

This paper cites Forward compatible few-shot class-incremental learning.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Forward compatible few-shot class-incremental learning

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:32.232236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f57d2158-79a8-4702-a7a8-76ac06643694 · outbound

This paper cites Gkeal: Gaussian kernel embedded analytic learning for few-shot class incremental task.

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning Gkeal: Gaussian kernel embedded analytic learning for few-shot class incremental task

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:31.878976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.