Paper Citation Record · LEDGER

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning

As of 10 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2509.11285.

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

pith.paper-citation-record.v1
2509.11285 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T16:55:15.359211Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T17:03:01.884380Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T00:47:30.257787Z

Reference resolution

35 of 35 outbound references displayed

verified exact0
verified fuzzy0
unresolved35
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 67558cde-3ed0-441d-9ccd-ee2a10677f48 · outbound

This paper cites A case study of incremental concept induction.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning A case study of incremental concept induction

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:13.475045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ceeaefc5-bce1-45c0-bbf0-a46b28753c4e · outbound

This paper cites an unresolved cited work.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:13.508271Z

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Observation f1906ec5-b7a9-481e-8a21-c2f6f966119d · outbound

This paper cites an unresolved cited work.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:13.589930Z

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Observation ad8238fc-ab4d-49e0-9cfb-6deb7ca306fa · outbound

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

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Learn to grow: A continual structure learning framework for overcoming catastrophic forgetting

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:13.653472Z

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Observation 4c253fb4-a2d3-4850-9890-5c024ed9f5d9 · outbound

This paper cites On Tiny Episodic Memories in Continual Learning.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning On Tiny Episodic Memories in Continual Learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:13.728445Z

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Observation 78090052-a1c1-402f-b3f3-dcf8ed690ce0 · outbound

This paper cites Dark experience for general continual learning: a strong, simple baseline.Advances in neural information processing systems, 33:15920–15930, 2020.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Dark experience for general continual learning: a strong, simple baseline.Advances in neural information processing systems, 33:15920–15930, 2020

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:13.789984Z

Source-reported events for the cited work

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Observation 9f35ee59-3f4d-4602-96d1-5b1f8b2f40cf · outbound

This paper cites Revisiting class-incremental learning with pre-trained models: Generalizability and adaptivity are all you need.International Journal of Computer Vision, 133(3):1012–1032, 2025.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Revisiting class-incremental learning with pre-trained models: Generalizability and adaptivity are all you need.International Journal of Computer Vision, 133(3):1012–1032, 2025

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:13.872771Z

Source-reported events for the cited work

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Observation c1390bdb-e02b-43cf-9111-7dccb28f2fcc · outbound

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

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Imagenet: A large-scale hierarchical image database

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:13.926489Z

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Observation 3cad18cf-6a76-4ec0-855f-19c6f379788a · outbound

This paper cites Tiny imagenet visual recognition challenge.CS 231N, 7(7):3, 2015.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Tiny imagenet visual recognition challenge.CS 231N, 7(7):3, 2015

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.009882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 348e4e07-2a0e-4b47-ab6a-9146f448ee73 · outbound

This paper cites Parisi, Ronald Kemker, Jose L.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Parisi, Ronald Kemker, Jose L

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.082874Z

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Observation 3a10b1e5-8cd8-4f94-ace3-47c4aef01bdf · outbound

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

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Memory-efficient incremental learning through feature adaptation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.141830Z

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Observation 3ce05f9b-d4ba-4ce0-8024-ac7bd2b1854d · outbound

This paper cites Lifelong Learning with Dynamically Expandable Networks.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Lifelong Learning with Dynamically Expandable Networks

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.197648Z

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Unavailable: canonical work link unavailable.

Observation 2e5f7e44-af0a-4879-bd30-f6bf3b47feb6 · outbound

This paper cites Class-incremental learning: survey and performance evaluation on image classification.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(5):5513–5533, 2022.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Class-incremental learning: survey and performance evaluation on image classification.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(5):5513–5533, 2022

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.245383Z

Source-reported events for the cited work

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Observation 68257fcf-1976-4b70-a192-738b9a13987c · outbound

This paper cites A neural network account of memory replay and knowledge consolidation.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning A neural network account of memory replay and knowledge consolidation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.309420Z

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Unavailable: canonical work link unavailable.

Observation ebbfa21a-5724-4d7a-9935-1ee6491492f5 · outbound

This paper cites Gradient based sample selection for online continual learning.Advances in neural information processing systems, 32, 2019.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Gradient based sample selection for online continual learning.Advances in neural information processing systems, 32, 2019

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.361989Z

Source-reported events for the cited work

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Observation e3336472-e179-4b24-8440-4ecfb0566f54 · outbound

This paper cites Continual learning with deep generative replay.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Continual learning with deep generative replay

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.392044Z

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Observation 1d1a074f-ea78-4b37-a449-cfec4e8635b1 · outbound

This paper cites Generative replay with feedback connections as a general strategy for continual learning.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Generative replay with feedback connections as a general strategy for continual learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.448071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cee51df-7036-4ae9-8338-e0a9710776dc · outbound

This paper cites Class-incremental learning with generative classifiers.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Class-incremental learning with generative classifiers

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.497228Z

Source-reported events for the cited work

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Observation 4de67d8c-1058-438c-807e-d4e44466e4f1 · outbound

This paper cites Progressive Neural Networks.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Progressive Neural Networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.557104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation beaa5321-7b33-45c4-b91b-319011ef68a6 · outbound

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

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Packnet: Adding multiple tasks to a single network by iterative pruning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.597132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 042b6ea3-0418-4517-9202-ebbe504727b2 · outbound

This paper cites an unresolved cited work.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.636291Z

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Unavailable: canonical work link unavailable.

Observation a414f5b8-f4be-499d-ae47-4cfa6ec23aa5 · outbound

This paper cites Generating instance-level prompts for rehearsal- free continual learning.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Generating instance-level prompts for rehearsal- free continual learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.715559Z

Source-reported events for the cited work

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Observation a771c893-dae7-4a32-89c3-22e66438cd55 · outbound

This paper cites Regularized one-layer neural networks for distributed and incremental environments.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Regularized one-layer neural networks for distributed and incremental environments

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.755961Z

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Observation 9b9003c4-ee53-4bff-ae64-64ab08835f31 · outbound

This paper cites Deep residual learning for image recognition.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Deep residual learning for image recognition

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.823578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1daba6c3-935d-499b-9a53-99a2c85f644c · outbound

This paper cites Class-incremental learning: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12):9851–9873, 2024.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Class-incremental learning: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12):9851–9873, 2024

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.855398Z

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Observation df4e3f22-444c-4505-8bd7-ee2749c08f74 · outbound

This paper cites Connectionist models of recognition memory: constraints imposed by learning and forgetting functions.Psychological review, 97(2):285, 1990.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Connectionist models of recognition memory: constraints imposed by learning and forgetting functions.Psychological review, 97(2):285, 1990

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.916947Z

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Unavailable: canonical work link unavailable.

Observation 842f2725-82e3-48a9-83f5-f47e3bf037e6 · outbound

This paper cites Rmm: Reinforced memory management for class-incremental learning.Advances in Neural Information Processing Systems, 34:3478–3490, 2021.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Rmm: Reinforced memory management for class-incremental learning.Advances in Neural Information Processing Systems, 34:3478–3490, 2021

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.961065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c24ea2e-dbb8-4242-b95f-49219eaf38bb · outbound

This paper cites Gradient episodic memory for continual learning.Advances in neural information processing systems, 30, 2017.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Gradient episodic memory for continual learning.Advances in neural information processing systems, 30, 2017

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:14.997563Z

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Observation 3a36c2cc-a22e-4034-9d19-4d6e6a15157a · outbound

This paper cites Foster: Feature boosting and compression for class-incremental learning.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Foster: Feature boosting and compression for class-incremental learning

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:15.053973Z

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Unavailable: canonical work link unavailable.

Observation 3f95b71c-4b3d-4681-9e2d-42729f73221f · outbound

This paper cites A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:15.102431Z

Source-reported events for the cited work

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Observation 5c021668-2480-4442-a278-86e69398faff · outbound

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

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Der: Dynamically expandable representation for class incremental learning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:15.138743Z

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Observation a92cc541-4c45-45c8-a96e-ca1319b02c90 · outbound

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

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Podnet: Pooled outputs distillation for small-tasks incremental learning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:15.196886Z

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Observation bb1e5f07-fc3e-4fc6-82d5-bfb95a95a46e · outbound

This paper cites Co-transport for class-incremental learning.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Co-transport for class-incremental learning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:15.247049Z

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Observation 9b3cd2c9-e94d-4bf5-bd08-951c879d81fa · outbound

This paper cites Large scale incremental learning.

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Large scale incremental learning

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:15.303063Z

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Observation 3f707691-5a42-4da1-94cc-5d8a0417147b · outbound

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

CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning Maintaining discrimination and fairness in class incremental learning

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-04T16:55:15.359211Z

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Pith citing papers

Observation 396b5822-c3cb-4c9f-9c84-cc78ea12db35 · inbound

HydraCIL: Decoupled Class-Incremental Learning through Prototype-Guided Multi-Head Classifiers cites this paper.

HydraCIL: Decoupled Class-Incremental Learning through Prototype-Guided Multi-Head Classifiers CIFNet: An Analytic Neural Learning Framework for Efficient and Calibrated Class-Incremental Learning

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-29T01:24:25.241578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.