Paper Citation Record · LEDGER

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation

As of 19 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2507.08686.

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

pith.paper-citation-record.v1
2507.08686 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:19:59.280738Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

39 of 39 outbound references displayed

verified exact3
verified fuzzy24
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cbaff13d-80c1-43f4-b9cd-7742953da9a2 · outbound

This paper cites A convnet for the 2020s,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation A convnet for the 2020s,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.802562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4fb93a48-7349-4b49-aaba-2c382fff0e0b · outbound

This paper cites Deep learning-based improved snapshot ensemble technique for covid-19 chest x-ray classification,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Deep learning-based improved snapshot ensemble technique for covid-19 chest x-ray classification,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.789953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ef575f4d-95d0-483c-a06f-34fdb484adf5 · outbound

This paper cites On Local Overfitting and Forgetting in Deep Neural Networks.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation On Local Overfitting and Forgetting in Deep Neural Networks

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-06T18:19:59.471472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 22ce29d4-44a2-47ab-87f1-52fc3c7c4eb3 · outbound

This paper cites A closer look at memorization in deep networks,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation A closer look at memorization in deep networks,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.773867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3600a677-4c6e-46ba-815b-21e537e0048d · outbound

This paper cites Catastrophic interfer- ence in connectionist networks: The sequential learning problem,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Catastrophic interfer- ence in connectionist networks: The sequential learning problem,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.761979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ee681d88-199a-4121-823d-57f890f3b47e · outbound

This paper cites A survey on ensemble learning under the era of deep learning,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation A survey on ensemble learning under the era of deep learning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.750237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fd565a2f-ec28-47de-b1a7-b4d36da0805c · outbound

This paper cites Dropout: a simple way to pre- vent neural networks from overfitting,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Dropout: a simple way to pre- vent neural networks from overfitting,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.739962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e0d036fa-b036-4138-b402-152f030c9c7f · outbound

This paper cites Horizontal and Vertical Ensemble with Deep Representation for Classification.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Horizontal and Vertical Ensemble with Deep Representation for Classification

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-06T18:19:59.457126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dfcf775b-985d-4ecf-83c0-02a8547aabed · outbound

This paper cites Acceleration of stochastic approximation by averaging,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Acceleration of stochastic approximation by averaging,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.728553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5fbddbde-fc22-4141-9490-04045e6d8783 · outbound

This paper cites Averaging Weights Leads to Wider Optima and Better Generalization.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Averaging Weights Leads to Wider Optima and Better Generalization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T18:19:59.170546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60d0deda-d632-4dc3-8e54-5cf8d40dbfd4 · outbound

This paper cites dropcyclic: snapshot en- semble convolutional neural network based on a new learning rate schedule for land use classification,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation dropcyclic: snapshot en- semble convolutional neural network based on a new learning rate schedule for land use classification,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.716450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 197f8b4a-c9c5-418b-9e1a-ca3086de1d1b · outbound

This paper cites Stochastic weight averaging revisited,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Stochastic weight averaging revisited,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.704459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dd0a1ef2-6aa9-43c4-9470-ce09b60ee3f3 · outbound

This paper cites Reconcil- ing modern machine-learning practice and the classical bias–variance trade-off,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Reconcil- ing modern machine-learning practice and the classical bias–variance trade-off,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.692504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5e4414c9-290c-4dc3-9960-ba74e41ee945 · outbound

This paper cites Deep double descent: Where bigger models and more data hurt,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Deep double descent: Where bigger models and more data hurt,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.679599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 253ab1ba-467c-4da7-b099-75b03d3f0035 · outbound

This paper cites When and how epochwise double descent happens.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation When and how epochwise double descent happens

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T18:19:59.193516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 078eaf52-f203-40d6-b116-55c7f5b41b16 · outbound

This paper cites Early Stopping in Deep Networks: Double Descent and How to Eliminate it.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Early Stopping in Deep Networks: Double Descent and How to Eliminate it

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T18:19:59.197904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94f07cc1-5eb5-4e3e-be6c-9b50fd1d5d6d · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Distilling the Knowledge in a Neural Network

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T18:19:59.201651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38b0fb14-64cb-4d9c-97f0-a07951a89ed5 · outbound

This paper cites Rethinking Self-Distillation: Label Averaging and Enhanced Soft Label Refinement with Partial Labels.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Rethinking Self-Distillation: Label Averaging and Enhanced Soft Label Refinement with Partial Labels

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-06T18:19:59.384475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 68cce53b-592a-43b3-a234-7ae83059a179 · outbound

This paper cites United we stand: Using epoch-wise agreement of ensembles to combat overfit,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation United we stand: Using epoch-wise agreement of ensembles to combat overfit,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.664411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c799125e-ab5f-436e-9539-60df4ff2888d · outbound

This paper cites Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T18:19:59.213224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcae711c-346e-4018-85f4-bf4876c51ff8 · outbound

This paper cites Revisiting Self-Distillation.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Revisiting Self-Distillation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T18:19:59.216769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9c93570-d932-4a75-98b9-130d2b34b6a1 · outbound

This paper cites Understanding self-distillation in the presence of label noise,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Understanding self-distillation in the presence of label noise,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.652479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 26ebbe31-060c-4542-83ba-9a33cca7750e · outbound

This paper cites Efficient knowledge distillation from model check- points,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Efficient knowledge distillation from model check- points,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.639843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation feaa9914-09bb-4b7a-9d16-80f5663cb750 · outbound

This paper cites Learn from the past: Experience ensemble knowledge distilla- tion,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Learn from the past: Experience ensemble knowledge distilla- tion,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.626480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2f82c8b5-67a2-4cdd-9ee8-4092e3511575 · outbound

This paper cites Snapshot Ensembles: Train 1, get M for free.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Snapshot Ensembles: Train 1, get M for free

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T18:19:59.228219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4385af9b-55c2-409f-862a-717d3be202fd · outbound

This paper cites Loss surfaces, mode connectivity, 1 and fast ensembling of dnns,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Loss surfaces, mode connectivity, 1 and fast ensembling of dnns,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.613215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e20db75f-b6e0-4825-9f86-eda1da4bbb05 · outbound

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

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T18:19:59.233671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53d4d906-2695-4e04-b610-5fcac534bc98 · outbound

This paper cites Maxvit: Multi-axis vision trans- former,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Maxvit: Multi-axis vision trans- former,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.598916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b867ce83-b17b-47e5-90f9-cc5e1de861dd · outbound

This paper cites Principal components bias in over-parameterized linear models, and its mani- festation in deep neural networks,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Principal components bias in over-parameterized linear models, and its mani- festation in deep neural networks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.579852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 541d22cc-9aa2-47dc-b1da-65712adee65e · outbound

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

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Imagenet: A large-scale hierarchical image database,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.569733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1f2d5dfd-2453-433d-9c89-c9e308269633 · outbound

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

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Learning multiple layers of features from tiny images,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T18:19:59.248528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25f7d5de-0c76-4b81-b877-d41db36639f6 · outbound

This paper cites Tiny imagenet visual recognition challenge,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Tiny imagenet visual recognition challenge,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.553920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b6d2f36f-93a3-417b-8e99-544e444bf8c8 · outbound

This paper cites Learning with noisy labels revisited: A study using real-world human annotations,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Learning with noisy labels revisited: A study using real-world human annotations,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.544368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8e4c738a-150f-4874-a21a-50cf915c2020 · outbound

This paper cites Deep residual learning for image recognition,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Deep residual learning for image recognition,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.534279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2bc9065e-0f43-43cb-957f-f5a31e41873b · outbound

This paper cites Making deep neural networks robust to label noise: A loss correction approach,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Making deep neural networks robust to label noise: A loss correction approach,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.525532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cec2400a-cd15-4292-9641-ba0a08ced8bc · outbound

This paper cites Towards fair- ness in visual recognition: Effective strategies for bias mitigation,.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Towards fair- ness in visual recognition: Effective strategies for bias mitigation,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:19:59.514416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 506237b9-3ddb-4c60-8d8e-0d63508a34f9 · outbound

This paper cites Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T18:19:59.272856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66a487e6-aa51-4dcc-86f4-ab7e8b10c72b · outbound

This paper cites an unresolved cited work.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-08-06T18:19:59.502165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9544ae66-6237-4eea-b3e9-a3b9a406173f · outbound

This paper cites an unresolved cited work.

Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-06T18:19:59.492153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.