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Paper Citation Record · LEDGER

Multi-Level Correlation Network For Few-Shot Image Classification

As of 13 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2412.03159.

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

pith.paper-citation-record.v1
2412.03159 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:45:45.615044Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

30 of 30 outbound references displayed

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  • verified fuzzy29
  • unresolved1
  • parse uncertain0
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External citation measurements

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Outbound references

Observation 53a8b636-2370-40bc-b852-5cde9ccf3cde · outbound

This paper cites Model-agnostic meta-learning for fast adap- tation of deep networks,.

Multi-Level Correlation Network For Few-Shot Image Classification Model-agnostic meta-learning for fast adap- tation of deep networks,

Reference 1

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Observation 29d53fe2-2ddd-4101-9120-899f0f985038 · outbound

This paper cites Matching networks for one shot learning,.

Multi-Level Correlation Network For Few-Shot Image Classification Matching networks for one shot learning,

Reference 2

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Observation 989aa713-b2e4-48a8-baee-e11d02c91f74 · outbound

This paper cites Prototypical networks for few-shot learning,.

Multi-Level Correlation Network For Few-Shot Image Classification Prototypical networks for few-shot learning,

Reference 3

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Observation 767c0892-5cd4-4fe8-9a59-68353446113a · outbound

This paper cites Learning to compare: Relation network for few-shot learning,.

Multi-Level Correlation Network For Few-Shot Image Classification Learning to compare: Relation network for few-shot learning,

Reference 4

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Observation 4be96974-a0eb-4d25-9912-b3e269f8fe1c · outbound

This paper cites Siamese neural networks for one-shot image recognition,.

Multi-Level Correlation Network For Few-Shot Image Classification Siamese neural networks for one-shot image recognition,

Reference 5

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Observation 4d66e749-a2ad-42a9-ae57-cfbeb404efd9 · outbound

This paper cites LibFewShot: A Comprehensive Library for Few-shot Learning.

Multi-Level Correlation Network For Few-Shot Image Classification LibFewShot: A Comprehensive Library for Few-shot Learning

Reference 6

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Observation bbb89b1c-573a-43d0-b985-135e3d290352 · outbound

This paper cites A closer look at few-shot classification,.

Multi-Level Correlation Network For Few-Shot Image Classification A closer look at few-shot classification,

Reference 7

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Observation d716df75-c0e7-41e6-b234-3be8432c3618 · outbound

This paper cites Tadam: Task dependent adaptive metric for improved few-shot learning,.

Multi-Level Correlation Network For Few-Shot Image Classification Tadam: Task dependent adaptive metric for improved few-shot learning,

Reference 8

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Observation 3599b52d-444f-42b9-a7b0-91bc6be362eb · outbound

This paper cites Meta-baseline: Exploring simple meta- learning for few-shot learning,.

Multi-Level Correlation Network For Few-Shot Image Classification Meta-baseline: Exploring simple meta- learning for few-shot learning,

Reference 9

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Observation 5a65c782-206a-41aa-9360-385e4ec8b952 · outbound

This paper cites Cross attention network for few-shot classi- fication,.

Multi-Level Correlation Network For Few-Shot Image Classification Cross attention network for few-shot classi- fication,

Reference 10

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Observation d9dab77b-dc1e-43dc-aa37-c8ff94222f43 · outbound

This paper cites Few-shot learning with embed- ded class models and shot-free meta training,.

Multi-Level Correlation Network For Few-Shot Image Classification Few-shot learning with embed- ded class models and shot-free meta training,

Reference 11

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Observation 24a2bab8-8200-4156-bafb-be4b3c465d10 · outbound

This paper cites Learning self-similarity in space and time as generalized motion for video action recognition,.

Multi-Level Correlation Network For Few-Shot Image Classification Learning self-similarity in space and time as generalized motion for video action recognition,

Reference 12

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Source-reported events for the cited work

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Observation c61dd4dc-e1e3-42b9-99bf-ce6d187d46c9 · outbound

This paper cites Relational embedding for few-shot classifi- cation,.

Multi-Level Correlation Network For Few-Shot Image Classification Relational embedding for few-shot classifi- cation,

Reference 13

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Observation 4b8cc0b5-8a6b-4f43-aba4-c1b1d6fbdf58 · outbound

This paper cites Cbam: Convolutional block attention mod- ule,.

Multi-Level Correlation Network For Few-Shot Image Classification Cbam: Convolutional block attention mod- ule,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 7d0e49b1-e93e-48f9-95fa-334698e6901a · outbound

This paper cites Prototype mixture models for few-shot semantic segmentation,.

Multi-Level Correlation Network For Few-Shot Image Classification Prototype mixture models for few-shot semantic segmentation,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 5f004e32-862a-485f-81e5-05055de09923 · outbound

This paper cites Versa: Versatile and efficient few-shot learning,.

Multi-Level Correlation Network For Few-Shot Image Classification Versa: Versatile and efficient few-shot learning,

Reference 16

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation bf0adc66-d777-46b5-b9d0-a62ba7a743b4 · outbound

This paper cites Meta-learning with latent embedding opti- mization,.

Multi-Level Correlation Network For Few-Shot Image Classification Meta-learning with latent embedding opti- mization,

Reference 17

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 5d7dbc59-d818-4e05-a917-71de48602eea · outbound

This paper cites Boil: Towards representation change for few- shot learning,.

Multi-Level Correlation Network For Few-Shot Image Classification Boil: Towards representation change for few- shot learning,

Reference 18

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Observation 4ea0f098-2c04-47d9-be9e-1cde9246566f · outbound

This paper cites Meta-learning with differentiable closed-form solvers,.

Multi-Level Correlation Network For Few-Shot Image Classification Meta-learning with differentiable closed-form solvers,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 26f4d3c7-e6a2-41cf-ba22-d25c13b26264 · outbound

This paper cites Meta-transfer learning for few-shot learn- ing,.

Multi-Level Correlation Network For Few-Shot Image Classification Meta-transfer learning for few-shot learn- ing,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 8c671900-96a9-4bfa-a069-b5a2bbbd09c5 · outbound

This paper cites Learning to propagate labels: Transductive propagation network for few-shot learning,.

Multi-Level Correlation Network For Few-Shot Image Classification Learning to propagate labels: Transductive propagation network for few-shot learning,

Reference 21

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Observation c6dad133-0ab7-40df-bb9a-8de8395535dc · outbound

This paper cites Meta-learning with differentiable convex optimization,.

Multi-Level Correlation Network For Few-Shot Image Classification Meta-learning with differentiable convex optimization,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 145a5f9b-8323-4fd0-9795-b0186e213e34 · outbound

This paper cites Prototypical networks for few-shot learning,.

Multi-Level Correlation Network For Few-Shot Image Classification Prototypical networks for few-shot learning,

Reference 23

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 32c3c7e3-6a50-45fd-95c0-dafc5441a37e · outbound

This paper cites Rethinking few-shot image classification: a good embedding is all you need?,.

Multi-Level Correlation Network For Few-Shot Image Classification Rethinking few-shot image classification: a good embedding is all you need?,

Reference 24

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Observation f8b08f46-27f3-4248-aebb-b44addf7dde8 · outbound

This paper cites Mixture-based feature space learning for few-shot image classification,.

Multi-Level Correlation Network For Few-Shot Image Classification Mixture-based feature space learning for few-shot image classification,

Reference 25

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation e98e4dd0-34cb-4cd1-b2ba-9c7c4a3069f2 · outbound

This paper cites Charting the right manifold: Manifold mixup for few-shot learning,.

Multi-Level Correlation Network For Few-Shot Image Classification Charting the right manifold: Manifold mixup for few-shot learning,

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation e997636a-0acf-4325-bee2-a6d9482702dd · outbound

This paper cites Few-shot learning via embedding adaptation with set-to-set functions,.

Multi-Level Correlation Network For Few-Shot Image Classification Few-shot learning via embedding adaptation with set-to-set functions,

Reference 27

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Source-reported events for the cited work

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Observation 4a985f02-f560-4fe3-8c35-43b970443ec0 · outbound

This paper cites Deepemd: Few-shot image classification with differentiable earth mover’s distance and structured classifiers,.

Multi-Level Correlation Network For Few-Shot Image Classification Deepemd: Few-shot image classification with differentiable earth mover’s distance and structured classifiers,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 0df7ee66-ba01-4037-a308-157fb55c07ad · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization,.

Multi-Level Correlation Network For Few-Shot Image Classification Grad-cam: Visual explanations from deep networks via gradient-based localization,

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 87733856-40db-4ee1-9b7c-87bdc5441672 · outbound

This paper cites Different from [2], we use the ResNet12 architecture to extract feature without patches to reduce the computing complexity and avoid overfitting for few-shot classification.

Multi-Level Correlation Network For Few-Shot Image Classification Different from [2], we use the ResNet12 architecture to extract feature without patches to reduce the computing complexity and avoid overfitting for few-shot classification

Reference 30

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raw_fallback, observed 2026-08-11T22:45:46.005375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Pith citing papers

No inbound Pith citation observations are available.