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Paper Citation Record · LEDGER

Slot Attention-based Feature Filtering for Few-Shot Learning

As of 10 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2508.09699.

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

pith.paper-citation-record.v1
2508.09699 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:56:13.842065Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

41 of 41 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cc3f91a1-4b9e-4b4c-bc55-189f11f910ec · outbound

This paper cites Uncertainty-aware selecting for an ensem- ble of deep food recognition models.

Slot Attention-based Feature Filtering for Few-Shot Learning Uncertainty-aware selecting for an ensem- ble of deep food recognition models

Reference 1

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Observation ad4c00f1-1b71-4c35-9d0e-b6362a5c05b3 · outbound

This paper cites Frozen feature augmentation for few- shot image classification.

Slot Attention-based Feature Filtering for Few-Shot Learning Frozen feature augmentation for few- shot image classification

Reference 2

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Observation 6cec752e-b781-4826-ba63-15150a356667 · outbound

This paper cites Henriques, Philip H.

Slot Attention-based Feature Filtering for Few-Shot Learning Henriques, Philip H

Reference 3

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Observation 3ef29c40-3128-41fd-b27b-5ab7a2ac6c14 · outbound

This paper cites Image deformation meta-networks for one-shot learning.

Slot Attention-based Feature Filtering for Few-Shot Learning Image deformation meta-networks for one-shot learning

Reference 4

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Observation 0678e3d4-ad2a-4c6f-9dbb-ceaeb50cfaef · outbound

This paper cites Pareto self-supervised training for few-shot learning.

Slot Attention-based Feature Filtering for Few-Shot Learning Pareto self-supervised training for few-shot learning

Reference 5

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Observation 315c3389-5031-4114-afd2-6b2927e92ef2 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Slot Attention-based Feature Filtering for Few-Shot Learning An image is worth 16x16 words: Transformers for image recognition at scale

Reference 6

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Observation 968a6762-5ac4-4f0e-bb44-7ff695dc6e61 · outbound

This paper cites Adaptive slot attention: Object discovery with dynamic slot number.

Slot Attention-based Feature Filtering for Few-Shot Learning Adaptive slot attention: Object discovery with dynamic slot number

Reference 7

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Observation a7ab9cb3-0b27-4ca9-b8e4-3ff3c5e58202 · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks.

Slot Attention-based Feature Filtering for Few-Shot Learning Model-agnostic meta-learning for fast adaptation of deep networks

Reference 8

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Observation f3f74059-d95f-460e-b2da-a7151d53e1df · outbound

This paper cites Class-aware patch em- bedding adaptation for few-shot image classification.

Slot Attention-based Feature Filtering for Few-Shot Learning Class-aware patch em- bedding adaptation for few-shot image classification

Reference 9

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Observation 215d303b-15d7-43ff-a4d5-95dbd0447ccf · outbound

This paper cites Rethinking generalization in few- shot classification.

Slot Attention-based Feature Filtering for Few-Shot Learning Rethinking generalization in few- shot classification

Reference 10

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Observation 3a05dc6b-7294-49e9-9aa4-bf62583a14a0 · outbound

This paper cites Relational embedding for few-shot clas- sification.

Slot Attention-based Feature Filtering for Few-Shot Learning Relational embedding for few-shot clas- sification

Reference 11

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Observation 2a9119d0-77db-4507-9e6b-b221b97fc560 · outbound

This paper cites Few-shot learning for fea- ture selection with hilbert-schmidt independence cri- terion.

Slot Attention-based Feature Filtering for Few-Shot Learning Few-shot learning for fea- ture selection with hilbert-schmidt independence cri- terion

Reference 12

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Observation 0bd41765-a576-424c-a91e-647d698aa225 · outbound

This paper cites Clustered-patch element connec- tion for few-shot learning.

Slot Attention-based Feature Filtering for Few-Shot Learning Clustered-patch element connec- tion for few-shot learning

Reference 13

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Observation 464cd291-3390-4894-b23f-e123be9497ae · outbound

This paper cites Guided slot attention for unsupervised video object segmentation.

Slot Attention-based Feature Filtering for Few-Shot Learning Guided slot attention for unsupervised video object segmentation

Reference 14

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Source-reported events for the cited work

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Observation 407882a0-2d7d-4991-b924-2f9fc2fcb21f · outbound

This paper cites An adaptive plug-and-play network for few-shot learning.

Slot Attention-based Feature Filtering for Few-Shot Learning An adaptive plug-and-play network for few-shot learning

Reference 15

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Observation df15ce3f-4d74-48c0-9010-aa3610cc890c · outbound

This paper cites SCOUTER: slot attention-based classifier for explain- able image recognition.

Slot Attention-based Feature Filtering for Few-Shot Learning SCOUTER: slot attention-based classifier for explain- able image recognition

Reference 16

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Observation 18b893ce-dce4-422f-955a-1d00dc968a0a · outbound

This paper cites Sabernet: Self-attention based effective relation net- work for few-shot learning.

Slot Attention-based Feature Filtering for Few-Shot Learning Sabernet: Self-attention based effective relation net- work for few-shot learning

Reference 17

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Observation cfd28ed9-bcaa-45af-a6d0-03fa99dbb156 · outbound

This paper cites Learning a few-shot embedding model with contrastive learning.

Slot Attention-based Feature Filtering for Few-Shot Learning Learning a few-shot embedding model with contrastive learning

Reference 18

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Observation f6487a58-b807-4acd-828a-9ded42ae77bb · outbound

This paper cites Object-centric learning with slot attention.

Slot Attention-based Feature Filtering for Few-Shot Learning Object-centric learning with slot attention

Reference 19

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Observation 38e70ffe-bad3-427d-967a-6b90987b6928 · outbound

This paper cites Bi-directional task-guided network for few-shot fine- grained image classification.

Slot Attention-based Feature Filtering for Few-Shot Learning Bi-directional task-guided network for few-shot fine- grained image classification

Reference 20

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Observation ae1d7262-4a1b-4977-97ea-129789197dae · outbound

This paper cites LaFTer: Label-free tuning of zero-shot classifier using language and unlabeled image collections.

Slot Attention-based Feature Filtering for Few-Shot Learning LaFTer: Label-free tuning of zero-shot classifier using language and unlabeled image collections

Reference 21

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Observation 5b4f50c7-f0e3-4d39-a513-cad6936b8f98 · outbound

This paper cites On First-Order Meta-Learning Algorithms.

Slot Attention-based Feature Filtering for Few-Shot Learning On First-Order Meta-Learning Algorithms

Reference 22

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Source-reported events for the cited work

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Observation 35828dd1-aa6f-447c-bd61-c4714fd6b886 · outbound

This paper cites Oreshkin, Pau Rodr´ıguez L´opez, and Alexan- dre Lacoste.

Slot Attention-based Feature Filtering for Few-Shot Learning Oreshkin, Pau Rodr´ıguez L´opez, and Alexan- dre Lacoste

Reference 23

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Observation 33930420-180b-41ea-9668-bcecd1a54333 · outbound

This paper cites Transductive few-shot classification on the oblique manifold.

Slot Attention-based Feature Filtering for Few-Shot Learning Transductive few-shot classification on the oblique manifold

Reference 24

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Observation da6eb04a-b5c3-4c51-a6f0-04398f5333b0 · outbound

This paper cites Tenenbaum, Hugo Larochelle, and Richard S.

Slot Attention-based Feature Filtering for Few-Shot Learning Tenenbaum, Hugo Larochelle, and Richard S

Reference 25

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Observation cd65faf4-5b44-44f4-8705-6319d9b47640 · outbound

This paper cites Proto- typical networks for few-shot learning.

Slot Attention-based Feature Filtering for Few-Shot Learning Proto- typical networks for few-shot learning

Reference 26

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Observation 2f3dec42-c537-45e9-a927-cefde5984a99 · outbound

This paper cites Label propagation for zero-shot classification with vision-language models.

Slot Attention-based Feature Filtering for Few-Shot Learning Label propagation for zero-shot classification with vision-language models

Reference 27

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Observation 57f660e8-2ccb-4d0e-a8f2-40272897462b · outbound

This paper cites Meta-transfer learning for few-shot learning.

Slot Attention-based Feature Filtering for Few-Shot Learning Meta-transfer learning for few-shot learning

Reference 28

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Observation 394f72a7-3132-47fa-8322-f1e9ce03a4d1 · outbound

This paper cites Matching networks for one shot learning.

Slot Attention-based Feature Filtering for Few-Shot Learning Matching networks for one shot learning

Reference 29

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Observation 9a22139d-94a9-4b2a-8fe5-0e991401fc1a · outbound

This paper cites Background-filtering feature-enhanced graph neural networks for few-shot learning.

Slot Attention-based Feature Filtering for Few-Shot Learning Background-filtering feature-enhanced graph neural networks for few-shot learning

Reference 30

Resolution
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Observation b48443f5-eb41-4b8d-8f27-723b48390b24 · outbound

This paper cites Focus your attention when few-shot classification.

Slot Attention-based Feature Filtering for Few-Shot Learning Focus your attention when few-shot classification

Reference 31

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Observation c2d38406-24b5-4b45-83fe-2c1f6aae058f · outbound

This paper cites Distribu- tional modeling on a diet: One-shot word learning from text only.

Slot Attention-based Feature Filtering for Few-Shot Learning Distribu- tional modeling on a diet: One-shot word learning from text only

Reference 32

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Source-reported events for the cited work

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Observation 5ffd6195-b5f4-478d-8f69-de03666dea09 · outbound

This paper cites Task-aware part mining network for few- shot learning.

Slot Attention-based Feature Filtering for Few-Shot Learning Task-aware part mining network for few- shot learning

Reference 33

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Source-reported events for the cited work

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Observation 37cb0d31-aa12-4f93-8f01-474baf0944f0 · outbound

This paper cites Learning dynamic alignment via meta- filter for few-shot learning.

Slot Attention-based Feature Filtering for Few-Shot Learning Learning dynamic alignment via meta- filter for few-shot learning

Reference 34

Resolution
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Source-reported events for the cited work

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Observation 9af048e1-8abb-4f59-a224-0f85545e510f · outbound

This paper cites A dual attention network with semantic embedding for few-shot learning.

Slot Attention-based Feature Filtering for Few-Shot Learning A dual attention network with semantic embedding for few-shot learning

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:56:14.800472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T20:56:13.310534Z digest=sha256:96557e7724b153920a465df37a849006f732413fd4dbf2f82b884a43166c90e7

Observation ff80cdf2-57b9-41f5-aa47-95543f732d64 · outbound

This paper cites Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions.

Slot Attention-based Feature Filtering for Few-Shot Learning Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-05T20:56:13.377043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:56:13.377043Z digest=sha256:482fdcbe20cd3c0b4c64c92ae5dcee93056dc4d3d76e0381d71ced4c8fd77e76

Observation 29e0885f-00f7-428c-8541-d6f469182a49 · outbound

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

Slot Attention-based Feature Filtering for Few-Shot Learning Few-shot learning via embedding adaptation with set-to-set functions

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:56:14.692175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T20:56:13.466368Z digest=sha256:57720e77435f731f9a4a7fa818d661436e72cd087a3b23247fdc54d255034892

Observation 6b7f3a58-f4bb-4daf-91ca-4ceeaabdf966 · outbound

This paper cites Simple semantic-aided few-shot learning.

Slot Attention-based Feature Filtering for Few-Shot Learning Simple semantic-aided few-shot learning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:56:14.540608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T20:56:13.539677Z digest=sha256:0657ce1b77a961024f235b8da513c132cd94a45f28401db93809b01b89363677

Observation 5ef8781a-c3f2-4083-9ed2-3d828b7e69ee · outbound

This paper cites Hospedales.

Slot Attention-based Feature Filtering for Few-Shot Learning Hospedales

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:56:14.425467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T20:56:13.626915Z digest=sha256:b60f5f973b4ec6967372049dea16bdc99b67698d7ab85d02056b59f9348cb759

Observation 1db16e98-b44c-42a8-bda5-81f4c4dc4800 · outbound

This paper cites Few-shot learning based on prototype rectification with a self-attention mechanism.

Slot Attention-based Feature Filtering for Few-Shot Learning Few-shot learning based on prototype rectification with a self-attention mechanism

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:56:14.248320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T20:56:13.735504Z digest=sha256:065cf0b6cb5c8154298de4884a20c1f1e1f43513b51fd556e663bd6a88bdbd50

Observation 5e5746c9-7dbb-41ac-ae1a-4e0acfb994eb · outbound

This paper cites Yuille, and Tao Kong.

Slot Attention-based Feature Filtering for Few-Shot Learning Yuille, and Tao Kong

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:56:14.071433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T20:56:13.842065Z digest=sha256:f9af1482e09992803ed44ef793aedfa1d1b5a0be6f821a786e6db34e69efcb6c

Pith citing papers

No inbound Pith citation observations are available.