Paper Citation Record · LEDGER

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training

As of 21 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2506.17499.

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

pith.paper-citation-record.v1
2506.17499 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:14:23.188652Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation db5a2cf9-bb36-4d0b-a7af-d5979e30a39d · outbound

This paper cites A Closer Look at Few-shot Classification.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training A Closer Look at Few-shot Classification

Reference 1

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Observation 776be7c2-e2c0-4561-9360-bff3e50cb970 · outbound

This paper cites Metaaudio: A few-shot audio classification benchmark,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Metaaudio: A few-shot audio classification benchmark,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:14:23.801348Z

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Observation 06319542-8801-48cd-b3a6-436754e39025 · outbound

This paper cites Few- shot continual learning for audio classification,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Few- shot continual learning for audio classification,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:14:23.787653Z

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Observation ba4f6be8-1481-4028-a788-3b92cc1ce5ce · outbound

This paper cites Few-shot class-incremental audio classification via discriminative prototype learning,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Few-shot class-incremental audio classification via discriminative prototype learning,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:14:23.774163Z

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Observation 01f3ed89-7922-473c-b06b-5bd2fd162fae · outbound

This paper cites Few-shot audio classification with attentional graph neural networks.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Few-shot audio classification with attentional graph neural networks

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:14:23.759577Z

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Observation ff8c75f8-47f7-43bd-b413-50b8975cd7b7 · outbound

This paper cites Learning from taxonomy: Multi- label few-shot classification for everyday sound recognition,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Learning from taxonomy: Multi- label few-shot classification for everyday sound recognition,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:14:23.747163Z

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Observation 1ee95384-0e13-4f08-a13c-d6dc836dc6b9 · outbound

This paper cites Few-shot sound event detection,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Few-shot sound event detection,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:14:23.733948Z

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Observation f4d6cc10-fdf8-4412-9b8b-600a45e10771 · outbound

This paper cites Active few-shot learning for sound event detection.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Active few-shot learning for sound event detection

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:14:23.708512Z

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Observation 00e5a5cc-7ef4-4ff3-b210-9992dd73509c · outbound

This paper cites Few-shot acoustic event detection via meta learning,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Few-shot acoustic event detection via meta learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:14:23.721344Z

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Observation 600d615e-71f8-42b8-bd8a-f91da840dbb2 · outbound

This paper cites Few-shot bioacoustic event detection at the DCASE 2022 challenge.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Few-shot bioacoustic event detection at the DCASE 2022 challenge

Reference 11

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Observation 288558d6-1e0d-42e2-bd60-180516ea7efc · outbound

This paper cites Overview of birdclef 2022: Endangered bird species recognition in soundscape recordings.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Overview of birdclef 2022: Endangered bird species recognition in soundscape recordings

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:14:23.694360Z

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Observation 02274f55-852a-45b4-a0a7-cfcb34d86ef6 · outbound

This paper cites Few-shot musical source separation,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Few-shot musical source separation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:14:23.679691Z

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Observation 9f011020-87f9-4e3e-8070-fc5514efc3f4 · outbound

This paper cites Leveraging Hierarchical Structures for Few-Shot Musical Instrument Recognition.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Leveraging Hierarchical Structures for Few-Shot Musical Instrument Recognition

Reference 14

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Observation 3a56509f-db88-4108-86df-39d358237271 · outbound

This paper cites Lc-protonets: Multi- label few-shot learning for world music audio tagging,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Lc-protonets: Multi- label few-shot learning for world music audio tagging,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:14:23.666026Z

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Observation 94fe39d4-1fcc-40df-898f-81a57e345eee · outbound

This paper cites Few-Shot Drum Transcription in Polyphonic Music.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Few-Shot Drum Transcription in Polyphonic Music

Reference 16

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Observation 478c0a08-1816-4218-8559-b1cff869ff63 · outbound

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

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Prototypical networks for few-shot learning,

Reference 17

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Observation f459a6ae-2b9a-40ff-9289-fa38f8c199cc · outbound

This paper cites Cross Attention Network for Few-shot Classification.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Cross Attention Network for Few-shot Classification

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-15T19:14:23.437245Z

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Observation 257b3910-cc2e-489a-8662-a3c2d1f38e8c · outbound

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

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Learning to compare: Relation network for few-shot learning,

Reference 19

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Observation d5145e30-789a-40f8-af33-6ace03823cb5 · outbound

This paper cites Matching net- works for one shot learning,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Matching net- works for one shot learning,

Reference 20

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Observation 67a2ff69-274a-432e-b9c5-e1e55f0c4a4d · outbound

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

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Model-agnostic meta-learning for fast adaptation of deep networks,

Reference 21

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Observation 78df7ea0-e26a-4864-8dc0-b64972d8e17f · outbound

This paper cites Meta-SGD: Learning to Learn Quickly for Few-Shot Learning.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Meta-SGD: Learning to Learn Quickly for Few-Shot Learning

Reference 22

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Observation 5132297a-187a-427d-ba81-613e9023afa7 · outbound

This paper cites Meta-curvature,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Meta-curvature,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:14:23.613397Z

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Observation 347d18ee-056d-4dc5-ac18-133847043509 · outbound

This paper cites Episodic fine-tuning prototypical networks for optimization-based few-shot learning: Application to audio classification,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Episodic fine-tuning prototypical networks for optimization-based few-shot learning: Application to audio classification,

Reference 24

Resolution: verified exact; raw_fallback, observed 2026-08-15T19:14:23.403978Z

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Observation 1ebec4f8-efe3-40fa-8480-461343b48924 · outbound

This paper cites Adapted deep embeddings: A synthesis of methods for k-shot inductive transfer learning,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Adapted deep embeddings: A synthesis of methods for k-shot inductive transfer learning,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:14:23.593136Z

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Observation 0c5ea368-8f24-4cce-beb2-00d13a16c260 · outbound

This paper cites Adaptive Prototypical Networks.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Adaptive Prototypical Networks

Reference 26

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This paper cites Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples

Reference 27

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Observation 76a29e30-3b2f-452f-aafc-9d927d9a0b8f · outbound

This paper cites A hybrid approach with optimization and metric-based meta-learner for few-shot learning,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training A hybrid approach with optimization and metric-based meta-learner for few-shot learning,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:14:23.578652Z

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Observation f49eb7f7-da32-4c31-9a65-06ba978eda24 · outbound

This paper cites Esc: Dataset for environmental sound classification,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Esc: Dataset for environmental sound classification,

Reference 29

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Observation d69f84c4-ae76-49d5-aee3-6fe991d99ed0 · outbound

This paper cites Deep convolutional networks on the pitch spiral for musical instrument recognition.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Deep convolutional networks on the pitch spiral for musical instrument recognition

Reference 31

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Observation 9a275942-a1d4-4304-81c2-8fa24279e3c7 · outbound

This paper cites Learning to match transient sound events using attentional similarity for few- shot sound recognition,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Learning to match transient sound events using attentional similarity for few- shot sound recognition,

Reference 32

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Observation eae77a08-9b08-482f-8c0b-cf749114e231 · outbound

This paper cites Nearest neighbor pattern classification,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Nearest neighbor pattern classification,

Reference 33

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This paper cites Rectified linear units improve restricted boltz- mann machines,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Rectified linear units improve restricted boltz- mann machines,

Reference 34

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Observation 1ba0747b-d4a9-4a6f-b07a-3007ab63392d · outbound

This paper cites Network In Network.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Network In Network

Reference 35

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Observation 7a3e2cea-2bc7-4a70-8e84-f1aab3181a2d · outbound

This paper cites Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition

Reference 36

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This paper cites Medleydb: A multitrack dataset for annotation-intensive mir research,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Medleydb: A multitrack dataset for annotation-intensive mir research,

Reference 37

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Observation 514e79e2-895c-4195-9d14-115b84ad2211 · outbound

This paper cites Musical instrument recognition based on class pairwise feature selection,.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training Musical instrument recognition based on class pairwise feature selection,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:14:23.517071Z

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Observation 3ff113c5-5d5a-4f68-9916-aa35a0c3f427 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 39

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This paper cites learn2learn: A Library for Meta-Learning Research.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training learn2learn: A Library for Meta-Learning Research

Reference 40

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Observation 7f5b7d98-294e-4c69-895f-a96733ef1da0 · outbound

This paper cites librosa: Audio and music signal analysis in python.

Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training librosa: Audio and music signal analysis in python

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T19:14:23.188652Z

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