Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:06:36.146152Z
Paper Citation Record · LEDGER
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation
As of 10 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2507.09299.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
54 of 54 outbound references displayed
- verified exact12
- verified fuzzy12
- unresolved28
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 90f5db2c-98eb-4642-943d-a9c9e9b27a52 · outbound
This paper cites Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Reference 1
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2f2a8cbe-401d-476b-9883-d3434cc41b6b · outbound
This paper cites & Lillicrap, T.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation & Lillicrap, T
Reference 2
- Resolution
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Source-reported events for the cited work
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Observation 1fd6384e-5b3e-4d15-90b9-feffbb63f639 · outbound
This paper cites Prototypical Networks for Few-shot Learning.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Prototypical Networks for Few-shot Learning
Reference 3
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 39d87660-af2b-4c57-bc3a-bb8b31c88bf7 · outbound
This paper cites & Haffner, P.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation & Haffner, P
Reference 4
- Resolution
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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.
Observation 0381af54-8405-40ab-a0bd-48ce97e744a1 · outbound
This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Reference 5
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 03a90c08-f078-4a12-9dfb-d77b8b2820a6 · outbound
This paper cites Attention Is All You Need.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Attention Is All You Need
Reference 6
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4e16f2e9-8306-4408-b085-e11b25b09bb3 · outbound
This paper cites CrossTransformers: spatially-aware few-shot transfer.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation CrossTransformers: spatially-aware few-shot transfer
Reference 7
- Resolution
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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.
Observation b3e25ef5-0f75-4fc8-a7b4-22401ab9d3b4 · outbound
This paper cites Meta-learning with differentiable closed-form solvers.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Meta-learning with differentiable closed-form solvers
Reference 8
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3ab1b583-7e5a-4a48-810b-1a9c91878579 · outbound
This paper cites The Caltech-UCSD Birds-200- 2011 Dataset.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation The Caltech-UCSD Birds-200- 2011 Dataset
Reference 9
- Resolution
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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.
Observation b8af3202-e7eb-4457-8da8-e959ff2e9abc · outbound
This paper cites TADAM: Task dependent adaptive metric for improved few-shot learning.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation TADAM: Task dependent adaptive metric for improved few-shot learning
Reference 10
- Resolution
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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.
Observation ca067580-af3b-4692-a80a-12dadc209739 · outbound
This paper cites Learning to Compare: Relation Network for Few-Shot Learning.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Learning to Compare: Relation Network for Few-Shot Learning
Reference 11
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d8bd7ad2-469d-4580-8dcd-44babce64f6e · outbound
This paper cites an unresolved cited work.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Unresolved cited work
Reference 12
- Resolution
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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.
Observation 448914db-8a0b-472e-941b-e83c99abc246 · outbound
This paper cites H., Shehata, M.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation H., Shehata, M
Reference 13
- Resolution
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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.
Observation 8a2b4ef8-f8fb-4036-83f5-997a7aa9a444 · outbound
This paper cites Deep Residual Learning for Image Recognition.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Deep Residual Learning for Image Recognition
Reference 14
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cd5d6def-5485-4a2b-b9ee-6accc9059e61 · outbound
This paper cites Densely Connected Convolutional Networks.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Densely Connected Convolutional Networks
Reference 15
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c446dab6-7a13-4d19-8bb9-fa1f57867a7d · outbound
This paper cites Wide Residual Networks.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Wide Residual Networks
Reference 16
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 62a7380e-927b-4915-99c7-1d7613da42a4 · outbound
This paper cites & Drummond, T.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation & Drummond, T
Reference 17
- Resolution
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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.
Observation baa09baf-b1ff-4bae-baec-ff6886f98d45 · outbound
This paper cites S., Chaudhari, P., Ravichandran, A.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation S., Chaudhari, P., Ravichandran, A
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:06:40.866079Z
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.
Observation 0b04e7d3-87c6-44ae-b7f0-33e66f6b8a60 · outbound
This paper cites On First-Order Meta-Learning Algorithms.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation On First-Order Meta-Learning Algorithms
Reference 19
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 26e65407-fe08-4e1b-bdf9-d475a7b14b59 · outbound
This paper cites Meta-SGD: Learning to Learn Quickly for Few-Shot Learning.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Meta-SGD: Learning to Learn Quickly for Few-Shot Learning
Reference 20
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 662b1771-1d36-4992-b6e9-417ec33f3d23 · outbound
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ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Meta-Learning with Differentiable Convex Optimization
Reference 21
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 098ac64f-3b22-4aeb-9da5-6e9524092a92 · outbound
This paper cites Meta-Learning for Semi-Supervised Few-Shot Classification.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Meta-Learning for Semi-Supervised Few-Shot Classification
Reference 22
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d1e55385-cafe-4410-8ffa-fe8a10236e98 · outbound
This paper cites & Monfardini, G.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation & Monfardini, G
Reference 23
- Resolution
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Source-reported events for the cited work
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Observation 7f482467-32af-49eb-80e3-a3097acc002f · outbound
This paper cites Few-Shot Learning with Graph Neural Networks.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Few-Shot Learning with Graph Neural Networks
Reference 24
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ef7f359a-c71d-46e5-8527-ed3b2a8a6ae2 · outbound
This paper cites & Salakhutdinov, R.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation & Salakhutdinov, R
Reference 25
- Resolution
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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.
Observation 757a9b2a-a1a8-48fe-bf2e-3ee49ca9764d · outbound
This paper cites Edge-labeling Graph Neural Network for Few-shot Learning.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Edge-labeling Graph Neural Network for Few-shot Learning
Reference 26
- Resolution
- verified exact
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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.
Observation a7992f02-eb61-4ed9-ab06-b3a7a362145c · outbound
This paper cites Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Reference 27
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e00e0e6c-b9c3-4797-8bf9-31a0bd9daec3 · outbound
This paper cites Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions
Reference 28
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f201ead1-cb04-43e5-9fa5-d5e1e4782f7f · outbound
This paper cites Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
Reference 29
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c829db2e-1a17-44d7-a160-d0495ee42b96 · outbound
This paper cites Few-Shot Learning Meets Transformer: Unified Query-Support Transformers for Few-Shot Classification.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Few-Shot Learning Meets Transformer: Unified Query-Support Transformers for Few-Shot Classification
Reference 30
- Resolution
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Source-reported events for the cited work
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Observation ac0bc42d-0412-450e-a190-3c9a07f3894e · outbound
This paper cites SgVA-CLIP: Semantic-guided Visual Adapting of Vision-Language Models for Few-shot Image Classification.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation SgVA-CLIP: Semantic-guided Visual Adapting of Vision-Language Models for Few-shot Image Classification
Reference 31
- Resolution
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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.
Observation 549facea-53c4-4949-aecd-24e75dfbcdfb · outbound
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ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Learning Transferable Visual Models From Natural Language Supervision
Reference 32
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 02754b74-4417-4d6c-9eb8-31a0afb277cf · outbound
This paper cites ImageNet-21K Pretraining for the Masses.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation ImageNet-21K Pretraining for the Masses
Reference 33
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 244b429e-9cf7-4751-bd78-67dfa73fa22a · outbound
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ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation A Simple Neural Attentive Meta-Learner
Reference 34
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ff48c22-8fb9-4b35-b8fd-1038cfaf7067 · outbound
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ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Meta Networks
Reference 35
- Resolution
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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.
Observation 5837ff53-f436-4f77-bb19-bd229b1f0ff2 · outbound
This paper cites Laplacian Regularized Few-Shot Learning.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Laplacian Regularized Few-Shot Learning
Reference 36
- Resolution
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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.
Observation e5568795-e6dd-4e5e-988f-2f535c047dd7 · outbound
This paper cites Generative Adversarial Networks.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Generative Adversarial Networks
Reference 37
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 994dafd6-94e2-4098-a98e-902d56fb78ca · outbound
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ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Auto-Encoding Variational Bayes
Reference 38
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 84729a2d-a8ed-4e2a-bf58-982146c7a089 · outbound
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ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Unresolved cited work
Reference 39
- Resolution
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Source-reported events for the cited work
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Observation b6d5e653-bc9c-4cb6-a528-5adaf3513d13 · outbound
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ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning
Reference 40
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fbf3aac8-415d-473e-87bc-8eb6509dada8 · outbound
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ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation & Salakhutdinov, R
Reference 41
- Resolution
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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.
Observation 37db4d11-872b-4018-a897-0aaf9901a56c · outbound
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ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation & Friedman, J
Reference 42
- Resolution
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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.
Observation 9ba46b02-0d8c-42d2-9607-511437a17ed0 · outbound
This paper cites & Courville, A.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation & Courville, A
Reference 43
- Resolution
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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.
Observation 284784a5-0be5-425d-a7c4-3088dfff3f13 · outbound
This paper cites Decoupled Weight Decay Regularization.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Decoupled Weight Decay Regularization
Reference 44
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 12e2afe5-65ec-4ed4-846e-95de370837d8 · outbound
This paper cites Bag of Tricks for Image Classification with Convolutional Neural Networks.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Bag of Tricks for Image Classification with Convolutional Neural Networks
Reference 45
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 118818b8-8964-4cdc-8167-691df3eb40e9 · outbound
This paper cites Context-Aware Meta-Learning.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Context-Aware Meta-Learning
Reference 46
- Resolution
- verified exact
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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.
Observation 0624a4b2-94fa-405b-92b2-53fc6023dac1 · outbound
This paper cites Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference
Reference 47
- Resolution
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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.
Observation cc91f58b-6380-4d48-ba4d-ae533dfb3c8f · outbound
This paper cites Transductive Decoupled Variational Inference for Few-Shot Classification.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Transductive Decoupled Variational Inference for Few-Shot Classification
Reference 48
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5f4bdb57-3c00-446d-a3f0-4e255f68fa06 · outbound
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ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation & Korman, S
Reference 49
- Resolution
- verified fuzzy
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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.
Observation 8e559829-4d21-484f-89d5-8087612ba28a · outbound
This paper cites The Balanced-Pairwise-Affinities Feature Transform.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation The Balanced-Pairwise-Affinities Feature Transform
Reference 50
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T18:06:37.428911Z
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.
Observation a88e5c97-fe69-48c0-8287-59c165bc7880 · outbound
This paper cites Squeezing Backbone Feature Distributions to the Max for Efficient Few-Shot Learning.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Squeezing Backbone Feature Distributions to the Max for Efficient Few-Shot Learning
Reference 51
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T18:06:37.184146Z
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.
Observation cbb503bd-9b58-4c65-8caa-8493027e6df8 · outbound
This paper cites Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification
Reference 52
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T18:06:36.883930Z
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.
Observation d65ba4a2-f416-407f-a793-fd936a29a3f8 · outbound
This paper cites Task Augmentation by Rotating for Meta-Learning.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Task Augmentation by Rotating for Meta-Learning
Reference 53
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- verified exact
- local_arxiv, observed 2026-08-06T18:06:36.617915Z
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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation aac07d08-cdc8-49e1-bc7a-862eab9b8f5b · outbound
This paper cites Generalized Adaptation for Few-Shot Learning.
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Generalized Adaptation for Few-Shot Learning
Reference 54
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T18:06:36.366309Z
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.
Pith citing papers
No inbound Pith citation observations are available.