Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T15:30:27.730403Z
Paper Citation Record · LEDGER
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning
As of 22 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 1 inbound Pith citation observation for arXiv:2412.11017.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-27T10:39:37.920953Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T08:57:47.662538Z
Reference resolution
68 of 68 outbound references displayed
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 42a0803e-ce0e-436a-b25c-64b1db89f48e · outbound
This paper cites iCaRL: Incremental classifier and representation learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning iCaRL: Incremental classifier and representation learning,
Reference 1
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 707d4901-eefb-4b87-9143-2bf9c2d39999 · outbound
This paper cites Learning a unified classifier incrementally via rebalancing,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Learning a unified classifier incrementally via rebalancing,
Reference 3
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 0cc6babd-7980-4299-8e47-7bc4c5f6c267 · outbound
This paper cites Few-shot class-incremental learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Few-shot class-incremental learning,
Reference 4
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 7058ac37-b0c9-4d2e-978e-982fb3993fb4 · outbound
This paper cites Distilling the Knowledge in a Neural Network.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Distilling the Knowledge in a Neural Network
Reference 5
- Resolution
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Source-reported events for the cited work
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Observation 8d3797cb-e906-4073-9f60-9b3237485664 · outbound
This paper cites Relational knowledge distilla- tion,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Relational knowledge distilla- tion,
Reference 6
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation bbcf462b-0184-4d7d-8ba8-9c5c870f51a4 · outbound
This paper cites Few- shot class-incremental learning via class-aware bilateral distillation,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Few- shot class-incremental learning via class-aware bilateral distillation,
Reference 7
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 38abc1dd-59ea-49b8-9008-351ade77f6b7 · outbound
This paper cites Few- shot class-incremental learning via relation knowledge distillation,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Few- shot class-incremental learning via relation knowledge distillation,
Reference 8
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 36dc08f3-e0d4-4853-9233-a9dacc51b22d · outbound
This paper cites Optimization as a model for few-shot learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Optimization as a model for few-shot learning,
Reference 9
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation fee22476-2075-44ec-b8c2-be2f91146499 · outbound
This paper cites Matching networks for one shot learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Matching networks for one 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 2026-08-21T06:32:19.484+00:00.
Observation f9594a29-d708-4358-b421-3043bd1c8393 · outbound
This paper cites Model-agnostic meta-learning for fast adaptation of deep networks,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Model-agnostic meta-learning for fast adaptation of deep networks,
Reference 11
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 9f76bc12-d232-4161-a224-59b444da7f45 · outbound
This paper cites Prototypical networks for few- shot learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Prototypical networks for few- shot learning,
Reference 12
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 0113bc63-4439-40f6-8eb1-724ac679439e · outbound
This paper cites Meta-Learning with Latent Embedding Optimization.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Meta-Learning with Latent Embedding Optimization
Reference 13
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0bc3556d-80d0-4fdb-b2a3-4201bddf2563 · outbound
This paper cites Learning to compare: Relation network for few-shot learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Learning to compare: Relation network for few-shot learning,
Reference 14
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation a6fa65cf-6b25-4b32-80b9-cd481ff6888e · outbound
This paper cites Dynamic few-shot visual learning without forgetting,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Dynamic few-shot visual learning without forgetting,
Reference 15
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 372b2d75-8cc4-4aed-adaf-1da85f9fafc9 · outbound
This paper cites Cross attention network for few-shot classification,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Cross attention network for few-shot classification,
Reference 16
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f83ffafb-584e-4496-9b33-219f66c66724 · outbound
This paper cites Re- thinking few-shot image classification: A good embedding is all you need?,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Re- thinking few-shot image classification: A good embedding is all you need?,
Reference 17
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 9bd23672-d0ac-4146-963f-d4013b685df4 · outbound
This paper cites Few-shot learning via embedding adaptation with set-to-set functions,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Few-shot learning via embedding adaptation with set-to-set functions,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:28.765591Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 66323375-4914-42ca-b1d5-80bf1d9a5558 · outbound
This paper cites Learning adaptive classifiers synthesis for generalized few-shot learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Learning adaptive classifiers synthesis for generalized few-shot learning,
Reference 19
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 33de31ef-6fd0-4e6b-a617-794409f69682 · outbound
This paper cites Hybrid graph neural networks for few-shot learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Hybrid graph neural networks for few-shot learning,
Reference 20
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 2043925f-137c-4ff5-98d3-a6a86b25b1cf · outbound
This paper cites Few-shot learning with noisy labels,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Few-shot learning with noisy labels,
Reference 21
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation bca32774-dc77-4784-93ba-6fc1a8b97b0f · outbound
This paper cites A closer look at few-shot classification,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning A closer look at few-shot classification,
Reference 22
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 7fe28106-beed-40c3-979c-d0a771374964 · outbound
This paper cites Self-promoted prototype refinement for few-shot class-incremental learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Self-promoted prototype refinement for few-shot class-incremental learning,
Reference 23
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 4d82ff07-814e-46ed-8cd6-36d20b4f1024 · outbound
This paper cites S3c: Self-supervised stochastic classifiers for few-shot class-incremental learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning S3c: Self-supervised stochastic classifiers for few-shot class-incremental learning,
Reference 24
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 63b1c30b-48e5-435e-ba0c-5925e30a413d · outbound
This paper cites Mo- boo: Memory-boosted vision transformer for class-incremental learn- ing,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Mo- boo: Memory-boosted vision transformer for class-incremental learn- ing,
Reference 25
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 53a35bb9-df57-4503-a837-261f0f27db04 · outbound
This paper cites Few-shot class incremental learning leveraging self- supervised features,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Few-shot class incremental learning leveraging self- supervised features,
Reference 26
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation ee7ca654-cda7-4cea-83e7-8051a9904dae · outbound
This paper cites Uncertainty-aware distillation for semi-supervised few-shot class-incremental learning.,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Uncertainty-aware distillation for semi-supervised few-shot class-incremental learning.,
Reference 27
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 9cd6b979-5f75-4c22-9783-0173b54f92dc · outbound
This paper cites Lcsl: Long- tailed classification via self-labeling,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Lcsl: Long- tailed classification via self-labeling,
Reference 28
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation b99eed74-2863-42ad-8ef6-b0306d1b567a · outbound
This paper cites Analogical learning-based few-shot class-incremental learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Analogical learning-based few-shot class-incremental learning,
Reference 29
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation fc182ee2-c977-4ae9-b7ab-ddba8afa2cf0 · outbound
This paper cites Memorizing complementation network for few-shot class-incremental learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Memorizing complementation network for few-shot class-incremental learning,
Reference 30
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f67dd1e9-bb4d-4383-9319-2d517d49d79e · outbound
This paper cites Reformulating classification as image-class matching for class incremental learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Reformulating classification as image-class matching for class incremental learning,
Reference 31
- Resolution
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Source-reported events for the cited work
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Observation 509026d2-cc4f-432d-822e-944575cefda0 · outbound
This paper cites Multimodal parameter-efficient few-shot class incremental learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Multimodal parameter-efficient few-shot class incremental learning,
Reference 32
- Resolution
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Source-reported events for the cited work
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Observation d5e175cb-5f83-4adb-af99-8f78f8acb841 · outbound
This paper cites Representation robustness and feature expansion for exemplar-free class-incremental learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Representation robustness and feature expansion for exemplar-free class-incremental learning,
Reference 33
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 49a5b189-b75d-495d-a277-ad30e9268b34 · outbound
This paper cites Warping the space: Weight space rotation for class-incremental few-shot learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Warping the space: Weight space rotation for class-incremental few-shot learning,
Reference 34
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation c923b168-99aa-449d-b749-9d4ade397dfb · outbound
This paper cites Class incremental learning with less forgetting direction and equilibrium point,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Class incremental learning with less forgetting direction and equilibrium point,
Reference 35
- Resolution
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Source-reported events for the cited work
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Observation f68c93dd-79a0-43a9-acf6-16f49a7dcdf1 · outbound
This paper cites Few-shot incre- mental learning with continually evolved classifiers,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Few-shot incre- mental learning with continually evolved classifiers,
Reference 36
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 2b5036d2-bed4-44d5-92ac-08502e197ea2 · outbound
This paper cites Improved continually evolved clas- sifiers for few-shot class-incremental learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Improved continually evolved clas- sifiers for few-shot class-incremental learning,
Reference 37
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation dcc8636b-d3fa-41e6-8289-bc8bb1bb2560 · outbound
This paper cites For- ward compatible few-shot class-incremental learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning For- ward compatible few-shot class-incremental learning,
Reference 38
- Resolution
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Source-reported events for the cited work
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Observation ef66c866-04b0-4f1a-b324-af9e152f7842 · outbound
This paper cites Mics: Midpoint interpolation to learn compact and separated representations for few- shot class-incremental learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Mics: Midpoint interpolation to learn compact and separated representations for few- shot class-incremental learning,
Reference 39
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 0abe75e5-5576-42e8-857f-91311459a68c · outbound
This paper cites mixup: Beyond Empirical Risk Minimization.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning mixup: Beyond Empirical Risk Minimization
Reference 40
- Resolution
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Source-reported events for the cited work
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Observation dc913ed5-c546-47d9-9f57-1a0bf33248b6 · outbound
This paper cites Knowledge distillation: A survey,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Knowledge distillation: A survey,
Reference 41
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 24345d64-dd9d-4842-aa2c-ae383c521fa1 · outbound
This paper cites Do deep nets really need to be deep?,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Do deep nets really need to be deep?,
Reference 42
- Resolution
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Source-reported events for the cited work
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Observation 96779447-a74e-4016-93c6-7b74e197cd8b · outbound
This paper cites Paraphrasing complex network: Network compression via factor transfer,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Paraphrasing complex network: Network compression via factor transfer,
Reference 43
- Resolution
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Source-reported events for the cited work
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Observation 443854cf-a40c-412a-a3fc-9752fa83aeb1 · outbound
This paper cites Improved knowledge distillation via teacher assis- tant,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Improved knowledge distillation via teacher assis- tant,
Reference 44
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation 73aa83a8-7a3e-4b1d-81dd-2aba601d691b · outbound
This paper cites Like What You Like: Knowledge Distill via Neuron Selectivity Transfer.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Like What You Like: Knowledge Distill via Neuron Selectivity Transfer
Reference 45
- Resolution
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Source-reported events for the cited work
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Observation f3b54b1a-6e55-42e3-bf1a-8a5b62208b92 · outbound
This paper cites Paying more attention to attention: improving the performance of convolutional neural networks via atten- tion transfer,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Paying more attention to attention: improving the performance of convolutional neural networks via atten- tion transfer,
Reference 46
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation fb894c10-06e2-4966-81f6-a2877e746619 · outbound
This paper cites Varia- tional information distillation for knowledge transfer,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Varia- tional information distillation for knowledge transfer,
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:28.254582Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 59620837-3e2a-4a55-a061-07b7210fa0fb · outbound
This paper cites Knowledge transfer via distillation of activation boundaries formed by hidden neurons,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Knowledge transfer via distillation of activation boundaries formed by hidden neurons,
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:28.234484Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 88eae647-4f54-434f-91db-8c65bb1066c0 · outbound
This paper cites A gift from knowledge distillation: Fast optimization, network minimization and transfer learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning A gift from knowledge distillation: Fast optimization, network minimization and transfer learning,
Reference 49
- Resolution
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- raw_fallback, observed 2026-08-11T15:30:28.215569Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 01689eef-a6dc-4a5c-b984-1d56bf155d7f · outbound
This paper cites Graph-based Knowledge Distillation by Multi-head Attention Network.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Graph-based Knowledge Distillation by Multi-head Attention Network
Reference 50
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cddaf478-41b5-43a3-b21b-8393770e1969 · outbound
This paper cites Knowledge distillation via instance relationship graph,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Knowledge distillation via instance relationship graph,
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:28.197113Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 4bec14e9-9ab7-43a9-bc65-b0a36371b1a9 · outbound
This paper cites Similarity-preserving knowledge distillation,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Similarity-preserving knowledge distillation,
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:28.178504Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 1e2c06f1-8b8d-43e8-9a7f-ee6ec35d97dd · outbound
This paper cites Incremental few-shot learning via vector quantization in deep embedded space,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Incremental few-shot learning via vector quantization in deep embedded space,
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:28.154091Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 48444f56-7d80-4baf-9ccb-c4c89ae4ae77 · outbound
This paper cites End-to-end incremental learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning End-to-end incremental learning,
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:29.041263Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 79867b1c-012d-44ed-af22-3cee99d06297 · outbound
This paper cites Metafscil: A meta-learning approach for few-shot class incremental learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Metafscil: A meta-learning approach for few-shot class incremental learning,
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:28.132402Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 8a2b8b7b-bcc2-4dc7-9f7b-5aea778e4910 · outbound
This paper cites Overcoming catastrophic forgetting in incremental few-shot learning by finding flat minima,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Overcoming catastrophic forgetting in incremental few-shot learning by finding flat minima,
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:28.113194Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f5037c19-d9ba-42ba-89b9-4479bd1e40a0 · outbound
This paper cites Few-shot continual infomax learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Few-shot continual infomax learning,
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:28.095636Z
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Observation 4677899a-1e55-46cf-9e03-d9817bd62aab · outbound
This paper cites Neural col- lapse inspired feature-classifier alignment for few-shot class-incremental learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Neural col- lapse inspired feature-classifier alignment for few-shot class-incremental learning,
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:28.077928Z
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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 796ebdd7-ebe6-4e04-94e7-c75ac41752c2 · outbound
This paper cites Learning multiple layers of features from tiny images,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Learning multiple layers of features from tiny images,
Reference 59
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9d7956fd-3279-4894-9313-c539ec1ecc08 · outbound
This paper cites The caltech-ucsd birds-200-2011 dataset,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning The caltech-ucsd birds-200-2011 dataset,
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:28.043845Z
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Observation 84afcf80-70df-4285-bb6b-fa5dbd1a6ca9 · outbound
This paper cites Ima- genet: A large-scale hierarchical image database,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Ima- genet: A large-scale hierarchical image database,
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:28.023515Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 67574e02-9bff-4e97-bf50-bcc7fb208f99 · outbound
This paper cites Deep residual learning for image recognition,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Deep residual learning for image recognition,
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:28.002752Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 34d02bfe-4a24-48a0-8d33-2a4d56228a73 · outbound
This paper cites Learning without forgetting,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Learning without forgetting,
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:27.982886Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation dd116641-14b8-4ed5-a013-0ee4fc832b29 · outbound
This paper cites Maintaining dis- crimination and fairness in class incremental learning,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Maintaining dis- crimination and fairness in class incremental learning,
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:27.964934Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 8e4f30fc-f935-4960-9032-81f984ecf195 · outbound
This paper cites Online continual learning in image classification: An empirical survey,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Online continual learning in image classification: An empirical survey,
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:27.944835Z
Source-reported events for the cited work
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Observation 0c4393c7-5f91-4713-83ab-af2eb4232202 · outbound
This paper cites Densely connected convolutional networks,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Densely connected convolutional networks,
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:27.926001Z
Source-reported events for the cited work
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Observation 6c058d28-fe65-45a6-ace2-88d19d317639 · outbound
This paper cites Identity Mappings in Deep Residual Networks.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Identity Mappings in Deep Residual Networks
Reference 67
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T15:30:27.718788Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b00695d5-e069-43fe-8dd4-f8a093271bd8 · outbound
This paper cites Aggregated Residual Transformations for Deep Neural Networks.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Aggregated Residual Transformations for Deep Neural Networks
Reference 68
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T15:30:27.724733Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 53653889-afdf-40ed-bf5e-c4f273ccf62d · outbound
This paper cites Wide residual networks,.
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning Wide residual networks,
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T15:30:27.906024Z
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Pith citing papers
Observation f54605b0-cedf-401e-ba73-e45c41f2ca84 · inbound
On Aligning Hierarchical Standardized Embedding for Audio-visual Generalized Zero-shot Learning cites this paper.
On Aligning Hierarchical Standardized Embedding for Audio-visual Generalized Zero-shot Learning On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T08:57:47.664025Z
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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.