Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T22:30:10.796722Z
Paper Citation Record · LEDGER
As of 19 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 0 inbound Pith citation observations for arXiv:2501.01601.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T22:30:10.796722Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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
79 of 79 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 0969621e-8396-4e2a-9a3c-d764797c8cd1 · outbound
Few-shot Implicit Function Generation via Equivariance Data Augmentation Generative Adversarial Networks
Reference 1
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Observation 3b168320-f5a3-4346-8d03-7441f8deac93 · outbound
Few-shot Implicit Function Generation via Equivariance Nern: Learning neural representations for neural networks
Reference 2
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Observation c92f4e1a-bfa5-49c8-87cf-473c6753e4ea · outbound
Few-shot Implicit Function Generation via Equivariance Mip-nerf: A multiscale representation for anti-aliasing neu- ral radiance fields
Reference 3
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Observation e55bffb6-ab12-46e2-a2af-0ed6d9923027 · outbound
Few-shot Implicit Function Generation via Equivariance Dynamic programming
Reference 4
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Observation 99777b00-65c2-4cc4-974b-c892cfac1c9b · outbound
Few-shot Implicit Function Generation via Equivariance Deep local shapes: Learning local sdf priors for detailed 3d reconstruction
Reference 5
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Observation 97fc42c6-a1a5-4a63-a607-4568af8bc73f · outbound
Few-shot Implicit Function Generation via Equivariance ShapeNet: An Information-Rich 3D Model Repository
Reference 6
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Observation 83dea53f-d43f-4f3d-bba2-a2534655e439 · outbound
Few-shot Implicit Function Generation via Equivariance A simple framework for contrastive learn- ing of visual representations
Reference 7
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Observation 51a6fc82-1f72-4ebe-9b04-da5a96aed2b5 · outbound
Few-shot Implicit Function Generation via Equivariance Learning con- tinuous image representation with local implicit image func- tion
Reference 8
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Observation e6c03baa-6659-480a-a8d6-77b3f877d23d · outbound
Few-shot Implicit Function Generation via Equivariance Learning implicit fields for generative shape modeling
Reference 9
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Observation dae21d03-548b-4d89-925b-ae70d995898d · outbound
Few-shot Implicit Function Generation via Equivariance Neurbf: A neural fields rep- resentation with adaptive radial basis functions
Reference 10
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Observation b218b1f2-32a2-4cd3-a5c2-0bf18ec17be7 · outbound
Few-shot Implicit Function Generation via Equivariance FIGR: Few-shot Image Generation with Reptile
Reference 11
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Observation 52525746-cb65-4aa6-88a8-5498e6c28a21 · outbound
Few-shot Implicit Function Generation via Equivariance Spherical cnns
Reference 12
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Observation 8d5be9a6-4378-49da-82c0-458b64489414 · outbound
Few-shot Implicit Function Generation via Equivariance Deep learning on implicit neural representations of shapes
Reference 13
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Observation 79a49b4c-26c7-4de7-bc6f-a73da3fac8f8 · outbound
Few-shot Implicit Function Generation via Equivariance Wedit- gan: Few-shot image generation via latent space relocation
Reference 14
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Observation 14e2d17d-57f8-4d76-8d92-0556a1fe4405 · outbound
Few-shot Implicit Function Generation via Equivariance From data to functa: Your data point is a function and you can treat it like one
Reference 15
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Observation cf94f174-a15d-46fa-b392-43e499a2d6ca · outbound
Few-shot Implicit Function Generation via Equivariance Hyperdiffusion: Generating implicit neural fields with weight-space diffusion
Reference 16
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Observation 59648722-e171-4dfa-a190-0378af2ae055 · outbound
Few-shot Implicit Function Generation via Equivariance Learning so (3) equivariant repre- sentations with spherical cnns
Reference 17
Source-reported events for the cited work
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Observation e6d65ece-924b-43fd-aa0b-9b9f8dd2b52d · outbound
Few-shot Implicit Function Generation via Equivariance Depgraph: Towards any structural pruning
Reference 18
Source-reported events for the cited work
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Observation 488f1dbb-7339-4ae5-a2c2-f7b00d153913 · outbound
Few-shot Implicit Function Generation via Equivariance Model- agnostic meta-learning for fast adaptation of deep networks
Reference 19
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Observation 633e7c02-9f3c-40bf-bd00-018924f5ff79 · outbound
Few-shot Implicit Function Generation via Equivariance Learning shape templates with structured implicit functions
Reference 20
Source-reported events for the cited work
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Observation 1a1b9972-3c1c-4af0-a4b9-55acb5c1b1ef · outbound
Few-shot Implicit Function Generation via Equivariance HyperNetworks
Reference 21
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Observation 30448455-aee1-4d0b-89fe-5a337850ad60 · outbound
Few-shot Implicit Function Generation via Equivariance Deep models of interactions across sets
Reference 22
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Observation 29effea6-2a83-40b9-82f3-d8135ceafb5f · outbound
Few-shot Implicit Function Generation via Equivariance Computers and intractability: a guide to the theory of np-completeness (michael r
Reference 23
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Observation afce0555-aff5-402f-9ed7-06e7a139365e · outbound
Few-shot Implicit Function Generation via Equivariance Learning useful representations of recurrent neural network weight matrices
Reference 24
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Observation f7d7ee5b-d181-4e23-966e-d1dc4a6f1e32 · outbound
Few-shot Implicit Function Generation via Equivariance Gans trained by a two time-scale update rule converge to a local nash equilib- rium
Reference 25
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Observation d0b3c4ee-6e57-4d2c-9cc3-258ac87f865c · outbound
Few-shot Implicit Function Generation via Equivariance Anomalyd- iffusion: Few-shot anomaly image generation with diffusion model
Reference 26
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Observation f2f99ff6-2ddf-4ccb-a1a2-d1508bf4069e · outbound
Few-shot Implicit Function Generation via Equivariance Highly accurate protein structure prediction with alphafold
Reference 27
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Observation 6798151d-8cdb-4e04-a24f-d57c5cda3153 · outbound
Few-shot Implicit Function Generation via Equivariance Parameter prediction for unseen deep architectures
Reference 28
Source-reported events for the cited work
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Observation 3b2f8fe7-fde0-460e-a320-e0e1188a542d · outbound
Few-shot Implicit Function Generation via Equivariance On the generalization of equivariance and convolution in neural networks to the ac- tion of compact groups
Reference 29
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Observation 1469e61f-f3f5-4267-ae8a-a369de32fc37 · outbound
Few-shot Implicit Function Generation via Equivariance Learning multiple layers of features from tiny images
Reference 30
Source-reported events for the cited work
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Observation bf1a7944-864f-49c0-84b7-92634bd42143 · outbound
Few-shot Implicit Function Generation via Equivariance Gradient-based learning applied to document recog- nition
Reference 31
Source-reported events for the cited work
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Observation 41573a6d-8f8b-46a1-9faa-615360c5cb3e · outbound
Few-shot Implicit Function Generation via Equivariance Dynibar: Neural dynamic image-based rendering
Reference 32
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Observation 2b697590-e381-4865-92a9-e0495e3e501a · outbound
Few-shot Implicit Function Generation via Equivariance DAWSON: A Domain Adaptive Few Shot Generation Framework
Reference 33
Source-reported events for the cited work
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Observation 14d66f31-6444-4010-8578-0b40a29f9621 · outbound
Few-shot Implicit Function Generation via Equivariance Dist: Rendering deep implicit signed distance function with differentiable sphere tracing
Reference 34
Source-reported events for the cited work
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Observation 9f116f17-3ae8-4e86-8d5a-5d0f0f2a4d5b · outbound
Few-shot Implicit Function Generation via Equivariance Marching cubes: A high resolution 3d surface construction algorithm
Reference 35
Source-reported events for the cited work
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Observation 72923d51-5105-4dc8-9aa6-430828f54bc8 · outbound
Few-shot Implicit Function Generation via Equivariance Diffusion probabilistic models for 3d point cloud generation
Reference 36
Source-reported events for the cited work
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Observation e721f735-1aba-4923-a0ca-f904f156dd36 · outbound
Few-shot Implicit Function Generation via Equivariance Deformable neural radiance fields using rgb and event cameras
Reference 37
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Observation 0426f04a-7678-401b-b77c-513e2c5f6f99 · outbound
Few-shot Implicit Function Generation via Equivariance Continuous pose for monocular cameras in neural implicit representation
Reference 38
Source-reported events for the cited work
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Observation 5ca76dc7-6bbd-410b-9e3b-d5ed3111410c · outbound
Few-shot Implicit Function Generation via Equivariance Implicit-zoo: A large-scale dataset of neural im- plicit functions for 2d images and 3d scenes
Reference 39
Source-reported events for the cited work
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Observation 3897fe0e-45c1-4bff-a9ab-635b3cb1b490 · outbound
Few-shot Implicit Function Generation via Equivariance Invariant and equivariant graph networks
Reference 40
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Observation c17f246a-bb51-4ebf-be58-d6f772643a7b · outbound
Few-shot Implicit Function Generation via Equivariance Single-subject multi-contrast mri super-resolution via implicit neural representations
Reference 41
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Observation bf715cff-135c-43ea-a492-59dc9f4f492a · outbound
Few-shot Implicit Function Generation via Equivariance Occupancy networks: Learning 3d reconstruction in function space
Reference 42
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Observation 217e7b99-0ec9-4145-9015-f1b38ffe664b · outbound
Few-shot Implicit Function Generation via Equivariance Nerf: Representing scenes as neural radiance fields for view syn- thesis
Reference 43
Source-reported events for the cited work
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Observation 04b984f1-4388-429f-9739-57f88c57a8bc · outbound
Few-shot Implicit Function Generation via Equivariance Instant neural graphics primitives with a mul- tiresolution hash encoding
Reference 44
Source-reported events for the cited work
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Observation d1a765c7-6521-4fab-a9e0-dd4b4e2cbcf7 · outbound
Few-shot Implicit Function Generation via Equivariance Equivariant architectures for learning in deep weight spaces
Reference 45
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Observation db7109b9-0b87-4fbf-911f-99bcdb428b43 · outbound
Few-shot Implicit Function Generation via Equivariance Improved denoising diffusion probabilistic models
Reference 46
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Observation a3555599-7eda-4aca-97a8-0ba23bf662cc · outbound
Few-shot Implicit Function Generation via Equivariance Image generation from small datasets via batch statistics adaptation
Reference 47
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Observation fa97a362-5555-4b27-bf92-f05c4426f997 · outbound
Few-shot Implicit Function Generation via Equivariance Deepsdf: Learning con- tinuous signed distance functions for shape representation
Reference 48
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Observation cd03c579-3872-4575-9f6f-12e93a58d6cc · outbound
Few-shot Implicit Function Generation via Equivariance Learning to Learn with Generative Models of Neural Network Checkpoints
Reference 49
Source-reported events for the cited work
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Observation b5cc77c7-b07f-4024-ab30-232805b08823 · outbound
Few-shot Implicit Function Generation via Equivariance Learn- ing transferable visual models from natural language super- vision
Reference 50
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Observation d3a12aef-2f04-4222-9dda-32eed08c191c · outbound
Few-shot Implicit Function Generation via Equivariance On the spectral bias of neural networks
Reference 51
Source-reported events for the cited work
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Observation 8af13e91-566d-450a-8d0f-a368e7dabff7 · outbound
Few-shot Implicit Function Generation via Equivariance Beyond periodicity: Towards a unifying framework for activations in coordinate- mlps
Reference 52
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Observation 8d74ee14-f8d5-4386-b136-4bac0584b93a · outbound
Few-shot Implicit Function Generation via Equivariance Equivariance through parameter-sharing
Reference 53
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Observation d2d87459-e7a1-431f-9ecd-a262bc979dda · outbound
Few-shot Implicit Function Generation via Equivariance High-resolution image syn- thesis with latent diffusion models
Reference 54
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Observation bcace0cc-3e58-4789-b80e-b931ac17ac47 · outbound
Few-shot Implicit Function Generation via Equivariance Nonlinear total variation based noise removal algorithms
Reference 55
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Observation 1fcc79a8-dfa0-43bc-b7e6-16cea46e5dda · outbound
Few-shot Implicit Function Generation via Equivariance Wire: Wavelet implicit neural representations
Reference 56
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Observation c144f2a1-2275-443c-9169-f98fb8065102 · outbound
Few-shot Implicit Function Generation via Equivariance Hyper-representations as genera- tive models: Sampling unseen neural network weights
Reference 57
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Observation 04bc347b-70d7-49cc-add9-dd6b741f61e0 · outbound
Few-shot Implicit Function Generation via Equivariance Meshgpt: Generating triangle meshes with decoder-only transformers
Reference 58
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Observation 1d531013-2f11-4d7b-b318-67d01d4b2030 · outbound
Few-shot Implicit Function Generation via Equivariance Implicit neural representa- tions with periodic activation functions
Reference 59
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Observation 5a94213a-4d65-4801-8a51-a795d8e21a61 · outbound
Few-shot Implicit Function Generation via Equivariance Denois- ing diffusion implicit models
Reference 60
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Observation 9ae69dd5-3a61-45b3-8e71-0bc8bca4f040 · outbound
Few-shot Implicit Function Generation via Equivariance On the neighborhood structure of the traveling salesman problem generated by lo- cal search moves
Reference 61
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Observation f722c925-a756-4112-a737-2dc50bf70f36 · outbound
Few-shot Implicit Function Generation via Equivariance LLaMA: Open and Efficient Foundation Language Models
Reference 62
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Observation 67ede45e-388d-4f8d-8a9c-79e3838b6511 · outbound
Few-shot Implicit Function Generation via Equivariance Lion: Latent point dif- fusion models for 3d shape generation
Reference 63
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Observation 0e546917-cae3-46c5-aec0-1c59c611d030 · outbound
Few-shot Implicit Function Generation via Equivariance Neural Network Diffusion
Reference 64
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Few-shot Implicit Function Generation via Equivariance Representation theory and invariant neural networks
Reference 65
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Observation 83db8065-7d82-4f99-9945-277704d295b8 · outbound
Few-shot Implicit Function Generation via Equivariance Few shot generative model adaption via relaxed spatial structural alignment
Reference 66
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Reference 67
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Observation 2eb59c70-de13-44a2-8d1c-6e16dc6703ca · outbound
Few-shot Implicit Function Generation via Equivariance Signal processing for implicit neural rep- resentations
Reference 68
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Observation 1c2e044f-ab69-4916-9d0f-1c371273886d · outbound
Few-shot Implicit Function Generation via Equivariance Nesvor: implicit neural representation for slice-to- volume reconstruction in mri
Reference 69
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Observation 89a379a7-8337-458b-a09d-5588d2533640 · outbound
Few-shot Implicit Function Generation via Equivariance Neural metamorphosis
Reference 70
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Observation fa32c8f7-2a32-4366-a583-140b18f94099 · outbound
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Reference 71
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Observation 72cf86e5-9eed-4e07-a2bc-2cc2f47e48f2 · outbound
Few-shot Implicit Function Generation via Equivariance Deep sets
Reference 72
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Observation 2828a14c-9d37-45c6-8113-8124229ec0e8 · outbound
Few-shot Implicit Function Generation via Equivariance The unreasonable effectiveness of deep features as a perceptual metric
Reference 73
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Observation 933c7be7-9dd8-47c9-a658-60420a92669a · outbound
Few-shot Implicit Function Generation via Equivariance Ex- ploring incompatible knowledge transfer in few-shot image generation
Reference 74
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Observation 52094b22-6fb5-4b16-a91b-f2aa7864e4a7 · outbound
Few-shot Implicit Function Generation via Equivariance Where is my spot? few-shot image generation via latent subspace optimization
Reference 75
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Observation 9707f638-c7ef-45f2-8295-6f3df997d9a1 · outbound
Few-shot Implicit Function Generation via Equivariance Hypertransformer: Model generation for supervised and semi-supervised few-shot learning
Reference 76
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Observation fb7ff30d-3a37-4bb7-85ec-9be0c100bc47 · outbound
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Reference 77
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Few-shot Implicit Function Generation via Equivariance Neural functional transformers
Reference 78
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Few-shot Implicit Function Generation via Equivariance 3d shape genera- tion and completion through point-voxel diffusion
Reference 79
Source-reported events for the cited work
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No inbound Pith citation observations are available.