Weight Space Representation Learning via Neural Field Adaptation | Paper Citation Record

Observation fea70f94-621e-4c2c-8976-faa8f1a7919e · outbound

This paper cites Image generators with conditionally-independent pixel synthesis.

Weight Space Representation Learning via Neural Field Adaptation Image generators with conditionally-independent pixel synthesis

Reference 1

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Observation 1de771f0-0a24-40c7-b326-e95eff12ce41 · outbound

This paper cites Demystifying MMD GANs.

Weight Space Representation Learning via Neural Field Adaptation Demystifying MMD GANs

Reference 2

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Observation 81eaa5ff-f3f6-4875-94d0-ed875f497b52 · outbound

This paper cites pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis.

Weight Space Representation Learning via Neural Field Adaptation pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis

Reference 3

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Observation 1c855a4c-9878-4a17-bc5c-e871b86f04c0 · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

Weight Space Representation Learning via Neural Field Adaptation ShapeNet: An Information-Rich 3D Model Repository

Reference 4

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This paper cites Transformers as meta- learners for implicit neural representations.

Weight Space Representation Learning via Neural Field Adaptation Transformers as meta- learners for implicit neural representations

Reference 5

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This paper cites Interpreting the weight space of customized dif- fusion models.Advances in Neural Information Processing Systems, 37:137334–137371, 2024.

Weight Space Representation Learning via Neural Field Adaptation Interpreting the weight space of customized dif- fusion models.Advances in Neural Information Processing Systems, 37:137334–137371, 2024

Reference 6

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Observation 31653fba-2123-41db-a296-4a47d8c05bff · outbound

This paper cites COIN: COmpression with Implicit Neural representations.

Weight Space Representation Learning via Neural Field Adaptation COIN: COmpression with Implicit Neural representations

Reference 7

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This paper cites an unresolved cited work.

Weight Space Representation Learning via Neural Field Adaptation Unresolved cited work

Reference 8

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Observation d3fe77d5-a990-4c8b-99f7-b6e666cb1be8 · outbound

This paper cites Hyperdiffusion: Generating implicit neural fields with weight-space diffusion.

Weight Space Representation Learning via Neural Field Adaptation Hyperdiffusion: Generating implicit neural fields with weight-space diffusion

Reference 9

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Observation 46d211e9-9391-47dc-b38f-8db35f8dd760 · outbound

This paper cites Where Do We Stand with Implicit Neural Representations? A Technical and Performance Survey.

Weight Space Representation Learning via Neural Field Adaptation Where Do We Stand with Implicit Neural Representations? A Technical and Performance Survey

Reference 10

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Observation a05c05b9-4a1b-4bc3-9ee8-8dae22ed8e34 · outbound

This paper cites Linear mode connectivity and the lot- tery ticket hypothesis.

Weight Space Representation Learning via Neural Field Adaptation Linear mode connectivity and the lot- tery ticket hypothesis

Reference 11

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Observation da897e78-9888-4032-ad16-202c6b0f168b · outbound

This paper cites Sur la distance de deux lois de probabilit´e.

Weight Space Representation Learning via Neural Field Adaptation Sur la distance de deux lois de probabilit´e

Reference 12

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Observation 327ceafd-6b1c-4898-a2e2-b347e4c83bc9 · outbound

This paper cites Revisiting model merging: A statistical perspective.arXiv preprint, 2024.

Weight Space Representation Learning via Neural Field Adaptation Revisiting model merging: A statistical perspective.arXiv preprint, 2024

Reference 13

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Observation 68f6a812-d4df-43d0-ba55-4bcd7e208ab5 · outbound

This paper cites D’oh: Decoder-only ran- dom hypernetworks for implicit neural representations.

Weight Space Representation Learning via Neural Field Adaptation D’oh: Decoder-only ran- dom hypernetworks for implicit neural representations

Reference 14

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Observation 69e98d55-0d89-41d6-8f06-73276b68be29 · outbound

This paper cites Hypernetworks.

Weight Space Representation Learning via Neural Field Adaptation Hypernetworks

Reference 15

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Observation 4d3d3fd7-b7ef-4c2e-82e9-d2be863d4c9b · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.Advances in neural information processing systems, 30, 2017.

Weight Space Representation Learning via Neural Field Adaptation Gans trained by a two time-scale update rule converge to a local nash equilib- rium.Advances in neural information processing systems, 30, 2017

Reference 16

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Observation 89945907-d141-45e7-a258-8ceae63f136e · outbound

This paper cites Meta- learning in neural networks: a survey.

Weight Space Representation Learning via Neural Field Adaptation Meta- learning in neural networks: a survey

Reference 17

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Observation 52a4a8e7-de50-4679-8f95-80c16923f925 · outbound

This paper cites Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022.

Weight Space Representation Learning via Neural Field Adaptation Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022

Reference 18

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Observation 198e80d0-47d6-49ec-9b8e-6558b5331b4b · outbound

This paper cites Re- thinking fid: Towards a better evaluation metric for image generation.

Weight Space Representation Learning via Neural Field Adaptation Re- thinking fid: Towards a better evaluation metric for image generation

Reference 19

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Observation ea84900d-8ea1-4064-8945-45e78d5f1a88 · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

Weight Space Representation Learning via Neural Field Adaptation A style-based generator architecture for generative adversarial networks

Reference 20

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Observation 08e89adc-e1a8-4f96-ad1a-efeb849ed3ae · outbound

This paper cites Alias-free generative adversarial networks.Advances in neural infor- mation processing systems, 34:852–863, 2021.

Weight Space Representation Learning via Neural Field Adaptation Alias-free generative adversarial networks.Advances in neural infor- mation processing systems, 34:852–863, 2021

Reference 21

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Observation bba381c9-c7fd-4fa0-b9fe-b088a221f843 · outbound

This paper cites Hypernetwork functional image representation.

Weight Space Representation Learning via Neural Field Adaptation Hypernetwork functional image representation

Reference 22

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Observation f46bc721-6da7-4078-9ec9-d83a91707050 · outbound

This paper cites Graph neural net- works for learning equivariant representations of neural net- works.

Weight Space Representation Learning via Neural Field Adaptation Graph neural net- works for learning equivariant representations of neural net- works

Reference 23

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Observation 2f81cf83-7cbd-46ac-9eed-67d0189edcb7 · outbound

This paper cites Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models.

Weight Space Representation Learning via Neural Field Adaptation Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models

Reference 24

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Observation e9eca306-0424-4105-ba86-852832d9c791 · outbound

This paper cites The empirical impact of neural param- eter symmetries, or lack thereof.Advances in Neural Infor- mation Processing Systems, 37:28322–28358, 2024.

Weight Space Representation Learning via Neural Field Adaptation The empirical impact of neural param- eter symmetries, or lack thereof.Advances in Neural Infor- mation Processing Systems, 37:28322–28358, 2024

Reference 25

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Observation 5ae4cc1d-95b5-4785-b87c-0d71d610705d · outbound

This paper cites Diffusion probabilistic models for 3d point cloud generation.

Weight Space Representation Learning via Neural Field Adaptation Diffusion probabilistic models for 3d point cloud generation

Reference 26

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Observation 74f4d4ca-649b-4fee-a3ed-6efbac884b10 · outbound

This paper cites Equivariant architectures for learning in deep weight spaces.

Weight Space Representation Learning via Neural Field Adaptation Equivariant architectures for learning in deep weight spaces

Reference 27

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Observation 08adb873-b120-45fd-a486-79503629be36 · outbound

This paper cites Fusion of graph convolutional net- works via optimal transport.arXiv preprint, 2025.

Weight Space Representation Learning via Neural Field Adaptation Fusion of graph convolutional net- works via optimal transport.arXiv preprint, 2025

Reference 28

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Observation 6336206f-bffe-4dad-9457-80696a468fff · outbound

This paper cites Deepsdf: Learning con- tinuous signed distance functions for shape representation.

Weight Space Representation Learning via Neural Field Adaptation Deepsdf: Learning con- tinuous signed distance functions for shape representation

Reference 29

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Observation 70bd3169-0e68-4fa7-a4c2-4d62ab7dd61b · outbound

This paper cites Learning to Learn with Generative Models of Neural Network Checkpoints.

Weight Space Representation Learning via Neural Field Adaptation Learning to Learn with Generative Models of Neural Network Checkpoints

Reference 30

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Observation 92dc9382-04bb-4061-b411-d9956896e56b · outbound

This paper cites Scalable diffusion mod- els with transformers.

Weight Space Representation Learning via Neural Field Adaptation Scalable diffusion mod- els with transformers

Reference 31

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Observation 308b4ae4-a4b9-4b2c-b63e-ab4f9f958c46 · outbound

This paper cites Pointnet++: Deep hierarchical feature learning on point sets in a metric space.Advances in neural information processing systems, 30, 2017.

Weight Space Representation Learning via Neural Field Adaptation Pointnet++: Deep hierarchical feature learning on point sets in a metric space.Advances in neural information processing systems, 30, 2017

Reference 32

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Observation 5d46db78-15e1-451a-b416-4941cc8c9a22 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

Weight Space Representation Learning via Neural Field Adaptation Learning transferable visual models from natural language supervi- sion

Reference 33

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Observation 20e07569-f1a9-496c-a10a-d5072f276bc6 · outbound

This paper cites Model fusion via optimal transport.

Weight Space Representation Learning via Neural Field Adaptation Model fusion via optimal transport

Reference 34

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Observation 22212989-bd4c-4e77-87a1-f73c3b4f3973 · outbound

This paper cites Hyper-align: Efficient modality alignment via hy- pernetworks.

Weight Space Representation Learning via Neural Field Adaptation Hyper-align: Efficient modality alignment via hy- pernetworks

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T19:13:33.150938Z

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Observation 1bf6cceb-7702-4429-836e-51f71145b4b6 · outbound

This paper cites Fourier features let networks learn high frequency functions in low dimen- sional domains.Advances in neural information processing systems, 33:7537–7547, 2020.

Weight Space Representation Learning via Neural Field Adaptation Fourier features let networks learn high frequency functions in low dimen- sional domains.Advances in neural information processing systems, 33:7537–7547, 2020

Reference 36

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This paper cites Lion: Latent point dif- fusion models for 3d shape generation.Advances in Neural Information Processing Systems, 35:10021–10039, 2022.

Weight Space Representation Learning via Neural Field Adaptation Lion: Latent point dif- fusion models for 3d shape generation.Advances in Neural Information Processing Systems, 35:10021–10039, 2022

Reference 37

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This paper cites Learning transferable features for implicit neural representations.Advances in Neural Information Processing Systems, 37:42268–42291, 2024.

Weight Space Representation Learning via Neural Field Adaptation Learning transferable features for implicit neural representations.Advances in Neural Information Processing Systems, 37:42268–42291, 2024

Reference 38

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Observation b6328f2a-c07a-4922-b2d0-3b1890953dc4 · outbound

This paper cites Scaling weight space generative mod- els.arXiv preprint, 2025.

Weight Space Representation Learning via Neural Field Adaptation Scaling weight space generative mod- els.arXiv preprint, 2025

Reference 39

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Observation a13c0d7c-328e-4246-b47e-fbfaeaf9a904 · outbound

This paper cites Neural Network Diffusion.

Weight Space Representation Learning via Neural Field Adaptation Neural Network Diffusion

Reference 40

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Observation 8a5786f3-c543-47de-83f8-c438239d02a3 · outbound

This paper cites Neural fields in visual computing and beyond.

Weight Space Representation Learning via Neural Field Adaptation Neural fields in visual computing and beyond

Reference 41

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Observation 42ba9c64-9f6f-4ec9-a864-ed63b20485bc · outbound

This paper cites Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities.

Weight Space Representation Learning via Neural Field Adaptation Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities

Reference 42

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Observation b709f7e1-ce0b-4383-bf28-df984b6db66f · outbound

This paper cites A structured dictionary perspective on implicit neural representations.

Weight Space Representation Learning via Neural Field Adaptation A structured dictionary perspective on implicit neural representations

Reference 43

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Observation 738c0ee1-ea8d-47c0-8726-2b7bba5f6c72 · outbound

This paper cites Symmetry in neural network parameter spaces.arXiv preprint arXiv:2506.13018, 2025.

Weight Space Representation Learning via Neural Field Adaptation Symmetry in neural network parameter spaces.arXiv preprint arXiv:2506.13018, 2025

Reference 44

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Observation 97a7cf5f-7295-46fb-96aa-bf955fc96534 · outbound

This paper cites Permutation equivariant neural functionals.Advances in neural information processing systems, 36:24966–24992,.

Weight Space Representation Learning via Neural Field Adaptation Permutation equivariant neural functionals.Advances in neural information processing systems, 36:24966–24992,

Reference 45

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This paper cites Neural functional transformers.Advances in neural infor- mation processing systems, 36:77485–77502, 2023.

Weight Space Representation Learning via Neural Field Adaptation Neural functional transformers.Advances in neural infor- mation processing systems, 36:77485–77502, 2023

Reference 46

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Observation 1a99edd7-0d1f-4d57-bd84-031c629cd15b · outbound

This paper cites 3d shape generation and completion through point-voxel diffusion.

Weight Space Representation Learning via Neural Field Adaptation 3d shape generation and completion through point-voxel diffusion

Reference 47

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Weight Space Representation Learning via Neural Field Adaptation Unresolved cited work

Reference 48

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This paper cites INRs repre- sent signals as continuous functionsΦ :R n →R m, where a neural network mapsn-dimensional coordinates tom- dimensional quantities.

Weight Space Representation Learning via Neural Field Adaptation INRs repre- sent signals as continuous functionsΦ :R n →R m, where a neural network mapsn-dimensional coordinates tom- dimensional quantities

Reference 49

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Observation e791d721-a880-4eae-b91f-c7eac090b8a9 · outbound

This paper cites Standalone MLP As shown in Figure 7(a), The standalone MLP is a Fourier Feature [36] layerα 1 = sin(ω0 ·(W 1p+b 1))followed by 2linear layers.

Weight Space Representation Learning via Neural Field Adaptation Standalone MLP As shown in Figure 7(a), The standalone MLP is a Fourier Feature [36] layerα 1 = sin(ω0 ·(W 1p+b 1))followed by 2linear layers

Reference 50

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Observation db15eee8-8a5a-4c28-a18e-275e3e4ed245 · outbound

This paper cites For 3D, we also calculate distance-based metrics.

Weight Space Representation Learning via Neural Field Adaptation For 3D, we also calculate distance-based metrics

Reference 51

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Observation de700329-3b7a-44f2-aee8-00adb77ca6b5 · outbound

This paper cites Following the practice of KID [2], we choose γp = 1/Nfeature.

Weight Space Representation Learning via Neural Field Adaptation Following the practice of KID [2], we choose γp = 1/Nfeature

Reference 52

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Weight Space Representation Learning via Neural Field Adaptation Unresolved cited work

Reference 53

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This paper cites To isolate its contribution, we train a baseline diffusion model without the layer encoder on the ShapeNet multi-category dataset.

Weight Space Representation Learning via Neural Field Adaptation To isolate its contribution, we train a baseline diffusion model without the layer encoder on the ShapeNet multi-category dataset

Reference 54

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Observation 2fea6064-6354-4e6c-8fba-e6b2308512a6 · outbound

This paper cites We linearly inter- polate between two instances’ LoRA weight pairs(A1,B 1) and(A 2,B 2), evaluating the resulting neural field at each interpolation step.

Weight Space Representation Learning via Neural Field Adaptation We linearly inter- polate between two instances’ LoRA weight pairs(A1,B 1) and(A 2,B 2), evaluating the resulting neural field at each interpolation step

Reference 55

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Observation abbe7efb-1106-4ffc-94da-3e9063d492bb · outbound

This paper cites Please see Figure 10 for results on ShapeNet Air- planes, Figure 11 for results on ShapeNet Multi, and Fig- ure 12 for results on FFHQ.

Weight Space Representation Learning via Neural Field Adaptation Please see Figure 10 for results on ShapeNet Air- planes, Figure 11 for results on ShapeNet Multi, and Fig- ure 12 for results on FFHQ

Reference 56

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Observation 384e3dec-c084-4deb-8e46-a1e9e2e2695d · outbound

This paper cites First, our approach requires all instances to share the same pre-trained base model and initialization.

Weight Space Representation Learning via Neural Field Adaptation First, our approach requires all instances to share the same pre-trained base model and initialization

Reference 57

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