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Paper Citation Record · LEDGER

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation

As of 7 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 6 inbound Pith citation observations for arXiv:2510.22491.

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

pith.paper-citation-record.v1
2510.22491 v3

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T08:10:10.744434Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T21:32:46.803408Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-15T06:35:09.461044Z

Reference resolution

42 of 42 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved41
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 13219519-6adb-4fcb-a917-1e4aa0b4ac3e · outbound

This paper cites Learning representations and generative models for 3d point clouds.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Learning representations and generative models for 3d point clouds

Reference 1

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source=arxiv_source observed=2026-08-04T08:10:07.233020Z digest=sha256:49e8d6095700ef24c0ec852aa021eb27fc8353ea534ae66c0220c98e3ec48998

Observation b137041b-2d3c-49dc-8f71-be911397b5bc · outbound

This paper cites Learning from Randomly Initialized Neural Network Features.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Learning from Randomly Initialized Neural Network Features

Reference 2

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source=arxiv_source observed=2026-08-04T08:10:07.317365Z digest=sha256:2436b2ce0543ba5da4d4a0d7ac9a35b99301608f07cdf93c0ea3a5fb00222e81

Observation a95de1d8-b09c-494b-930a-660bd42aac30 · outbound

This paper cites Sal: Sign agnostic learning of shapes from raw data.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Sal: Sign agnostic learning of shapes from raw data

Reference 3

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source=arxiv_source observed=2026-08-04T08:10:07.374699Z digest=sha256:0d1ea639a7bfbff7693bde09799b9f77bef113b3341ee98fc3b5fdcc149f5029

Observation 704f182c-b919-4459-98ac-9bc294f6af66 · outbound

This paper cites Gan cocktail: Mixing GAN s without dataset access.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Gan cocktail: Mixing GAN s without dataset access

Reference 4

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source=arxiv_source observed=2026-08-04T08:10:07.450115Z digest=sha256:d1842f8be6b46ea4a62abea8b709a78b432f016eabf6d9447774654b5dadccad

Observation e2126e7a-d55b-4033-80ae-bb22ea376f81 · outbound

This paper cites Diffusion soup: Model merging for text-to-image diffusion models.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Diffusion soup: Model merging for text-to-image diffusion models

Reference 5

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source=arxiv_source observed=2026-08-04T08:10:07.528778Z digest=sha256:01c121bc33ddf001a0c84768d04927137244a3319e8c5c41d73eba2ed100d73a

Observation 01eb257f-a043-4c84-81b1-3e62c96e4d55 · outbound

This paper cites Sdf-diff: Differentiable rendering of signed distance fields for 3d shape editing.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Sdf-diff: Differentiable rendering of signed distance fields for 3d shape editing

Reference 6

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source=arxiv_source observed=2026-08-04T08:10:07.596540Z digest=sha256:dbdbdb1d442ace727906a45364060f5d91f0a09d440489a1ce805b6c10dbc2dd

Observation 262a3418-0fb4-4c1d-89c4-a7c20892dc73 · outbound

This paper cites Maskedgen: Conditional 3d shape generation with masked diffusion.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Maskedgen: Conditional 3d shape generation with masked diffusion

Reference 7

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source=arxiv_source observed=2026-08-04T08:10:07.676968Z digest=sha256:a6ca899b1ecf982e3a96de1c5a16b840d69e402e010a4332775e293b9db0c2ac

Observation 4b164b3c-fbbb-4d19-887c-bdbc443bc956 · outbound

This paper cites Schwing, and Liang-Yan Gui.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Schwing, and Liang-Yan Gui

Reference 8

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source=arxiv_source observed=2026-08-04T08:10:07.793155Z digest=sha256:1e93c42c59360d30c36de011c368c6fe4c0f36a29b51274ac2cd2c5ea4578085

Observation c73d23ea-8fc8-4dc0-8b1c-e3a9ad61cdc6 · outbound

This paper cites Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion

Reference 9

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local_arxiv, observed 2026-08-04T08:13:31.637732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-04T08:10:07.844377Z digest=sha256:d1002acfee8f8db16a96e7a81c4eb631b68ddb8d65df2f905e2ba65e6c5a36d5

Observation 45b57455-8cf7-44f4-b7e8-92a6eac6a3a3 · outbound

This paper cites Diffusion-sdf: Conditional generative modeling of signed distance functions.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Diffusion-sdf: Conditional generative modeling of signed distance functions

Reference 10

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source=arxiv_source observed=2026-08-04T08:10:07.927056Z digest=sha256:e4373a7cc2cd2ee5175428631b8725c921879e6604dd5de98335d0dc87a35e06

Observation 8ad4640f-c1a7-4222-99a5-c0b7e78421a0 · outbound

This paper cites Cad2shape: Learning geometry representations from cad.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Cad2shape: Learning geometry representations from cad

Reference 11

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source=arxiv_source observed=2026-08-04T08:10:07.989938Z digest=sha256:9b855576167f1fe017e840423d3750b63e82a79b9e81c524d7eb530810074b02

Observation aba0689a-77ba-4c2b-bbea-fede8460fdff · outbound

This paper cites Drivaernet++: A large-scale multimodal car dataset with computational fluid dynamics simulations and deep learning benchmarks.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Drivaernet++: A large-scale multimodal car dataset with computational fluid dynamics simulations and deep learning benchmarks

Reference 12

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source=arxiv_source observed=2026-08-04T08:10:08.073287Z digest=sha256:7c5f4272b8a9cfd943796e600509630a6cba4067f3ab18668dcd3a3ed4fec190

Observation bb74b1e8-2ac1-4f4a-a129-225cd5f5a0c2 · outbound

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

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Hyperdiffusion: Generating implicit neural fields with weight-space diffusion

Reference 13

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source=arxiv_source observed=2026-08-04T08:10:08.203185Z digest=sha256:afd287bf4403af8a3565d9ff3924ae34386ae69d1c628990011030e9d6c42b7d

Observation 258067de-704e-40e6-8dba-4ff708ada38d · outbound

This paper cites GET3D : A generative model of high quality 3d textured shapes learned from images.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation GET3D : A generative model of high quality 3d textured shapes learned from images

Reference 14

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source=arxiv_source observed=2026-08-04T08:10:08.281702Z digest=sha256:e66cdfc9547df21a4a2707e627a3c956eb0b129fd7cc4e5033dc050041199e6a

Observation 0dbb6265-b64e-4ac0-be45-880691ebec0f · outbound

This paper cites Sdm-net: Deep generative network for structured deformable mesh.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Sdm-net: Deep generative network for structured deformable mesh

Reference 15

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source=arxiv_source observed=2026-08-04T08:10:08.376183Z digest=sha256:e9f26ef2a654c1fac202a6ba32ed1846df70af01b9ad91e89cc4e59fd7a70178

Observation 365ad26d-ae1a-44c3-bde9-889436d16052 · outbound

This paper cites Atlasnet: A papier-mâché approach to learning 3d surface generation.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Atlasnet: A papier-mâché approach to learning 3d surface generation

Reference 16

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source=arxiv_source observed=2026-08-04T08:10:08.539471Z digest=sha256:a4799cad95be671207d8fb8cbcea0d5c429a43cdf1c54077aa6bc6769c57fcd0

Observation 75ac1cf0-db31-4c6f-a8c8-e5025a0064c9 · outbound

This paper cites A Mechanism for Producing Aligned Latent Spaces with Autoencoders.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation A Mechanism for Producing Aligned Latent Spaces with Autoencoders

Reference 17

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source=arxiv_source observed=2026-08-04T08:10:08.678094Z digest=sha256:4f336bcbb0ca0024957999c59c1d62af671923adc7b98a2e92e7d614146a97c2

Observation fb30e42f-50be-4fcf-9944-ef58ce9cc2ec · outbound

This paper cites Salad: Part-level latent diffusion for 3d shape generation and manipulation.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Salad: Part-level latent diffusion for 3d shape generation and manipulation

Reference 18

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source=arxiv_source observed=2026-08-04T08:10:08.808144Z digest=sha256:ff5df1bb3f86f962a0222cd206fd179d6da885feb169eceae5ed245a78a4477a

Observation 279a2e07-f9e7-4b61-b373-c2577ed90985 · outbound

This paper cites Gen-ldm: A generative latent diffusion model for 3d shape generation.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Gen-ldm: A generative latent diffusion model for 3d shape generation

Reference 19

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source=arxiv_source observed=2026-08-04T08:10:08.926384Z digest=sha256:62931bfc4cc203673548be95be35fa18801431c9fbf7e0a8d090f5d72f35f76e

Observation 747a07b2-6237-4ddf-8b86-f4972600951d · outbound

This paper cites Openshape: Scaling up 3d shape representation towards open-world understanding.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Openshape: Scaling up 3d shape representation towards open-world understanding

Reference 20

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source=arxiv_source observed=2026-08-04T08:10:09.058441Z digest=sha256:8a0fc0bc43f99c93f51c0409716b18923c51c53bbd717bce986ee46b46f89212

Observation a0fb53b4-4a33-4ae3-871d-d0429f47171c · outbound

This paper cites Marching cubes: A high resolution 3d surface construction algorithm.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Marching cubes: A high resolution 3d surface construction algorithm

Reference 21

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source=arxiv_source observed=2026-08-04T08:10:09.147256Z digest=sha256:0a624eaacf2e4824a6860ef8937d145cba656d8102b02d8da757ef2994b082c2

Observation fbe2c5bc-053e-4fb7-a9d6-0e4196473e0e · outbound

This paper cites Vehiclesdf: A 3d generative model for constrained engineering design via surrogate modeling.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Vehiclesdf: A 3d generative model for constrained engineering design via surrogate modeling

Reference 22

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source=arxiv_source observed=2026-08-04T08:10:09.249330Z digest=sha256:734202aefc66550336fb3add04ca83ffe081a6fdd437d2c85c6a769aaafa1331

Observation eab5263f-a4fd-41c1-90b8-3b3230789ff9 · outbound

This paper cites Differentiable volumetric rendering: Learning implicit 3d representations without 3d supervision.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Differentiable volumetric rendering: Learning implicit 3d representations without 3d supervision

Reference 23

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source=arxiv_source observed=2026-08-04T08:10:09.303132Z digest=sha256:696bf9e44fcb29446045d683cc52e5eda9f32e2f0e64fdf5c9696f4a48b8f71d

Observation 7b5d804f-ae9f-4d48-9283-6090d7057873 · outbound

This paper cites Deepsdf: Learning continuous signed distance functions for shape representation.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Deepsdf: Learning continuous signed distance functions for shape representation

Reference 24

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source=arxiv_source observed=2026-08-04T08:10:09.374583Z digest=sha256:afa8805657275703cc359b1440f015b009c3c20e68cde6527a41a148e1afd4b5

Observation c179c907-ad8f-4090-8d0a-a4c8c4a1f2cb · outbound

This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Pointnet: Deep learning on point sets for 3d classification and segmentation

Reference 25

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source=arxiv_source observed=2026-08-04T08:10:09.455611Z digest=sha256:9d252a2e9bc39c7a4a86d224ed443c96c3eb3cfac758cc1cb087b38894a060b9

Observation b6c4bb05-e5aa-4219-9d0d-5f06c49564e4 · outbound

This paper cites Lambourne, Ye Wang, Chin-Yi Cheng, Marco Fumero, and Kamal Rahimi Malekshan.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Lambourne, Ye Wang, Chin-Yi Cheng, Marco Fumero, and Kamal Rahimi Malekshan

Reference 26

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source=arxiv_source observed=2026-08-04T08:10:09.538407Z digest=sha256:c1411fdfe28a36b6d18e1645e09c6b543e8ea7c5f5a77f11f68c69cb07380c0c

Observation f64af1af-dee5-4e2b-a4f7-f24179f6538d · outbound

This paper cites Sketchgraphs: A large-scale dataset for modeling relational geometry in cad.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Sketchgraphs: A large-scale dataset for modeling relational geometry in cad

Reference 27

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source=arxiv_source observed=2026-08-04T08:10:09.597133Z digest=sha256:61417476a9e8b365eb61c02199b1f09b9055191709ceec7a855cb1c0df8e24e2

Observation 44205b37-644b-40e6-b474-3283f3260843 · outbound

This paper cites Blendednet: A blended wing body aircraft dataset and surrogate model for aerodynamic predictions.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Blendednet: A blended wing body aircraft dataset and surrogate model for aerodynamic predictions

Reference 28

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source=arxiv_source observed=2026-08-04T08:10:09.678728Z digest=sha256:b423f9a60d4919b04229cea13cc345530843d5df28e339b07bed5e6d847b8cb0

Observation e2f374b5-732c-4b59-a925-d1689d4dd041 · outbound

This paper cites Regression shrinkage and selection via the lasso.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Regression shrinkage and selection via the lasso

Reference 29

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source=arxiv_source observed=2026-08-04T08:10:09.764831Z digest=sha256:6d536a0ab5cecf206d0e923c2207a179c04a96ec7667aeaa6a9c16bb0b2e0a73

Observation 36c6dc6f-f18b-44c3-b3a2-f06ecf3310ab · outbound

This paper cites Lion: Latent point diffusion models for 3d shape generation.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Lion: Latent point diffusion models for 3d shape generation

Reference 30

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source=arxiv_source observed=2026-08-04T08:10:09.826867Z digest=sha256:f844a3d503a8545618e5ab9f4af73347685a087bb4e2e04c4857fa93df27da7e

Observation 48b3312d-af38-4101-b734-ac6cfb7cec26 · outbound

This paper cites Deepcad: A deep generative network for computer-aided design models.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Deepcad: A deep generative network for computer-aided design models

Reference 31

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source=arxiv_source observed=2026-08-04T08:10:09.902952Z digest=sha256:231cc68ff4071391d8556c658ef9f5b6846f37e2f86dd23ade5cf3df705378d3

Observation e93321c2-e3e2-479c-a014-cb715e9083c7 · outbound

This paper cites Deep network interpolation for continuous imagery effect transition.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Deep network interpolation for continuous imagery effect transition

Reference 32

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source=arxiv_source observed=2026-08-04T08:10:09.972176Z digest=sha256:1edbe5eeef3ee05875630b3931b7ed1336ca1991d75d63c8a9494ba7b90d40b7

Observation d44427cf-42cb-420d-9637-87c6f48d299a · outbound

This paper cites Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time

Reference 33

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source=arxiv_source observed=2026-08-04T08:10:10.054418Z digest=sha256:4f78d4608131d7e4d3bac2be0eae0ccdda6519f48e7290e85b88d4a340e000c8

Observation 651fb9ab-d986-47c1-b32b-d2b8ff7d8569 · outbound

This paper cites Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling

Reference 34

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source=arxiv_source observed=2026-08-04T08:10:10.136170Z digest=sha256:f510432c1bf95604d9a101efd8b1bcba0fa94c58e406b063487a68e3e8ab2598

Observation e6dff850-6099-4164-9a9f-adba6867c069 · outbound

This paper cites Structured 3d latents for scalable and versatile 3d generation.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Structured 3d latents for scalable and versatile 3d generation

Reference 35

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This paper cites Learning semantic deformation flows with 3d convolutional networks.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Learning semantic deformation flows with 3d convolutional networks

Reference 36

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This paper cites Lion: Latent point diffusion models for 3d shape generation.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Lion: Latent point diffusion models for 3d shape generation

Reference 37

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This paper cites Michelangelo: Conditional 3d shape generation based on shape-image-text aligned latent representation.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Michelangelo: Conditional 3d shape generation based on shape-image-text aligned latent representation

Reference 38

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Observation 0ac83162-98c3-427a-af98-336d47698f4a · outbound

This paper cites write newline.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation write newline

Reference 39

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This paper cites @esa (Ref.

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation @esa (Ref

Reference 40

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LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Unresolved cited work

Reference 41

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LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation Unresolved cited work

Reference 42

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Pith citing papers

Observation 06843db3-79d6-4cfd-af6f-3d4d3d20b310 · inbound

FLARE: A Data-Efficient Surrogate for Predicting Displacement Fields in Directed Energy Deposition cites this paper.

FLARE: A Data-Efficient Surrogate for Predicting Displacement Fields in Directed Energy Deposition LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation

Reference 38

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GeoFunFlow-3D: A Physics-Guided Generative Flow Matching Framework for High-Fidelity 3D Aerodynamic Inference over Complex Geometries cites this paper.

GeoFunFlow-3D: A Physics-Guided Generative Flow Matching Framework for High-Fidelity 3D Aerodynamic Inference over Complex Geometries LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation

Reference 29

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Observation a49d45e5-43f4-47ff-afd8-67cb6c198b86 · inbound

Geometry-Aware Neural Optimizer for Shape Optimization and Inversion cites this paper.

Geometry-Aware Neural Optimizer for Shape Optimization and Inversion LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation

Reference 20

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Observation ec1af490-0a67-4676-8ee5-f2c688091a49 · inbound

Geometry-Aware Neural Optimizer for Shape Optimization and Inversion cites this paper.

Geometry-Aware Neural Optimizer for Shape Optimization and Inversion LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation

Reference 20

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Observation edb8bf4f-2903-4897-80e5-af80ca8c9420 · inbound

Geometry-Aware Neural Optimizer for Shape Optimization and Inversion cites this paper.

Geometry-Aware Neural Optimizer for Shape Optimization and Inversion LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation

Reference 20

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Observation 18767083-5945-4801-a414-98d4002c6173 · inbound

CertMix: Certified, Data-Efficient Metamaterial Design by Affine Mixing of Aligned Neural-Implicit Weight Spaces cites this paper.

CertMix: Certified, Data-Efficient Metamaterial Design by Affine Mixing of Aligned Neural-Implicit Weight Spaces LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation

Reference 1

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