Paper Citation Record · LEDGER

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

As of 9 August 2026, this Paper Citation Record lists 77 of 77 outbound references and 7 inbound Pith citation observations for arXiv:2508.09834.

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

pith.paper-citation-record.v1
2508.09834 v1

Coverage vector

measured 77 of 77 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:53:09.684389Z

measured 84 of 84 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T05:56:51.447893Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T08:44:28.037573Z

Reference resolution

77 of 77 outbound references displayed

verified exact2
verified fuzzy68
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b7ccb391-78cc-4408-b8b6-7020665a285e · outbound

This paper cites Representing 3D Shapes with Probabilistic Directed Distance Fields.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Representing 3D Shapes with Probabilistic Directed Distance Fields

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.935397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ddb1dac4-d9c5-4a59-8764-5d32b2474e81 · outbound

This paper cites Fast winding numbers for soups and clouds.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Fast winding numbers for soups and clouds

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.921961Z

Source-reported events for the cited work

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Observation 1a6fa3a8-3180-42bf-b3ae-eb90b573da5b · outbound

This paper cites ARK- itScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Data.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models ARK- itScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Data

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.908004Z

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Observation 5371290f-d3f0-4770-a653-5cc7292dbe7f · outbound

This paper cites A Survey of Surface Re- construction from Point Clouds.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models A Survey of Surface Re- construction from Point Clouds

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.894085Z

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Observation 194f368e-fe19-49ad-9400-bcabd65f28cd · outbound

This paper cites Richter, and Vladlen Koltun.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Richter, and Vladlen Koltun

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.880822Z

Source-reported events for the cited work

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Observation ab60de10-120f-4da0-9fa3-d6bd04ef1b7d · outbound

This paper cites Reid, and John J.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Reid, and John J

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.867235Z

Source-reported events for the cited work

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Observation a72c75bd-0b90-4815-9143-84ef80bbadff · outbound

This paper cites Real-Time Neural Light Field on Mobile Devices.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Real-Time Neural Light Field on Mobile Devices

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.853465Z

Source-reported events for the cited work

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Observation bd903b26-9f92-4b52-a2f6-8db83e05d1f9 · outbound

This paper cites Pointersect: Neural Ren- dering with Cloud-Ray Intersection.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Pointersect: Neural Ren- dering with Cloud-Ray Intersection

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.839406Z

Source-reported events for the cited work

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Observation 0129f079-70be-4f44-9ab0-367b8d64c409 · outbound

This paper cites PGSR: Planar-based Gaussian Splatting for Efficient and High-Fidelity Surface Reconstruction.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models PGSR: Planar-based Gaussian Splatting for Efficient and High-Fidelity Surface Reconstruction

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.825411Z

Source-reported events for the cited work

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Observation 8c1a0b80-cbcc-41d9-9591-440012b2808f · outbound

This paper cites 3d re- construction with fast dipole sums.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models 3d re- construction with fast dipole sums

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.811146Z

Source-reported events for the cited work

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Observation 703a58cc-e916-4412-bad2-fa233dbba68f · outbound

This paper cites VCR-GauS: View Consis- tent Depth-Normal Regularizer for Gaussian Surface Recon- struction.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models VCR-GauS: View Consis- tent Depth-Normal Regularizer for Gaussian Surface Recon- struction

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.797499Z

Source-reported events for the cited work

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Observation cdf176ce-947d-40d4-b90e-79e51ecc054f · outbound

This paper cites Learning Implicit Fields for Generative Shape Modeling.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Learning Implicit Fields for Generative Shape Modeling

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.783885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 40eaf655-61cd-41a9-b54a-9df652bba2c9 · outbound

This paper cites Neu- ral Unsigned Distance Fields for Implicit Function Learning.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Neu- ral Unsigned Distance Fields for Implicit Function Learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.770344Z

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Observation 2960957f-3eb6-4fee-b279-1fa472b6ad76 · outbound

This paper cites Choy, Danfei Xu, JunYoung Gwak, Kevin Chen, and Silvio Savarese.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Choy, Danfei Xu, JunYoung Gwak, Kevin Chen, and Silvio Savarese

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.756294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 18c8f6d5-b975-48ca-ab91-cfda5f54e159 · outbound

This paper cites Depth-Regularized Optimization for 3D Gaussian Splatting in Few-Shot Images.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Depth-Regularized Optimization for 3D Gaussian Splatting in Few-Shot Images

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.742272Z

Source-reported events for the cited work

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Observation 96ae5d91-60e8-4da6-9544-b15c9ee5a1ce · outbound

This paper cites Chang, Manolis Savva, Maciej Hal- ber, Thomas Funkhouser, and Matthias Nießner.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Chang, Manolis Savva, Maciej Hal- ber, Thomas Funkhouser, and Matthias Nießner

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.727942Z

Source-reported events for the cited work

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Observation 4f9ece06-969b-4ff5-9d83-213cf1be39b8 · outbound

This paper cites A Point Set Generation Network for 3D Object Reconstruction from a Single Image.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models A Point Set Generation Network for 3D Object Reconstruction from a Single Image

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.714188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a0de194f-c151-40e7-a0d2-dbfd8de80c90 · outbound

This paper cites Trim 3D Gaussian Splatting for Accurate Geometry Representation.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Trim 3D Gaussian Splatting for Accurate Geometry Representation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T20:53:09.440246Z

Source-reported events for the cited work

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Observation 94bef3d3-836c-4c5a-964a-e9d971e1bc96 · outbound

This paper cites SIGNET: Ef- ficient Neural Representation for Light Fields.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models SIGNET: Ef- ficient Neural Representation for Light Fields

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.699495Z

Source-reported events for the cited work

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Observation 5102c524-8311-4d70-9688-73c525469361 · outbound

This paper cites PRIF: Primary Ray-based Implicit Function.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models PRIF: Primary Ray-based Implicit Function

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.685835Z

Source-reported events for the cited work

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Observation 541132da-d75d-4293-84fe-9cea10e69186 · outbound

This paper cites State of the Art on Neural Rendering.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models State of the Art on Neural Rendering

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.671609Z

Source-reported events for the cited work

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Observation ad2bd80c-b1fa-429e-802e-1ca838a42126 · outbound

This paper cites 3D Semantic Segmentation with Submanifold Sparse Convolutional Networks.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models 3D Semantic Segmentation with Submanifold Sparse Convolutional Networks

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.658069Z

Source-reported events for the cited work

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Observation ebd0ae38-c632-421e-808a-86aa9b7a381e · outbound

This paper cites Grossman and William J.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Grossman and William J

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.643696Z

Source-reported events for the cited work

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Observation 7f701c50-e1fa-42a2-957c-6866fddf52e1 · outbound

This paper cites SuGaR: Surface- Aligned Gaussian Splatting for Efficient 3D Mesh Recon- struction and High-Quality Mesh Rendering.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models SuGaR: Surface- Aligned Gaussian Splatting for Efficient 3D Mesh Recon- struction and High-Quality Mesh Rendering

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.630190Z

Source-reported events for the cited work

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Observation 7681658a-3f1c-4df7-92df-e69700c3384c · outbound

This paper cites Image-based 3D Object Reconstruction: State-of-the-Art and Trends in the Deep Learning Era.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Image-based 3D Object Reconstruction: State-of-the-Art and Trends in the Deep Learning Era

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.616132Z

Source-reported events for the cited work

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Observation c054243a-156e-417a-a190-ae05ff3a646d · outbound

This paper cites 2D Gaussian Splatting for Geometrically Ac- curate Radiance Fields.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models 2D Gaussian Splatting for Geometrically Ac- curate Radiance Fields

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.601663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6ce77449-47f5-44d4-9271-d522c9f8c8c1 · outbound

This paper cites FatesGS: Fast and Accurate Sparse-View Sur- face Reconstruction using Gaussian Splatting with Depth- Feature Consistency.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models FatesGS: Fast and Accurate Sparse-View Sur- face Reconstruction using Gaussian Splatting with Depth- Feature Consistency

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.587865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e1f888a0-e123-4afc-882f-fb8a0417a30c · outbound

This paper cites 3DFIRES: Few Image 3D REconstruction for Scenes with Hidden Sur- face.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models 3DFIRES: Few Image 3D REconstruction for Scenes with Hidden Sur- face

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.574463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2a0aac2d-15c8-41de-8c4d-c733317ae1f1 · outbound

This paper cites Neu- ral 3D Mesh Renderer.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Neu- ral 3D Mesh Renderer

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.560928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5f5043cc-c9a5-421a-b11b-b919ef453103 · outbound

This paper cites 3D Gaussian Splatting for Real-Time Radiance Field Rendering.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models 3D Gaussian Splatting for Real-Time Radiance Field Rendering

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.547545Z

Source-reported events for the cited work

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Observation aeb3a30e-96e2-48d2-8027-73fe5770601e · outbound

This paper cites Approximate Differ- entiable Rendering with Algebraic Surfaces.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Approximate Differ- entiable Rendering with Algebraic Surfaces

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.533216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 31a4ac84-3ada-48fe-89e2-ac410964664b · outbound

This paper cites Di- rected Ray Distance Functions for 3D Scene Reconstruction.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Di- rected Ray Distance Functions for 3D Scene Reconstruction

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.519126Z

Source-reported events for the cited work

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Observation 78de5fce-f7f2-4555-84cf-eb6a3cb7dc33 · outbound

This paper cites DNGaussian: Optimizing Sparse-View 3D Gaussian Radiance Fields with Global-Local Depth Nor- malization.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models DNGaussian: Optimizing Sparse-View 3D Gaussian Radiance Fields with Global-Local Depth Nor- malization

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.504450Z

Source-reported events for the cited work

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Observation 1516e882-c66a-4cdb-a9f5-4336341265c3 · outbound

This paper cites NeuLF: Efficient Novel View Synthesis with Neural 4D Light Field.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models NeuLF: Efficient Novel View Synthesis with Neural 4D Light Field

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.489985Z

Source-reported events for the cited work

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Observation cdd85163-d8f6-46fa-a67e-df4864f06934 · outbound

This paper cites MVSGaussian: Fast Generalizable Gaussian Splatting Re- construction from Multi-View Stereo.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models MVSGaussian: Fast Generalizable Gaussian Splatting Re- construction from Multi-View Stereo

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.476075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 31400501-3e7e-47bd-a3a1-1ccdfe49602d · outbound

This paper cites RayDF: Neural Ray-surface Distance Fields with Multi-view Consistency.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models RayDF: Neural Ray-surface Distance Fields with Multi-view Consistency

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.462459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2f9dbb9c-bc50-4b20-9fe2-63422bbd666b · outbound

This paper cites MultiScan: Scalable RGBD scanning for 3D environments with articulated objects.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models MultiScan: Scalable RGBD scanning for 3D environments with articulated objects

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.447853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 78ff3404-31dd-4747-a59e-48f5595fe451 · outbound

This paper cites Occupancy Net- works: Learning 3D Reconstruction in Function Space.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Occupancy Net- works: Learning 3D Reconstruction in Function Space

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.434161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cb532701-f80e-49c0-bb77-b43e577e4d6f · outbound

This paper cites Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.419735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e8044d51-e6b8-4e2f-9ca7-09bc330e02e5 · outbound

This paper cites Instant neural graphics primitives with a mul- tiresolution hash encoding.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Instant neural graphics primitives with a mul- tiresolution hash encoding

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.405583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 58be36c1-c8a0-4ecf-aaf6-edacb9b5e14a · outbound

This paper cites Neural Point Light Fields.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Neural Point Light Fields

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.391315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5590cd48-1965-41a2-a064-4872947d31ce · outbound

This paper cites GigaGS: Scaling up Planar-Based 3D Gaussians for Large Scene Surface Reconstruction.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models GigaGS: Scaling up Planar-Based 3D Gaussians for Large Scene Surface Reconstruction

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-05T20:53:09.539752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ed51b9f-3feb-422e-9d7d-a87c9a56423e · outbound

This paper cites A Survey of Structure from Motion.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models A Survey of Structure from Motion

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.375301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e3b4ad0f-dad4-4e2c-a5e1-b389d0150bd2 · outbound

This paper cites DeepSDF: Learning Continuous Signed Distance Functions for Shape Represen- tation.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models DeepSDF: Learning Continuous Signed Distance Functions for Shape Represen- tation

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.358798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c31ae997-4ca6-4ac2-98d2-a4799a6e53fb · outbound

This paper cites an unresolved cited work.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-08-05T20:53:10.342527Z

Source-reported events for the cited work

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Observation 542db121-0f18-4deb-b7e5-9fbe26e28203 · outbound

This paper cites Towards Robust Monocu- lar Depth Estimation: Mixing Datasets for Zero-Shot Cross- Dataset Transfer.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Towards Robust Monocu- lar Depth Estimation: Mixing Datasets for Zero-Shot Cross- Dataset Transfer

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.327510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7521f712-80a8-4d9a-9aa4-c53c4a596b43 · outbound

This paper cites Neural Vector Fields for Surface Rep- resentation and Inference.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Neural Vector Fields for Surface Rep- resentation and Inference

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.312814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d8cfd8cf-a0b9-482d-982a-81dfa642861f · outbound

This paper cites Object Space EW A Surface Splatting: A Hardware Accelerated Ap- proach to High Quality Point Rendering.Computer Graphics Forum, 2003.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Object Space EW A Surface Splatting: A Hardware Accelerated Ap- proach to High Quality Point Rendering.Computer Graphics Forum, 2003

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.298487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7f7e0538-d84b-45a3-894e-6d9647047c14 · outbound

This paper cites Tenenbaum, and Fr ´edo Durand.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Tenenbaum, and Fr ´edo Durand

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.284254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c297cadd-b8f5-4139-9dd5-eae41ec49ee4 · outbound

This paper cites GVKF: Gaus- sian V oxel Kernel Functions for Highly Efficient Surface Re- construction in Open Scenes.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models GVKF: Gaus- sian V oxel Kernel Functions for Highly Efficient Surface Re- construction in Open Scenes

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.270758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a55483d7-a060-4030-a29c-b56db7fa6c5d · outbound

This paper cites Light Field Neural Rendering.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Light Field Neural Rendering

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.257072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2748f2ad-69e3-4eef-90a3-27245efba3af · outbound

This paper cites MARF: The Medial Atom Ray Field object representation.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models MARF: The Medial Atom Ray Field object representation

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.244521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d97f6d95-ba2f-499d-be9b-09ceefe2b5b9 · outbound

This paper cites Towards Multi-view Consistency in Neural Ray Fields using Paramet- ric Medial Surfaces.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Towards Multi-view Consistency in Neural Ray Fields using Paramet- ric Medial Surfaces

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.231074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1deeb845-cd32-44f0-83ed-538264873c88 · outbound

This paper cites Octree Generating Networks: Efficient Convolutional Archi- tectures for High-resolution 3D Outputs.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Octree Generating Networks: Efficient Convolutional Archi- tectures for High-resolution 3D Outputs

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.217746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6c6c643e-ded2-4268-8b12-0b55e2285102 · outbound

This paper cites Barron, Gordon Wetzstein, Michael Zollhoefer, and Vladislav Golyanik.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Barron, Gordon Wetzstein, Michael Zollhoefer, and Vladislav Golyanik

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.203197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 13d6f7d9-2d68-4f33-8e49-d7a64c753bbe · outbound

This paper cites GRF: Learning a General Ra- diance Field for 3D Representation and Rendering.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models GRF: Learning a General Ra- diance Field for 3D Representation and Rendering

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.187869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3a69353f-dd27-4097-9937-5324748b06b5 · outbound

This paper cites DN-Splatter: Depth and Normal Priors for Gaussian Splatting and Meshing.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models DN-Splatter: Depth and Normal Priors for Gaussian Splatting and Meshing

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.172746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fcd8ddf2-5dd6-4345-b095-385aac3d015e · outbound

This paper cites RangeUDF: Semantic Surface Reconstruction from 3D Point Clouds.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models RangeUDF: Semantic Surface Reconstruction from 3D Point Clouds

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-08-05T20:53:09.813860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 17442c2e-dad9-42ef-825e-f73ee1f61b8c · outbound

This paper cites PFGS: High Fidelity Point Cloud Rendering via Feature Splatting.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models PFGS: High Fidelity Point Cloud Rendering via Feature Splatting

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.158129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 58d3d06f-0359-448d-a317-d6401276dac1 · outbound

This paper cites NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-05T20:53:09.612525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1809dfe8-6f48-4766-86aa-f7e437dbb92f · outbound

This paper cites 3D Representation Methods: A Survey.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models 3D Representation Methods: A Survey

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-05T20:53:09.617105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0853c983-65ed-4db3-af8b-e44b1e134a9e · outbound

This paper cites GS2Mesh: Surface Reconstruction from Gaussian Splatting via Novel Stereo Views.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models GS2Mesh: Surface Reconstruction from Gaussian Splatting via Novel Stereo Views

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.142304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1fad8a0f-3c46-4fb2-8e87-542cc8e1a05f · outbound

This paper cites Surface Recon- struction from 3D Gaussian Splatting via Local Structural Hints.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Surface Recon- struction from 3D Gaussian Splatting via Local Structural Hints

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.128303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0d6d2014-2e60-4534-9d69-ceab06c224ef · outbound

This paper cites GaussianRoom: Improving 3D Gaussian Splatting with SDF Guidance and Monocular Cues for Indoor Scene Reconstruction.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models GaussianRoom: Improving 3D Gaussian Splatting with SDF Guidance and Monocular Cues for Indoor Scene Reconstruction

Reference 64

Resolution: verified exact; local_arxiv, observed 2026-08-05T20:53:09.762317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6d0baff7-cc26-425a-8af2-b54110b9c1ef · outbound

This paper cites Neural Fields in Visual Computing and Beyond.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Neural Fields in Visual Computing and Beyond

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.114467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 970e55ed-0838-417c-8b3a-c6872ed9389e · outbound

This paper cites DepthSplat: Connecting Gaussian Splatting and Depth.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models DepthSplat: Connecting Gaussian Splatting and Depth

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.099680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6c6f0a9c-f08d-40bd-8e3d-713000ea05cf · outbound

This paper cites Dense 3D Object Reconstruction from a Sin- gle Depth View.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Dense 3D Object Reconstruction from a Sin- gle Depth View

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.085700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e83b6ed1-a339-482d-82b6-c975c4e05283 · outbound

This paper cites Robust Attentional Aggregation of Deep Feature Sets for Multi-view 3D Reconstruction.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Robust Attentional Aggregation of Deep Feature Sets for Multi-view 3D Reconstruction

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.070844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 39ac2371-bbbd-4149-bc59-13d7f9bb001e · outbound

This paper cites Depth Any- thing V2.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Depth Any- thing V2

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.055285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fab80927-359c-4ae9-90e6-bf7da80c2b7e · outbound

This paper cites Neural Vector Fields: Implicit Representation by Explicit Learning.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Neural Vector Fields: Implicit Representation by Explicit Learning

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.040257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f10ffb01-9e16-4d9d-8508-629b771dab1d · outbound

This paper cites ScanNet++: A High-Fidelity Dataset of 3D Indoor Scenes.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models ScanNet++: A High-Fidelity Dataset of 3D Indoor Scenes

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.023563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8026b87b-9cf6-488f-b9e2-db9fb6b13823 · outbound

This paper cites Ray-Distance V olume Rendering for Neural Scene Re- construction.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Ray-Distance V olume Rendering for Neural Scene Re- construction

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:10.008290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cc5c772b-a659-446b-8ddc-3dd62fe65646 · outbound

This paper cites GSDF: 3DGS Meets SDF for Improved Rendering and Reconstruction.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models GSDF: 3DGS Meets SDF for Improved Rendering and Reconstruction

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:09.992158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation da3c17e1-1969-4404-9c18-019abae5993c · outbound

This paper cites Gaussian Opacity Fields: Efficient and Compact Surface Reconstruc- tion in Unbounded Scenes.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Gaussian Opacity Fields: Efficient and Compact Surface Reconstruc- tion in Unbounded Scenes

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:09.977326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ec95fa07-9190-4fb3-82dc-9c90ac1fe8f6 · outbound

This paper cites RaDe-GS: Rasterizing Depth in Gaussian Splatting.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models RaDe-GS: Rasterizing Depth in Gaussian Splatting

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-05T20:53:09.674855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0513b9cb-e327-40ef-bad5-b549758797c0 · outbound

This paper cites Quadratic Gaussian Splatting: High Quality Surface Reconstruction with Second-order Geometric Primitives.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Quadratic Gaussian Splatting: High Quality Surface Reconstruction with Second-order Geometric Primitives

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-05T20:53:09.679678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17cea0ff-391b-43cb-b983-32f247ce006e · outbound

This paper cites Surface splatting.

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Surface splatting

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:53:09.962041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

Observation d4f82593-c87e-4fb9-9005-e48f4a28ba0c · inbound

Hybrid Architectures for Language Models: Systematic Analysis and Design Insights cites this paper.

Hybrid Architectures for Language Models: Systematic Analysis and Design Insights Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-18T10:21:14.977133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation eeeef792-d4a8-40f5-9d24-84b1df4d6a67 · inbound

On the Reasoning Abilities of Masked Diffusion Language Models cites this paper.

On the Reasoning Abilities of Masked Diffusion Language Models Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T06:56:01.536166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 990f7d6a-f121-4932-9ec3-3363c7c2146e · inbound

Kimi Linear: An Expressive, Efficient Attention Architecture cites this paper.

Kimi Linear: An Expressive, Efficient Attention Architecture Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Reference 92

Resolution: verified exact; arxiv_id, observed 2026-05-13T23:49:10.800523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e44bbf8d-916b-4222-9cb8-1119b1d06ad6 · inbound

Attention Sink in Transformers: A Survey on Utilization, Interpretation, and Mitigation cites this paper.

Attention Sink in Transformers: A Survey on Utilization, Interpretation, and Mitigation Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:05:58.088861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cdd8c52b-8fbc-4252-8e06-b4b9dc3630ef · inbound

LayerBoost: Layer-Aware Attention Reduction for Efficient LLMs cites this paper.

LayerBoost: Layer-Aware Attention Reduction for Efficient LLMs Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T22:49:15.717399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a5dd80c5-4ee1-4332-ac86-2b0037e073ae · inbound

PSD: Pushing the Pareto Frontier of Diffusion LLMs via Parallel Speculative Decoding cites this paper.

PSD: Pushing the Pareto Frontier of Diffusion LLMs via Parallel Speculative Decoding Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-20T19:08:54.242892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 77bc78ef-3414-4038-82cb-22fffc078316 · inbound

Morphing into Hybrid Attention Models cites this paper.

Morphing into Hybrid Attention Models Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-06-30T08:44:28.039242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.