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Paper Citation Record · LEDGER

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views

As of 8 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2606.29513.

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

pith.paper-citation-record.v1
2606.29513 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T07:25:31.066786Z

measured 36 of 36 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

  • verified exact4
  • verified fuzzy0
  • unresolved32
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c2c552cf-02ff-41cd-add9-005a78a88fef · outbound

This paper cites C3G: Learning compact 3D representations with 2K gaussians.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views C3G: Learning compact 3D representations with 2K gaussians

Reference 1

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:061b22cfd661015329a6d3e16939436c70cabed9b3e348d2db6f59e77f269362

Observation 9bc8c2f5-8db6-445f-9127-416118b2fe5e · outbound

This paper cites Barron, Ben Mildenhall, Dor Verbin, Pratul P.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Barron, Ben Mildenhall, Dor Verbin, Pratul P

Reference 2

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:305a8855d00882ec70915b33dcefeba50c687acea4ff820ca0be6d76193b752f

Observation a6f95fe9-b2cd-4e8f-8a2a-e4a0245380cf · outbound

This paper cites End-to-end object detection with transformers.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views End-to-end object detection with transformers

Reference 3

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:c3ed950f0d435ee1c948c7b8a975253098a276da587ac78437ad55c52b18a1a1

Observation d5015bf9-e2e3-4df1-a46a-e59d7b075cfa · outbound

This paper cites Lifting by gaussians: A simple, fast and flexible method for 3D instance segmentation.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Lifting by gaussians: A simple, fast and flexible method for 3D instance segmentation

Reference 4

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:3365838c52600d9f71433b1204b1ae52969704d0af77b36d4c16689bf1757e55

Observation 524f377a-869f-4a4f-a254-d822d6ff4cb0 · outbound

This paper cites pixelsplat: 3d gaussian splats from image pairs for scalable generalizable 3d reconstruction.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views pixelsplat: 3d gaussian splats from image pairs for scalable generalizable 3d reconstruction

Reference 5

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:f59d3e593faad50797257d61365bcf52c5ae445ca02512f66a731cfd18a70857

Observation 2f8966ba-aca9-434c-bff0-f1713cdb7f14 · outbound

This paper cites Mvsplat: Efficient 3d gaussian splatting from sparse multi-view images.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Mvsplat: Efficient 3d gaussian splatting from sparse multi-view images

Reference 6

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:904a6c8cefec46f2451cdd6a8ea7936254b013e6e214c2042f673e093562e116

Observation 33771025-4bfe-4a1f-8e20-16b1bd7dcd71 · outbound

This paper cites Schwing, Alexander Kirillov, and Rohit Girdhar.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Schwing, Alexander Kirillov, and Rohit Girdhar

Reference 7

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:dfa6c1ae50d9aa61b75ef8b85428cbcebcd81e173d26fc31815b4957afe6f228

Observation c05dd16f-6035-4cc4-8cb2-8bf448478c00 · outbound

This paper cites Scannet: Richly-annotated 3d reconstructions of indoor scenes.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Scannet: Richly-annotated 3d reconstructions of indoor scenes

Reference 8

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:53b40677d07b59d92bd3617197e3f5b5675243a37d662edb5d4ad689a3d1d61a

Observation ee73b5fc-7ae2-4599-86e8-90de98c9c548 · outbound

This paper cites Large spatial model: End-to-end unposed images to semantic 3d.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Large spatial model: End-to-end unposed images to semantic 3d

Reference 9

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:310512402de8c1f5dd7d85d7c9fb0edd1d7c7e44b7ce496df04b893761c9d6ff

Observation 703c8053-6dad-4342-ae5d-6ab97df0e74c · outbound

This paper cites Scene-Agnostic Object-Centric Representation Learning for 3D Gaussian Splatting.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Scene-Agnostic Object-Centric Representation Learning for 3D Gaussian Splatting

Reference 10

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local_arxiv, observed 2026-06-30T07:34:22.080372Z

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

source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:4a8800f5f0ad9e362a1298ccb78e6125ec15c876477698605750931da0c77983

Observation af82ab69-c39f-4f49-b6aa-69bd1905ecd0 · outbound

This paper cites Anysplat: Feed-forward 3d gaussian splatting from unconstrained views.ACM Transactions on Graphics (TOG), 44(6):1–16, 2025.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Anysplat: Feed-forward 3d gaussian splatting from unconstrained views.ACM Transactions on Graphics (TOG), 44(6):1–16, 2025

Reference 11

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:5f786aa994446e9206ec82218d6c5de17705619d8d74dd241e3a0e3a15a23010

Observation d88d6897-9317-4409-9019-d30e644a4d00 · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.ACM Trans.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views 3d gaussian splatting for real-time radiance field rendering.ACM Trans

Reference 12

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:a338864e1f1b8d02e513b8edb2eb6adb3b5334e6c8cc90e3e021f9e21a224160

Observation 345b8c84-6815-4805-83c5-ccbad3f4c9a7 · outbound

This paper cites Grounding image matching in 3d with mast3r.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Grounding image matching in 3d with mast3r

Reference 13

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:ff2946d66f0d9001b13e400abd1aca528f686772be6b5deae8dfd27dcce44f7d

Observation ba8509a7-1783-43c4-a790-b034ce69b2aa · outbound

This paper cites Language-driven semantic segmentation.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Language-driven semantic segmentation

Reference 14

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:69b95cbaafd8b1ed9c7f49e8afff1318ccd638a2289fd08b7537e42a09dfe701

Observation 7d672dcc-4128-43a6-8ac0-cb601b2c6da3 · outbound

This paper cites IGGT: Instance-grounded geometry transformer for semantic 3D reconstruction.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views IGGT: Instance-grounded geometry transformer for semantic 3D reconstruction

Reference 15

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:0cd0b62078e87cb85438936609c04c28269469b0869827c7498394744b401525

Observation f3b7b5a3-1b5e-417f-9694-bc14265f3235 · outbound

This paper cites SlotLifter: Slot-guided feature lifting for learning object-centric radiance fields.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views SlotLifter: Slot-guided feature lifting for learning object-centric radiance fields

Reference 16

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:25e178bfbc72455cf1b5b5545d1dc8c5239210e9a32c748905c949a338ad413a

Observation 3a184519-7442-4382-aef1-cd9b55bc3b0e · outbound

This paper cites Object-centric learning with slot attention.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Object-centric learning with slot attention

Reference 17

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:7a44ca9bceefc25e1172cc4aae2230ec12af4542ed2620c57be0214796de18ed

Observation 95a4e091-4873-4c78-9837-1ea1f445e064 · outbound

This paper cites LUDVIG: Learning- free uplifting of 2D visual features to gaussian splatting scenes.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views LUDVIG: Learning- free uplifting of 2D visual features to gaussian splatting scenes

Reference 18

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:bd681e019ccf3a490a02956e6e754a250f339a0484c38581a5b558db36bf0f69

Observation 9cbc4155-04fc-49b6-a5af-15cffb9458bc · outbound

This paper cites V-net: Fully convolutional neural networks for volumetric medical image segmentation.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views V-net: Fully convolutional neural networks for volumetric medical image segmentation

Reference 19

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:80fe236e4d73f79e33a89ace7a98feb584d4d3436e98c72501f08c9e3ec05ecf

Observation d5138a93-e013-4a9d-9cb5-6c0664372f7b · outbound

This paper cites Any3DIS: Class-agnostic 3D instance segmentation by 2D mask tracking.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Any3DIS: Class-agnostic 3D instance segmentation by 2D mask tracking

Reference 20

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:6db1fcac3b2de81edd158d90b04d4842f6b6916235d5407320306668c021fc63

Observation 9e5b7126-3921-45bb-bd40-283a9d56dc93 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views SAM 2: Segment Anything in Images and Videos

Reference 21

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local_arxiv, observed 2026-06-30T07:34:22.085620Z

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.

source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:86abb17b2bdeaa5682669f7d62ab09c3b219799b13451bf7a0340769dbcbb718

Observation f512e97b-11ca-4877-8298-eaaf8dd33115 · outbound

This paper cites Schönberger and Jan-Michael Frahm.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Schönberger and Jan-Michael Frahm

Reference 22

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:5506be87197d6ab3e444076ae62a792c9bbb5b5de6cb3db343754ceb4b7359ac

Observation d2a1894d-dd54-44af-913b-80c4630ee8dc · outbound

This paper cites Trace3D: Consis- tent segmentation lifting via gaussian instance tracing.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Trace3D: Consis- tent segmentation lifting via gaussian instance tracing

Reference 23

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:21b13491708268649108532e2f4c42ebadf87cdbbd062dfb4c207dea48adc7bf

Observation fe1cb805-0a53-4fdf-ae2d-d1684925eaec · outbound

This paper cites Splatt3R: Zero-shot Gaussian Splatting from Uncalibrated Image Pairs.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Splatt3R: Zero-shot Gaussian Splatting from Uncalibrated Image Pairs

Reference 24

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local_arxiv, observed 2026-06-30T07:34:22.083023Z

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.

source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:7e92008ab933809bb8389ea0bf477edc77ebb3c08f082ad71cb66ffebf24723d

Observation cf0eb017-9388-4e11-9045-86d263849aa0 · outbound

This paper cites Uni3R: Unified 3D reconstruction and semantic understanding via generalizable gaussian splatting from unposed multi-view images.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Uni3R: Unified 3D reconstruction and semantic understanding via generalizable gaussian splatting from unposed multi-view images

Reference 25

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:90c12d1377a7b381775e389a4ab1f04c49b362a6705447ffc19498c4c3832939

Observation 24aa1ef5-6f99-4ced-b454-725167659a5f · outbound

This paper cites Sumner, Marc Pollefeys, Federico Tombari, and Francis Engelmann.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Sumner, Marc Pollefeys, Federico Tombari, and Francis Engelmann

Reference 26

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:542265e4e855c510dabccc6a8cb521c7587bb7b20e5af0042a34adb2b54e2ee1

Observation b1902f8b-32cc-49d1-9ff4-95e9f42c2939 · outbound

This paper cites Vggt: Visual geometry grounded transformer.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Vggt: Visual geometry grounded transformer

Reference 27

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:77e3e59f0fd7fdf7996c995157bed2e9d3019204b0b2c262b7b9d2bf5f1d057e

Observation 71b32977-b18d-4d30-ac4a-d1d241d94121 · outbound

This paper cites Dust3r: Geometric 3d vision made easy.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Dust3r: Geometric 3d vision made easy

Reference 28

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:c658a32cfee2cddbd2bc0b521840e100680fe2401b6f19e1e62276673670a3e1

Observation c0fef94e-fc9c-47b1-ae1e-1819b0488218 · outbound

This paper cites SAM3D: Segment Anything in 3D Scenes.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views SAM3D: Segment Anything in 3D Scenes

Reference 29

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arxiv_id, observed 2026-06-30T07:34:22.088631Z

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.

source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:d6f1f66de16fa5d0f292b8b985de51488cb05fd2d83daa796c490594d3b3c66e

Observation a6b284b4-7955-46ee-a410-e287f1918c62 · outbound

This paper cites No pose, no problem: Surprisingly simple 3d gaussian splats from sparse unposed images.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views No pose, no problem: Surprisingly simple 3d gaussian splats from sparse unposed images

Reference 30

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:97d1552279d584cd05510e1432a2d69894895ba7eab5a86ddd83e40cec4c99bf

Observation 45548888-0590-48c4-9054-3799e43836d1 · outbound

This paper cites Gaussian grouping: Segment and edit anything in 3d scenes.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Gaussian grouping: Segment and edit anything in 3d scenes

Reference 31

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:354a417084072eb734e9baf741cd704ac77eb8d9780b568a50c45a7f95651baf

Observation 75467a71-f315-4f43-8b59-74d134c7530f · outbound

This paper cites gsplat: An open-source library for gaussian splatting.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views gsplat: An open-source library for gaussian splatting

Reference 32

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:eacd14535ed4bf74175ea2f5a850be24af6056640a502e05b25c3ceb7c9f6032

Observation b98364ff-4275-4fef-93f0-a45f32ea3ff1 · outbound

This paper cites kMaX-DeepLab: k-means mask transformer.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views kMaX-DeepLab: k-means mask transformer

Reference 33

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:b69a2817f172c10989de06c8b50f23345d985c9b24c21c247ef456a21df67c19

Observation a0dc898f-2125-4968-beec-fb3650182909 · outbound

This paper cites Stereo magnification: Learning view synthesis using multiplane images.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views Stereo magnification: Learning view synthesis using multiplane images

Reference 34

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:628eb5ae7c794fd14e6da83af2184aa10cbddfaec166e112cf93807af6e7477e

Observation cf253710-3ab2-44f2-946f-d24eec4e45b1 · outbound

This paper cites ObjectGS: Object-aware scene reconstruction and scene understanding via gaussian splatting.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views ObjectGS: Object-aware scene reconstruction and scene understanding via gaussian splatting

Reference 35

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source=pdf_text observed=2026-06-30T07:25:31.066786Z digest=sha256:c01f22b329e286448720180df2c86e59e08ef8c208b25d44294f9173d20e3e19

Observation 2d7fab7b-4030-45f5-8e05-c72cda092415 · outbound

This paper cites PanSt3R: Multi-view consistent panoptic segmentation.

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views PanSt3R: Multi-view consistent panoptic segmentation

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