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Paper Citation Record · LEDGER

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo

As of 19 August 2026, this Paper Citation Record lists 81 of 81 outbound references and 9 inbound Pith citation observations for arXiv:2412.05268.

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

pith.paper-citation-record.v1
2412.05268 v1

Coverage vector

measured 81 of 81 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:57:12.539343Z

measured 90 of 90 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:51:05.402554Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:40:01.069980Z

Reference resolution

81 of 81 outbound references displayed

  • verified exact3
  • verified fuzzy42
  • unresolved32
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c5e45e6c-acd0-4b95-aa75-26954773bbde · outbound

This paper cites write newline.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo write newline

Reference 1

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unresolved
no resolver link, observed 2026-08-11T20:57:12.244780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.244780Z digest=sha256:050aad6c6866310edd50122488e335c350a1cc6fb54fea7d76ef86ce60b5a577

Observation 1faf6555-e515-4e9c-b68b-2d41db11b1a8 · outbound

This paper cites @esa (Ref.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo @esa (Ref

Reference 2

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unresolved
no resolver link, observed 2026-08-11T20:57:12.249628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.249628Z digest=sha256:42760cc2d2955913f52b3174d56e26f343379848eb59425e9f9f244d7d63b526

Observation 249dfaab-0502-486d-a70d-5f869664e266 · outbound

This paper cites an unresolved cited work.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Unresolved cited work

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.253294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.253294Z digest=sha256:6a7b4b7fd495b2e60d1633ddae89b0c7ac4ef838283e730400aa96f834faf3b8

Observation 03cd4437-d790-4cd1-945c-8e288d2fa7d4 · outbound

This paper cites an unresolved cited work.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-11T20:57:13.631135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.257250Z digest=sha256:e1c7cfe90d3251e10b2263f1e3684f288ca06833ffe5e528973a676f0534038f

Observation 954b52c8-adea-4f44-bf01-e9c96c8874a0 · outbound

This paper cites Accelerated Analog Neuromorphic Computing.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Accelerated Analog Neuromorphic Computing

Reference 5

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unresolved
no resolver link, observed 2026-08-11T20:57:12.261603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.261603Z digest=sha256:95b74580ec834f8a4abe5315f43faf294e0def305a50f33e2e8002d618c7b48e

Observation 87e8edc2-f6c6-417a-9e77-265297dcc0ef · outbound

This paper cites Deep ViT Features as Dense Visual Descriptors.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Deep ViT Features as Dense Visual Descriptors

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.265574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.265574Z digest=sha256:9d33dc69dd06dc98db9c9cd9bd9c210609b08b5a1d93d053d5ff33097603adee

Observation aadb55f9-2a1c-4e5d-9e66-c4e61b892cab · outbound

This paper cites The wave kernel signature: A quantum mechanical approach to shape analysis.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo The wave kernel signature: A quantum mechanical approach to shape analysis

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.619127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.269692Z digest=sha256:0705e4e705d1acb714ec5b2ae65e020f28db8ae9f7e5f49cbca90378b54f83a2

Observation e0e5ef3b-e4b2-4545-b064-767ec5222441 · outbound

This paper cites Affordances from human videos as a versatile representation for robotics.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Affordances from human videos as a versatile representation for robotics

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.608943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.273185Z digest=sha256:a0745ad4bda0da5e333a0f541fde5fd438e930a0eaf528765be5568f1404ccf4

Observation 9d188101-fd07-4b9e-9615-3bb351d5f75f · outbound

This paper cites Bernardini, J.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Bernardini, J

Reference 9

Resolution
metadata mismatch
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.277305Z digest=sha256:44d2f30294a4ddedf08b60480042850290ab86775baf9916ad4f2402ce62b722

Observation e7a4fe11-8fb6-4cec-8bcf-1bb7c9a272ff · outbound

This paper cites Faust: Dataset and evaluation for 3d mesh registration.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Faust: Dataset and evaluation for 3d mesh registration

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.597762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.281420Z digest=sha256:76e299796d8424f717c115f5437f2f99ca47cf8853286df5a0e1f70a02b77a2a

Observation cce88a7e-5072-4f35-a3cd-61153c28e12c · outbound

This paper cites an unresolved cited work.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Unresolved cited work

Reference 11

Resolution
malformed identifier
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.285023Z digest=sha256:8cde91bac7e17a4535d4a55c9cfd02c05ba82597e91b86529cfbea0e56c65247

Observation 7d197a33-ef73-4c3a-86ce-2b97251cb79d · outbound

This paper cites Bronstein, Michael M.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Bronstein, Michael M

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.575210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.288518Z digest=sha256:ea72fd126dcbc5c48bfe4e2e4d68f57f4901680d44b4644148de0c377f4fffd5

Observation 1bcc37f6-ff88-476d-9196-816754b231b0 · outbound

This paper cites Unsupervised deep multi-shape matching.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Unsupervised deep multi-shape matching

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.562562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.291894Z digest=sha256:7f602c0e204c08bbb18f18d990839bb020c09dcbbfae1ae26d99735b541e024a

Observation dfe91794-3dfd-4b5e-aed7-5143889d59fb · outbound

This paper cites Unsupervised Learning of Robust Spectral Shape Matching.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Unsupervised Learning of Robust Spectral Shape Matching

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.295212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.295212Z digest=sha256:a13603f54429b3ecd421462f7be21a4225dce3244c21060fbf07a31547114c4b

Observation 2ad860cb-bdf1-4e1f-baa2-30c471b3dcbb · outbound

This paper cites Emerging properties in self-supervised vision transformers.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Emerging properties in self-supervised vision transformers

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.551548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.298962Z digest=sha256:a1d1676f5a65cb6d1b2f46bd4ff9a3729947472d776046b2375fead163258354

Observation 668ca848-34d5-4064-8824-e15ccab7e92a · outbound

This paper cites Zero-shot image feature consensus with deep functional maps.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Zero-shot image feature consensus with deep functional maps

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.541303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.302249Z digest=sha256:0f90dfff6e08a9191418eb7f46cd2c7a79adbca9813b84239fa5af181fe3ba6f

Observation cec5502c-76a9-4ef5-accb-f16a20b9316f · outbound

This paper cites Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.308966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.308966Z digest=sha256:43fe7e0257a245aec83cfdec88bedd1efb0e745227077180f615d82b4fe673a0

Observation 3cfcdfbf-db40-4336-ad46-87a864e85545 · outbound

This paper cites Reducing the Barrier to Entry of Complex Robotic Software: a MoveIt! Case Study.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Reducing the Barrier to Entry of Complex Robotic Software: a MoveIt! Case Study

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.313396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.313396Z digest=sha256:711570ac2d3e24b5e90bdeec68f423e44af759bda0075159d0a809d478bf3a85

Observation 5af76bba-2f13-42b7-8e7c-bc7dfc8d67d3 · outbound

This paper cites Geodesics in Heat.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Geodesics in Heat

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-11T20:57:12.954495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.317551Z digest=sha256:50add59a8f4cc07118cb99ffa96652421a8736f4f3f4628d439c1111c3b53a6c

Observation a2faa9cd-4cc3-43d6-bb62-aca7ddcbba6d · outbound

This paper cites Objaverse-XL: A Universe of 10M+ 3D Objects.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Objaverse-XL: A Universe of 10M+ 3D Objects

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.321260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.321260Z digest=sha256:3c2801160cf660ce0ffd759b235bd8c4de60b920f4554bdd371631d244b697b2

Observation 1e77e7bd-e71f-43e6-a7fd-e2c8c4a497c9 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Imagenet: A large-scale hierarchical image database

Reference 21

Resolution
malformed identifier
no resolver link, observed 2026-08-11T20:57:12.324597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.324597Z digest=sha256:3be6752ed75f69836fc7b3f3922cc547301fe0aefc4a9735759632705dd50688

Observation cbe80c7a-f70b-4ad1-8755-c7dddea4bb91 · outbound

This paper cites Deep geometric functional maps: Robust feature learning for shape correspondence.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Deep geometric functional maps: Robust feature learning for shape correspondence

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.530414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.328266Z digest=sha256:6c7893f1bf652e9c8fd3154f0f273d591b3305a13bbe606e6f92a11637e0e9e3

Observation c2211a54-f3af-4061-9bb3-69a6503d7595 · outbound

This paper cites Diffusion 3D Features (Diff3F): Decorating Untextured Shapes with Distilled Semantic Features.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Diffusion 3D Features (Diff3F): Decorating Untextured Shapes with Distilled Semantic Features

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-11T20:57:12.860686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.331478Z digest=sha256:44f449f92d17ae40ba6e776caf675c414f52010f7fcb96467045f2857a308738

Observation 17ccf17c-0e73-4337-9910-bee137064c3b · outbound

This paper cites Dyke, Caleb Stride, Yu-Kun Lai, and Paul L.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Dyke, Caleb Stride, Yu-Kun Lai, and Paul L

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.519430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.334956Z digest=sha256:8daf7ac46acf2415bb221148431a0fccf59cc598d93d58bc0c798e64771cfabe

Observation 632073d8-7053-460e-8cd6-8fb0a8cdd27a · outbound

This paper cites Anygrasp: Robust and efficient grasp perception in spatial and temporal domains.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Anygrasp: Robust and efficient grasp perception in spatial and temporal domains

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.508688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.338260Z digest=sha256:4d95c3582ffd99d36495891f5465452ceaf850f46d62ed8ec4ddb0f2e8e6d6f7

Observation 06970799-794e-4f9e-bbe8-febfcd84ce1a · outbound

This paper cites Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.341567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.341567Z digest=sha256:4755d7292a261520fc98d1a3db513fcd3a156ba21140b94afb609c79e07f32f8

Observation c9ee3833-da66-4223-98b4-2e4e65a5d0fb · outbound

This paper cites Brandt, Axel Feldmann, Zhoutong Zhang, and William T.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Brandt, Axel Feldmann, Zhoutong Zhang, and William T

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.496972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.345415Z digest=sha256:bff192095c0a29e28bbd761da2301d562b9118e0dc6cce6d3e6bcfe5f23754ac

Observation ac0a1d67-ba0d-43f0-af3c-858b4403a6f5 · outbound

This paper cites Riemann: Near real-time se (3)-equivariant robot manipulation without point cloud segmentation.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Riemann: Near real-time se (3)-equivariant robot manipulation without point cloud segmentation

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.485375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.348586Z digest=sha256:77021ed2fc72ba89a369a924b60807a515a366623f360da35a514b02ff935226

Observation dccea46c-a3a5-4ee3-8445-15a85ffb69c5 · outbound

This paper cites Can pre-trained text-to-image models generate visual goals for reinforcement learning? NeurIPS, 36, 2024 b.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Can pre-trained text-to-image models generate visual goals for reinforcement learning? NeurIPS, 36, 2024 b

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.474369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.351906Z digest=sha256:40530179e3510d25ba8c0567af70369386c8c1263a32d718d2e3e102bfda790e

Observation f2c66d2f-b616-449c-8457-d90e972b2474 · outbound

This paper cites 3 d - coded : 3 d c orrespondences by d eep d eformation.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo 3 d - coded : 3 d c orrespondences by d eep d eformation

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.461230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.355074Z digest=sha256:64f2b3c7246978dc9563f38aa2cf3c25ea2d09d5d28e11bbc8e4feba301b35bf

Observation 09c6905b-1839-4439-905d-2cc98b1e7b82 · outbound

This paper cites 3D-CODED : 3D Correspondences by Deep Deformation.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo 3D-CODED : 3D Correspondences by Deep Deformation

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-11T20:57:12.833918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.358402Z digest=sha256:5478a59d7e2346cdbdd4249e370a7e75ee1a8896d189507dd2866e25934f4678

Observation 4b741dee-2bb7-4b98-9915-e0c66996f8f7 · outbound

This paper cites Unsupervised learning of dense shape correspondence.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Unsupervised learning of dense shape correspondence

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.448567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.361862Z digest=sha256:da430529a05902d763ec748998fe2fa189bb87ab2e0be225263195a51211de9d

Observation 3773a5b1-a345-4a39-a5a1-1200c562ec6c · outbound

This paper cites Proposal flow: Semantic correspondences from object proposals.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Proposal flow: Semantic correspondences from object proposals

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.437171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.366514Z digest=sha256:d009f07c2e5313b439c54b25b22cc49dd53d7631bab25dcaee3c04cff43babaf

Observation 1e46f39d-f3a2-4da6-81c1-d3636ceecb62 · outbound

This paper cites Unsupervised semantic correspondence using stable diffusion.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Unsupervised semantic correspondence using stable diffusion

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.370160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.370160Z digest=sha256:3cf4e5ee93e796e6562060f9c7cd8963128456410678b491cdc9ede9228907e8

Observation c6b28407-924e-4394-86b3-4e76707d7a6c · outbound

This paper cites Stem-OB: Generalizable Visual Imitation Learning with Stem-Like Convergent Observation through Diffusion Inversion.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Stem-OB: Generalizable Visual Imitation Learning with Stem-Like Convergent Observation through Diffusion Inversion

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.374272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.374272Z digest=sha256:d98e10340ab802da4da823114ed56a84815947cd3e50a87023ef026927fffccc

Observation 974fa5ed-70f9-4113-89fe-8e42fbda0083 · outbound

This paper cites Robo-abc: Affordance generalization beyond categories via semantic correspondence for robot manipulation.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Robo-abc: Affordance generalization beyond categories via semantic correspondence for robot manipulation

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.418289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.378054Z digest=sha256:fa76bb2a4739f67eebeb265bc55d6e6d163f4e0e2a9a047e802ef1c2e4f369cd

Observation 88d4e2a7-9267-4bbb-8b4d-4d58dd7591a4 · outbound

This paper cites Kazhdan, Matthew Bolitho, and Hugues Hoppe.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Kazhdan, Matthew Bolitho, and Hugues Hoppe

Reference 37

Resolution
metadata mismatch
raw_fallback, observed 2026-08-11T20:57:12.807438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.381378Z digest=sha256:9cee85920b5a4c726a7c0fb02db4a7897fe79d9c9ae11244e2ce329f8f4f282b

Observation 8764528e-c953-4dca-aaf7-595f8ebf8c60 · outbound

This paper cites One-Shot Imitation under Mismatched Execution.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo One-Shot Imitation under Mismatched Execution

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.384806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.384806Z digest=sha256:b3324dc1fc50c6cf0b05d73c9a274ba37078ded609f382f97365c14d14843a89

Observation 61662e6d-5442-4d09-8bcc-7d7933abe3fd · outbound

This paper cites Robot See Robot Do: Imitating Articulated Object Manipulation with Monocular 4D Reconstruction.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Robot See Robot Do: Imitating Articulated Object Manipulation with Monocular 4D Reconstruction

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.388305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.388305Z digest=sha256:3a6d9f764effe23ef3b4677922dc45c226696d70d8e237a6beedf15b0cde8a78

Observation 23fbd966-128e-4afb-8ba9-f214d236659c · outbound

This paper cites Blended intrinsic maps.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Blended intrinsic maps

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.406530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.391821Z digest=sha256:f63cb0076282c259074edd3630ca46452135742ae11df32b618f8ed2fea3705f

Observation 9008c264-66f3-44b4-95a9-07456178b139 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Adam: A Method for Stochastic Optimization

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.395296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.395296Z digest=sha256:f2d06e5669337f361d87aadd14bb3fe47849844748e76a4885849b978254291b

Observation 6d3f5097-46fc-4346-9b32-016b75a074af · outbound

This paper cites RAM: Retrieval-Based Affordance Transfer for Generalizable Zero-Shot Robotic Manipulation.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo RAM: Retrieval-Based Affordance Transfer for Generalizable Zero-Shot Robotic Manipulation

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.398840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.398840Z digest=sha256:9753a0b06939ceb41e688a273206fec839ab550defde5dded36909c943de1847

Observation 953520f3-f579-4eb5-adc8-0cba37bbf9e3 · outbound

This paper cites Ag2Manip: Learning Novel Manipulation Skills with Agent-Agnostic Visual and Action Representations.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Ag2Manip: Learning Novel Manipulation Skills with Agent-Agnostic Visual and Action Representations

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.402274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.402274Z digest=sha256:62d32410aa59f7ef0c95cce937df9f765971ee2e83c3f97a3ba1375535c3873d

Observation 79161979-606f-4536-be6e-aedc5cd44a05 · outbound

This paper cites Dynamic 3d gaussians: Tracking by persistent dynamic view synthesis.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Dynamic 3d gaussians: Tracking by persistent dynamic view synthesis

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.394599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.405970Z digest=sha256:5e5a5b84dbdda40c9fdb1868c636b67c964a70d88e3f265178b09f3b6d163eb4

Observation ba176310-8f57-443d-b694-a6076c0d4400 · outbound

This paper cites Diffusion hyperfeatures: Searching through time and space for semantic correspondence.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Diffusion hyperfeatures: Searching through time and space for semantic correspondence

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.383483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.409502Z digest=sha256:b290fd7d9aad1d8928150b147afc7761490194b18bf63aa62325f1869005eb6f

Observation 06f32164-a160-4509-922a-8cf9688250b4 · outbound

This paper cites Diffusion hyperfeatures: Searching through time and space for semantic correspondence.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Diffusion hyperfeatures: Searching through time and space for semantic correspondence

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.370834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.412869Z digest=sha256:f8540f715d33262d1a6d3e00b6efe2bc1b2aa638e456db0171a1f335fea73297

Observation 93222aaa-4120-443d-bd06-9d65f0dae4f3 · outbound

This paper cites Discrete differential-geometry operators for triangulated 2-manifolds.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Discrete differential-geometry operators for triangulated 2-manifolds

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.359067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.416015Z digest=sha256:dd4096e63a5488fb94a5c63d8d6d2f8d02a1f4c2e02b9cd9f0cd5dc151bf8064

Observation d765abcf-1227-46b5-9775-732f475ad943 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Nerf: Representing scenes as neural radiance fields for view synthesis

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.419353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.419353Z digest=sha256:90a1c45498e311a1698c303e25d12b1f174634bceb526c1039246dcf869497a1

Observation bc1fd11c-83b4-42ed-8d3d-8db08fd4b2fe · outbound

This paper cites PyMeshLab , January 2021.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo PyMeshLab , January 2021

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.341232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.422708Z digest=sha256:369175443f893296a84456fddaf978ed42bf135ed14b3b1012a0bb6a6e79bbbc

Observation c475631c-971a-4f81-b56f-bc1a68b9d416 · outbound

This paper cites Informative descriptor preservation via commutativity for shape matching.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Informative descriptor preservation via commutativity for shape matching

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.330481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.426352Z digest=sha256:8b8dc9c5c94210b06981c4d50132d71e6621c13bb710a3b5610cb3abbf74d0b3

Observation 5d7b3a6c-3657-47ca-a810-2d5827150911 · outbound

This paper cites Neural congealing: Aligning images to a joint semantic atlas.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Neural congealing: Aligning images to a joint semantic atlas

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.319213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.429655Z digest=sha256:6fb9c2dd5cb29b5da5612e5718136477f75acf9054474dc8458159efbf79ed9a

Observation d1395cad-ea54-414d-b5fa-3123aff4178b · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo DINOv2: Learning Robust Visual Features without Supervision

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.436633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.436633Z digest=sha256:065a2b3457119d6f3e53f30f3cf3c4f20993fa8e2cc48250bebc8738addf6369

Observation 521cc3e6-6c66-404f-be5a-466f9544fb67 · outbound

This paper cites Functional maps: a flexible representation of maps between shapes.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Functional maps: a flexible representation of maps between shapes

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.308242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.440473Z digest=sha256:e5e3205ed8688d6ab0cf2aefefb3b1985954853e7185167116b01379f3b60daf

Observation 20050c3d-e6b2-4bba-ac2a-b06218aee886 · outbound

This paper cites Learning so (3)-invariant semantic correspondence via local shape transform.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Learning so (3)-invariant semantic correspondence via local shape transform

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.297089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.443690Z digest=sha256:b9bd188fbc217a770aaa88293bfc5f1521950bd6a790b1b6586bb7f2a6ed113b

Observation 8bb159a7-8374-4157-8f94-1c16a7910aef · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.447833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.447833Z digest=sha256:dff8beaf05f05f2884f497dd042b2bf437f1f4952fd53275b167532dad044b40

Observation e035bd18-8190-443b-b261-bb56335d2a68 · outbound

This paper cites an unresolved cited work.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-11T20:57:13.285759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.451802Z digest=sha256:92ad4e9f18cba0f82c53eee0a005820d6fb0f066436d316199988e079468e1b6

Observation b69bccc7-7e48-4829-8d1d-be7c69561bd1 · outbound

This paper cites PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.455717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.455717Z digest=sha256:294d03d0cff046605e5f8e656e5349622befc4ce8184ea9e7c86befd59e70fff

Observation 9f4e1f4c-59a6-49e1-ab8a-c15c8ff330d9 · outbound

This paper cites Continuous and orientation-preserving correspondences via functional maps.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Continuous and orientation-preserving correspondences via functional maps

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.274870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.459157Z digest=sha256:94e1938b42b741230371cb6827c351eae1879c0f3d8fdcb85562b031abe709e4

Observation e4050dc2-3960-4d6b-b45d-0fa590f7ab69 · outbound

This paper cites Partial functional correspondence.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Partial functional correspondence

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.262851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.462107Z digest=sha256:0e0c8825d0370124637271623579da5c942cc1965cf5c5c1e9496989a0807259

Observation 970687d7-7d83-4f70-8b7f-1f0573f3d17e · outbound

This paper cites Spidermatch: 3d shape matching with global optimality and geometric consistency.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Spidermatch: 3d shape matching with global optimality and geometric consistency

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.251999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.465525Z digest=sha256:bcc0a617e59be447d7509de9ee258e2bfa1452a84a6e82782f871992883c4cb0

Observation b5282e2c-3989-43fb-9f6e-4eb751e32e89 · outbound

This paper cites High-Resolution Image Synthesis with Latent Diffusion Models.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo High-Resolution Image Synthesis with Latent Diffusion Models

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.468991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.468991Z digest=sha256:ae33001de3d9ed0b0216445ff6a8e6f18a8cc6d2d1d4340b652a0248455b6b5f

Observation efa078f4-6621-4a5e-b119-6398b1b747ff · outbound

This paper cites Understanding human hands in contact at internet scale.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Understanding human hands in contact at internet scale

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.241148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.472725Z digest=sha256:c66f8b1c6dd1a806557109d71436bd9c49cb8e8c1adc4271bcd760720a20a357

Observation 41159c3e-11e2-45c1-8423-b737a3b33e02 · outbound

This paper cites Diffusionnet: Discretization agnostic learning on surfaces.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Diffusionnet: Discretization agnostic learning on surfaces

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.229978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.475906Z digest=sha256:aa426bb2796d510fe7cd566c903286a9c3c84a5a8cd3a2513c8284a3ff8129ec

Observation 6ee47ca2-eaaa-4590-956d-d7d32989d29f · outbound

This paper cites A concise and provably informative multi-scale signature based on heat diffusion.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo A concise and provably informative multi-scale signature based on heat diffusion

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.218100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.479370Z digest=sha256:5c8de3a332e4b03432a1421c6311285a272b0a6706849856918c29fa4c073f3f

Observation 31be6a8b-7162-4206-adca-c5bcc8d04a7c · outbound

This paper cites Emergent correspondence from image diffusion.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Emergent correspondence from image diffusion

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.206942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.482753Z digest=sha256:273c541ca0bd6b128a8464a8c740315d9b31bffcb16fd25560336eb39f3f02f1

Observation 0174d1fc-ffd0-4879-9fc1-59b28e758cdc · outbound

This paper cites Robotap: Tracking arbitrary points for few-shot visual imitation.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Robotap: Tracking arbitrary points for few-shot visual imitation

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.195244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.485904Z digest=sha256:5f5151e6392fe5ae42b185eeb4d81f3758a3c1b203056c1e38cab7a81eacd663

Observation 4e52559b-cf64-4124-9d76-c078931954ad · outbound

This paper cites One-Shot Imitation Learning: A Pose Estimation Perspective.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo One-Shot Imitation Learning: A Pose Estimation Perspective

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.488991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.488991Z digest=sha256:dece903113d7d5c8d6837114158a5e8856412f062d477678a932481097e53987

Observation f7a57ba1-1492-4bc2-a2e1-c71172ec0171 · outbound

This paper cites MimicPlay: Long-Horizon Imitation Learning by Watching Human Play.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo MimicPlay: Long-Horizon Imitation Learning by Watching Human Play

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.492582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.492582Z digest=sha256:932c0ffe2832edd94a75602027ef82ea51a5fc40327ec1c89169398a41a17dae

Observation b47a1bb6-8715-45ee-9fe4-0bdf07c0b9fc · outbound

This paper cites DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulation.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulation

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.495938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.495938Z digest=sha256:7272a73d693445c6c4a3c4607c8f264f8604495b26cce7ff65a00af9e3326bd2

Observation 7df45b97-668f-4fdc-a823-0444b7da120e · outbound

This paper cites Learning and Reasoning with Visual Correspondence in Time.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Learning and Reasoning with Visual Correspondence in Time

Reference 71

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verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.183772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.499107Z digest=sha256:d309217bcd600c3e5f8853a6773598372d80b965a423e3f99fdf61bbc3f83311

Observation bb9b2710-785a-474f-99a7-7eae4ff113c3 · outbound

This paper cites D$^3$Fields: Dynamic 3D Descriptor Fields for Zero-Shot Generalizable Rearrangement.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo D$^3$Fields: Dynamic 3D Descriptor Fields for Zero-Shot Generalizable Rearrangement

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.502649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.502649Z digest=sha256:e14928ad27a08cb125080f844bd6eadfa75517b2c80f307fa6bd040cc1cdb7af

Observation 8865cd4c-8974-4a0d-8895-7e4b4ca1c4c4 · outbound

This paper cites Dynamic graph cnn for learning on point clouds.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Dynamic graph cnn for learning on point clouds

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.171271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.507248Z digest=sha256:c33c19aa46f6266581626f655a347babc91c0ce6fd7cc19bde91cfa61e19bd5e

Observation 207d7c4f-9198-4b5e-953b-6564cdcf1c36 · outbound

This paper cites Omniobject3d: Large-vocabulary 3d object dataset for realistic perception, reconstruction and generation.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Omniobject3d: Large-vocabulary 3d object dataset for realistic perception, reconstruction and generation

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.159767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.510352Z digest=sha256:2205e419635e2a463a52794a8309704d9c2f19cee2bf4e8f93e7d5a68cc1c476

Observation 729543cd-de6a-4501-af75-444d1cb0b9fb · outbound

This paper cites Useek: Unsupervised se (3)-equivariant 3d keypoints for generalizable manipulation.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Useek: Unsupervised se (3)-equivariant 3d keypoints for generalizable manipulation

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.147757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.514308Z digest=sha256:c15266a3cc63e7b9d062128d67f35e01696890b605d8d54d0eec5213a3ffee13

Observation 3b421402-aef1-4763-90da-5deeeb77256d · outbound

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

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo SAM3D: Segment Anything in 3D Scenes

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.518282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.518282Z digest=sha256:d9a575ff76ce9aac5a21944bf308e9c6cf034f94ecbd7db5c0406f9376c6f6c0

Observation 807a81e8-a895-4c32-ae7b-74a84e5ab0a8 · outbound

This paper cites Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.521885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.521885Z digest=sha256:5e701186142271244ba4fdb466154ebb1e5bd728c94a88c8785a4bbbea9073b8

Observation 68b5c915-1dc3-4c85-b7ad-58252d46add5 · outbound

This paper cites 3d diffusion policy: Generalizable visuomotor policy learning via simple 3d representations.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo 3d diffusion policy: Generalizable visuomotor policy learning via simple 3d representations

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.136403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.526260Z digest=sha256:271c7744ab8579c6c650364c3da029a57075c715e7dbce17a9036fac6d5c24a8

Observation 0f23afae-b05e-4f84-b236-ec2826678d94 · outbound

This paper cites Corrnet3d: Unsupervised end-to-end learning of dense correspondence for 3d point clouds.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Corrnet3d: Unsupervised end-to-end learning of dense correspondence for 3d point clouds

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.124016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.529795Z digest=sha256:a9e695fc060234476eed50b73725d1300d1b27e5768aa4152e079c6c5f90059a

Observation bc57cd66-5384-47f5-98fb-0814972a898e · outbound

This paper cites A tale of two features: Stable diffusion complements dino for zero-shot semantic correspondence.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo A tale of two features: Stable diffusion complements dino for zero-shot semantic correspondence

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-11T20:57:12.532969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.532969Z digest=sha256:6aa99b1fac36cd6e900bed862c566269bb318507f9f74ba800dd337b8d182b5c

Observation 12cf4bdf-0982-46a1-be5d-d88e11f0a809 · outbound

This paper cites Telling left from right: Identifying geometry-aware semantic correspondence.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Telling left from right: Identifying geometry-aware semantic correspondence

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:57:13.104953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.536137Z digest=sha256:a6b57d756fa2d4b9a63b4bac9ca749268a0928005154f31823a6c21e3d520994

Observation 1c2f59ff-9b26-484b-8812-2dbf065b38af · outbound

This paper cites an unresolved cited work.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Unresolved cited work

Reference 82

Resolution
unresolved
raw_fallback, observed 2026-08-11T20:57:13.093636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T20:57:12.539343Z digest=sha256:0240e39a0d62f65bf52b6f9a08a951a1fd323ab18140a2c1852c67a11db7fda8

Pith citing papers

Observation 31347ab5-89e4-4054-9245-a85a0314e0e4 · inbound

ControlVLA: Few-shot Object-centric Adaptation for Pre-trained Vision-Language-Action Models cites this paper.

ControlVLA: Few-shot Object-centric Adaptation for Pre-trained Vision-Language-Action Models DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T23:51:05.402554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:51:05.402554Z digest=sha256:bb78da631d1d3a1fc3020de59b76cd9254d311638d8eea72b4168604fa9f0ef7

Observation 3e5669af-b5f3-478b-858e-9fcf8a1d8a7a · inbound

Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations cites this paper.

Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo

Reference 138

Resolution
verified exact
arxiv_id, observed 2026-05-19T06:37:07.333645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-19T06:36:13.144868Z digest=sha256:01c6b5793076da5b4920f8a248cfe7794962d1bf8c5693695dec55f989d23c73

Observation 6cd68ccc-db0e-407b-82f7-26af3da40de1 · inbound

Densemarks: Learning Canonical Embeddings for Human Heads Images via Point Tracks cites this paper.

Densemarks: Learning Canonical Embeddings for Human Heads Images via Point Tracks DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-18T00:55:35.231966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-18T00:53:24.323059Z digest=sha256:981d6fb673e755bf2393e320616875b00fbd6d7933fb614469472f648d9676fd

Observation 7cb25555-bcec-4973-b0cf-5b91531cb6c7 · inbound

IGen: Scalable Data Generation for Robot Learning from Open-World Images cites this paper.

IGen: Scalable Data Generation for Robot Learning from Open-World Images DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo

Reference 79

Resolution
verified exact
arxiv_id, observed 2026-05-17T02:58:54.791384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-17T02:58:36.214948Z digest=sha256:5bfc0a1494354f28ef7778775e822a5c550e0fb538c1da61aa53b4b562630de1

Observation 2dc9fe79-affb-4e1e-94ae-5529aefebe7a · inbound

AffordGen: Generating Diverse Demonstrations for Generalizable Object Manipulation with Afford Correspondence cites this paper.

AffordGen: Generating Diverse Demonstrations for Generalizable Object Manipulation with Afford Correspondence DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:00:59.161695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-10T16:21:40.381114Z digest=sha256:430467c3419afaae935fbd3d50e873174dbfd3abd4a0d08282bcdfb4d2149ad8

Observation e434bea8-e760-462c-b2aa-6de002330e4a · inbound

AffordGen: Generating Diverse Demonstrations for Generalizable Object Manipulation with Afford Correspondence cites this paper.

AffordGen: Generating Diverse Demonstrations for Generalizable Object Manipulation with Afford Correspondence DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo

Reference 39

Resolution
unresolved
no resolver link, observed 2026-07-12T22:32:10.188246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T22:32:10.188246Z digest=sha256:cfffa9f49e459610a6c183645587376cde1d6e4dd00587f7b56d8f663e736330

Observation 402a4108-1848-474f-bacd-e3e64d1c6b4c · inbound

SGSoft: Learning Fused Semantic-Geometric Features for 3D Shape Correspondence via Template-Guided Soft Signals cites this paper.

SGSoft: Learning Fused Semantic-Geometric Features for 3D Shape Correspondence via Template-Guided Soft Signals DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo

Reference 79

Resolution
verified exact
arxiv_id, observed 2026-05-20T11:53:15.145489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-20T11:48:55.446684Z digest=sha256:f63e35410a4bf0046339c57bfc1055fc38e1aaec7a0719b75ad30541b0c38e8e

Observation 09802c85-84ac-4eec-89ad-d934f6feca77 · inbound

GRAFT: Graph-Based Affordance Transfer via Part Correspondence cites this paper.

GRAFT: Graph-Based Affordance Transfer via Part Correspondence DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-07-04T17:40:01.071620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-25T23:27:15.576980Z digest=sha256:16ad0880914bd45552e53cfc16a50f5751f3644292302579172c652e243a3073

Observation ec17ba3c-0a22-43e8-9e8c-1e1873380023 · inbound

MeshFM: 2D Features Are All You Need for 3D Shape Understanding cites this paper.

MeshFM: 2D Features Are All You Need for 3D Shape Understanding DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-01T05:06:27.122910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T05:06:27.122910Z digest=sha256:e1229bf264625ed3a6cd061fb4eb899d00311ce056f3886a1a6cb84f2d9f2ee9