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Paper Citation Record · LEDGER

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions

As of 10 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 5 inbound Pith citation observations for arXiv:2502.05091.

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

pith.paper-citation-record.v1
2502.05091 v2

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:22:31.669704Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:47:07.624830Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T09:04:04.564701Z

Reference resolution

49 of 49 outbound references displayed

  • verified exact0
  • verified fuzzy18
  • unresolved31
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4f4627d5-021d-47b5-8bd9-72a7715a51af · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-08T20:22:31.408691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:22:31.408691Z digest=sha256:a78e38358b663da2880a379130cec3afb85f0741ea7f2b195d4eda9da9d489d5

Observation 1feaf703-fe71-4e2f-99f5-2765fc3d83d9 · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-08T20:22:32.591018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.414429Z digest=sha256:d218a2ee7c6042ec475171d6f0de86c770991b9e3ad66a810c1df7ad7dbad64f

Observation 14ef91bd-1594-403a-8895-1f98f7f51335 · outbound

This paper cites & Suk, H.-I.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions & Suk, H.-I

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-08T20:22:31.419274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:22:31.419274Z digest=sha256:7b2bc20dddd0fa15f3a5182d023030f97c2c55fecb69a4f251d664a4511af167

Observation 31706781-f351-48fb-85f7-11fb519f20b5 · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-08T20:22:32.564402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.424122Z digest=sha256:1ef98e0bb00c8fe3165a0643489527a4dbe28ab2b51270545696871da183eb22

Observation 6be1ff46-a2ae-413d-af9a-a68518bed240 · outbound

This paper cites Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.548552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.429167Z digest=sha256:7ec2d8b72774de48280ecd180a59dd70c7f76e6ea0f6ecc98d6b8ed5c7c4637a

Observation 53548f38-f838-4499-b33b-48fdd1cbc3e9 · outbound

This paper cites Handwritten digit recognition with a back-propagation network.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Handwritten digit recognition with a back-propagation network

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.532372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.434620Z digest=sha256:1767a7feba0e6354ef051daebac5e2ed303846b2cb8fc7be4dc4f2bdf385d729

Observation 2e6f5687-69aa-4eb4-808a-d7a830eba79b · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-08T20:22:31.441149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:22:31.441149Z digest=sha256:6a38049bcf6d4804a368475bcb1d9d8ff025fe8eae096387f8300c1b182bfcb4

Observation 304a5fb3-e63c-4f0b-9c7b-6178feb7b8bb · outbound

This paper cites & Brox, T.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions & Brox, T

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.516096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.447407Z digest=sha256:e1d993453dcd4cb259dd3a058782e25284eacd2d8fe7f08ab8f5446b98ca79ae

Observation f868bb9a-2623-45c6-bff4-457e1550adb6 · outbound

This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-08T20:22:31.452346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:22:31.452346Z digest=sha256:4895bc33ccf577e306072b8e447a0b4fbb32c108b6f9f81b75bdfeb1213a3507

Observation ce171980-96d0-4a05-acc7-57be20612808 · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-08T20:22:31.458137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:22:31.458137Z digest=sha256:7575fd4ae629dc0567968bea26213f4a6cab9508ad13c0f764b9a2a3132a211b

Observation 4380bf20-ed78-4264-9b72-d34ec2332413 · outbound

This paper cites & Zaiane, O.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions & Zaiane, O

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.488879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.463150Z digest=sha256:9591a61397e4438b94ebcfb375f58d2a0aa12d66ef9ddb86fe9919271febdad4

Observation 1e31ac2f-3edd-46bf-a91a-096a4f259204 · outbound

This paper cites C., Mohan, P.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions C., Mohan, P

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.473304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.468540Z digest=sha256:42f8dcaf4990d8a996d2aa5dde4ac51c0e3db12f506f838a6a9596906689153e

Observation 13ad220b-f439-478c-a5e2-4e95508a3fc4 · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-08T20:22:32.456815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.473949Z digest=sha256:0a2db18733dff176baf1dc8d64f4de2a431eeab9cbb6a715b233d2a9d9b8156c

Observation 395254c3-9abd-4421-8f27-cf924a819e81 · outbound

This paper cites Self-supervised pre-training of swin transformers for 3d medical image analysis.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Self-supervised pre-training of swin transformers for 3d medical image analysis

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.440825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.479003Z digest=sha256:442db13e80207b04d53e495f39296b455feef23042783806295d8eb380b8c3d2

Observation 569108c9-6e4a-45d8-a8a9-56def5f73632 · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-08-08T20:22:32.424037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.483990Z digest=sha256:1cdf33e010f817473ba402d00bda2e655ff593784c6e27264485a4585fd90348

Observation 02ea5657-52e5-42f3-a4d5-36fff5c89543 · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 16

Resolution
unresolved
raw_fallback, observed 2026-08-08T20:22:32.407527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.488739Z digest=sha256:574e5dea19a926221beaf1ff5c1a60d047074bf7268391aa8d96370f8fe67d8e

Observation 909fa245-6964-4731-b4c6-218fd3429bae · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 17

Resolution
unresolved
raw_fallback, observed 2026-08-08T20:22:32.391524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.493669Z digest=sha256:f66ab5b1222c4e0ce139b7351c0bd22a59ad60e94208c6050cc729530c061411

Observation 8f2c9c74-bc4c-4997-be80-b08a9a8ef0c7 · outbound

This paper cites CLIP model is an Efficient Continual Learner.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions CLIP model is an Efficient Continual Learner

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-08T20:22:31.499009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:22:31.499009Z digest=sha256:f858c5626ff97c996a873e1714b2ba17dbcbf0cdf87f5e86083d53be4545094c

Observation 6751b79c-3263-4126-b3d8-2842c852eb6b · outbound

This paper cites MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image Segmentation.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image Segmentation

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-08T20:22:31.505068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:22:31.505068Z digest=sha256:8c256d13262419dc11aa1b58541953fc7e9c2208bf8a1653ceb98ca5ebfe91e8

Observation 42e85e4c-ce6a-4237-86d7-453289cf4db8 · outbound

This paper cites Y .et al.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Y .et al

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.375161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.510758Z digest=sha256:25d0ade0e6ff883a7dbd1130bde0055dda6e063e0fb5f1e792daf1dda37fc00a

Observation c8e76da4-480b-4797-8fc6-3ca95400a2aa · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 21

Resolution
unresolved
raw_fallback, observed 2026-08-08T20:22:32.357921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.515665Z digest=sha256:9d90efa741ed8e81d0fa4b75b4f35ba40568939a26f96e4d5e6f692a273b1ae6

Observation 0a3f2d49-a26c-469a-bc35-08f5f8609e42 · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 22

Resolution
unresolved
raw_fallback, observed 2026-08-08T20:22:32.341404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.520837Z digest=sha256:67929879ec04bc3750a87e156737c90967ee777d36804d1d5a540cb4e6a03fdd

Observation 5e24ec39-b4a6-4c49-a3a2-14e014b6302d · outbound

This paper cites & Hoogs, A.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions & Hoogs, A

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.324049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.526501Z digest=sha256:94603433c12d7781847e8e282d28abbf6013db8d26b7ab87015e1f005133a971

Observation 8fa4aa6e-0681-4c8c-a186-f0558f62751b · outbound

This paper cites & De Melo, G.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions & De Melo, G

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.308277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.531791Z digest=sha256:e0e8d140e747dcfe4a9fa2787cf3c2a4c5b32cd4ae3cc73f7fd6cab3a5686fc3

Observation c3205b3e-dbd5-4b65-9824-b403ff05941f · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-08-08T20:22:32.292760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.536868Z digest=sha256:c5cb028bee4ad32b801d911edd5de7c1cf31e2bed0bcee16435eea1c8430905d

Observation cb36bbc2-3e4a-4666-9743-aff58dab8f09 · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-08T20:22:32.276842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.541998Z digest=sha256:b977a4eb5b302f6579e6a82317c487624571a528130769d427d51aa58ac3efd1

Observation 3c979471-f5a3-44f9-a60d-5834cba0ae03 · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-08T20:22:32.260854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.548807Z digest=sha256:f62b52f4f65326b205113c9d840a6651792620a5acc27be347ef6d828a22e68a

Observation 6b85243e-c964-4a72-878f-9d46a58c7e81 · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-08T20:22:31.554482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:22:31.554482Z digest=sha256:3beb59460832162b200a98f8324c9adcc96896cf8ee4d3106bd8aaede82abb75

Observation 0ae100d5-f1a4-4960-ac6b-45e1afb422a0 · outbound

This paper cites Xception: Deep learning with depthwise separable convolutions.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Xception: Deep learning with depthwise separable convolutions

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.234738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.560426Z digest=sha256:c9786bab9e6c3724c7424b37e8f37d485c7cf2d0e6498323b59eafefbe76e985

Observation 4e95742f-f58d-426e-ad80-cd20d752fecd · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-08T20:22:32.218434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.567021Z digest=sha256:acae0825216f4950a76a9f93d3e8d749fa794b233b59276a80bc1a4029a166f0

Observation e83645f6-7c7c-452a-b50b-e1a548a000a4 · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-08T20:22:31.572927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:22:31.572927Z digest=sha256:b7dabf946cf958bc79aae2853650b5011c83af9d76302e04ebf3087dfbd5b145

Observation bc8648ae-6354-48c0-acec-9848d21ec188 · outbound

This paper cites Metaformer is actually what you need for vision.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Metaformer is actually what you need for vision

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.191189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.578764Z digest=sha256:6dcd1445cba8f0487b2c3127e0e242288e44616971c36667b589bc0e81987e8e

Observation 881a7669-f059-4f07-9212-924569cb4578 · outbound

This paper cites C., Gong, K.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions C., Gong, K

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-08T20:22:31.584153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:22:31.584153Z digest=sha256:9cec7e5f2874d76020a77a586debd887cce1bc9fd6bdb861d3836bbb2e5a6792

Observation 178b622c-4024-4820-85d2-d838944f849f · outbound

This paper cites & Beyer, L.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions & Beyer, L

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.176131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.589418Z digest=sha256:5e6ed2774fd05d184f20b1af2f5a93dc2492ac996a16dba6bb6a2e4706853566

Observation ceeca7d5-7905-45d9-b5ff-4e32cc4d4559 · outbound

This paper cites & Lee, Y.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions & Lee, Y

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.160506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.594594Z digest=sha256:f80879557e10db2dded95ecfd059f28914146ca00e8f9d6c252420906002f97a

Observation 868142d8-6833-4294-82c7-fbaf7a5cc2b1 · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-08T20:22:32.144929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.600089Z digest=sha256:65bbc8450ae4d2646a50bcd6702356f6f88e3432626156ae7c4f109b1ecc19fa

Observation fbaa89d4-4d1e-4cac-99e7-9241454e2fca · outbound

This paper cites Metaformer baselines for vision.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Metaformer baselines for vision

Reference 37

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raw_fallback, observed 2026-08-08T20:22:32.128761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.605522Z digest=sha256:fa21015c8ab5d0f768cae96290965eb8a07c1f1aa8c80f457130dd869048dc9b

Observation 6237c074-21bc-4fa4-8b8a-c2dd17e63eb4 · outbound

This paper cites & Sun, J.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions & Sun, J

Reference 38

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no resolver link, observed 2026-08-08T20:22:31.611057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:22:31.611057Z digest=sha256:eb873108d860f0ac23cfd11337e6f71f524aa91aba99eb9d1e2a6a489ad8a0f7

Observation 260df854-4e83-4c4c-ada0-3e7d8f532135 · outbound

This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 39

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no resolver link, observed 2026-08-08T20:22:31.616684Z

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source=pdf_text observed=2026-08-08T20:22:31.616684Z digest=sha256:bfd68f1aec77499a3da08d541b02abbc10120101a9e0f7f884e4bba3e1dfa80b

Observation 5e0d8c74-b65d-4292-b8bc-31ae5d06f3b7 · outbound

This paper cites Layer Normalization.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Layer Normalization

Reference 40

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no resolver link, observed 2026-08-08T20:22:31.622388Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-08T20:22:31.622388Z digest=sha256:8e25a5cf77499eb2ce90c321a5bb2ada50a0fe70a88a9a6b0edc2fd127c07b0d

Observation bcfb8c97-e405-4faa-a390-d28ade72a72b · outbound

This paper cites & Hinton, G.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions & Hinton, G

Reference 41

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raw_fallback, observed 2026-08-08T20:22:32.101451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.627846Z digest=sha256:4a7afec04a327f82118d6e62acd5db4ab94fbc8f2485be584e2cc793313b8f79

Observation eceab749-53a3-4e53-8c93-a832be0ab0b1 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Gaussian Error Linear Units (GELUs)

Reference 42

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no resolver link, observed 2026-08-08T20:22:31.633121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:22:31.633121Z digest=sha256:23cbd0e17eb2e702e0ca6fe92940ceb2ad3ee381a318af5ae4aa690ec0ffa0b5

Observation f1c2f9ff-0aa6-4ae0-9708-ad438f292c92 · outbound

This paper cites & Wang, X.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions & Wang, X

Reference 43

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verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.083878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.638479Z digest=sha256:1ea1f134488ac77fb8e9f42e908fa1c16d1c85427a29dbf7383b16e79a592c56

Observation c716ac88-8919-49db-98cd-0117a1942ed3 · outbound

This paper cites & Ding, G.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions & Ding, G

Reference 44

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verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.067358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.643425Z digest=sha256:122b01258fe9aaf890b59188f11099ad2117de3bd47b4abe2c3d04518ae7ece6

Observation 213f2d4d-e857-46e8-ad5f-4654d99043b7 · outbound

This paper cites More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity

Reference 45

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no resolver link, observed 2026-08-08T20:22:31.648897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:22:31.648897Z digest=sha256:35534f60d9bf92c2ee0b3005b75915e9c6de6c834de596b77743ae39e77758d9

Observation 2520711c-7e0c-4d7c-825e-609bb9647939 · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 46

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unresolved
raw_fallback, observed 2026-08-08T20:22:32.050774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.654283Z digest=sha256:18d96ca422dc4e792e6faa2cecc8d3806891df866706ae2cb0b618f98d439273

Observation f842f6f1-f9fa-4f1a-8af1-44042e2f24ac · outbound

This paper cites Internimage: Exploring large-scale vision foundation models with deformable convolutions.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Internimage: Exploring large-scale vision foundation models with deformable convolutions

Reference 47

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verified fuzzy
raw_fallback, observed 2026-08-08T20:22:32.034306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.659448Z digest=sha256:7453f844d1d1084c3adba096ad201e6ff36e53043f3769bfa83cfd387c125ece

Observation c1dcebba-0de5-4e14-84c7-4af712e75db0 · outbound

This paper cites an unresolved cited work.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Unresolved cited work

Reference 48

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unresolved
raw_fallback, observed 2026-08-08T20:22:32.016410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T20:22:31.664396Z digest=sha256:5288882ce90e748ab25f5fdfa2b5aca3508b20889968868647e79c79b7e33d8d

Observation 9c4e5950-47e2-44ae-9fd2-e99c3b731341 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions Adam: A Method for Stochastic Optimization

Reference 49

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unresolved
no resolver link, observed 2026-08-08T20:22:31.669704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:22:31.669704Z digest=sha256:15b56e8530686b7b4d93d63849e9d2b099b079de3a71342a5b39fe1e99da0032

Pith citing papers

Observation 656efc58-2110-4998-a288-a64b06889b1a · inbound

HSENet: Hybrid Spatial Encoding Network for 3D Medical Vision-Language Understanding cites this paper.

HSENet: Hybrid Spatial Encoding Network for 3D Medical Vision-Language Understanding DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions

Reference 2

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unresolved
no resolver link, observed 2026-08-07T04:47:07.624830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:07.624830Z digest=sha256:80b4aee849efa32616db9d861cbd6d18a131baed02b821c8c95f6b8f82e02c71

Observation 41515c9d-78eb-4bda-9f62-a0d8bd3239c4 · inbound

GreenRFM: Learning a resource-efficient radiology vision-language foundation model via supervision-centric pre-training cites this paper.

GreenRFM: Learning a resource-efficient radiology vision-language foundation model via supervision-centric pre-training DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions

Reference 37

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no resolver link, observed 2026-07-15T13:49:27.721549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-15T13:49:27.721549Z digest=sha256:91e9db9513be8495e74b505cdff4d07c426bb57bc25183b1494b8dc5f4bb1925

Observation b641ae26-628b-4a9d-82e2-480f236dfd1f · inbound

ESICA: A Scalable Framework for Text-Guided 3D Medical Image Segmentation cites this paper.

ESICA: A Scalable Framework for Text-Guided 3D Medical Image Segmentation DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions

Reference 9

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metadata mismatch
arxiv_id, observed 2026-05-11T21:46:43.213228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T04:22:26.340374Z digest=sha256:940c4c061ce88b10028b79ecbb885a47700c6fca93db151486c409c504266002

Observation d8cad099-a01a-49af-b433-1072ea394c17 · inbound

UCSF-PDGM-VQA: Visual Question Answering dataset for brain tumor MRI interpretation cites this paper.

UCSF-PDGM-VQA: Visual Question Answering dataset for brain tumor MRI interpretation DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions

Reference 13

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arxiv_id, observed 2026-05-20T14:58:24.707647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-20T14:54:59.212600Z digest=sha256:ac453f111ea782cb6704ba8a0d8f200b841e0afcd34051b750f43b8ffb2bcc46

Observation 60510827-52e7-417c-baba-c88185d2e735 · inbound

UCSF-PDGM-VQA: Visual Question Answering dataset for brain tumor MRI interpretation cites this paper.

UCSF-PDGM-VQA: Visual Question Answering dataset for brain tumor MRI interpretation DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions

Reference 13

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verified exact
arxiv_id, observed 2026-05-21T09:04:04.566460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-21T09:01:38.453097Z digest=sha256:4100f611ced845fb5f5d226765e6ce53d704510167b89ff2ba65d3d0f089af82