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Paper Citation Record · LEDGER

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning

As of 8 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2507.11834.

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

pith.paper-citation-record.v1
2507.11834 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:05:11.138353Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

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

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

47 of 47 outbound references displayed

  • verified exact0
  • verified fuzzy17
  • unresolved30
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 273abd4c-23fb-467e-99dc-cb785b38b811 · outbound

This paper cites Agarwal, Y.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Agarwal, Y

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T17:05:06.833624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:05:06.833624Z digest=sha256:ada303f966b39c041bef0695f4e68012b6786504e6d285900c8851d2ada83226

Observation b0f8e5a4-40d1-494f-a5b9-192160854476 · outbound

This paper cites Barath, J.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Barath, J

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:14.840853Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:06.918630Z digest=sha256:a8b49a76b5862123a57183f5fe382589667cabdda544c6928839a2eecec55980

Observation 3c444015-60e2-4657-9057-4dd84cbc73bc · outbound

This paper cites Campos, R.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Campos, R

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:14.827195Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:07.006076Z digest=sha256:9f07fad80b3649b2705d2dec5332744d434ef469f32049d5f3c66049d08a3abb

Observation bc3c9e2a-d03a-4d74-9fdb-d0a7736f4f52 · outbound

This paper cites Chum and J.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Chum and J

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:14.813596Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:07.099880Z digest=sha256:26446613334c11aa07a335bfa70d87da648ad493d955a33cc79c8a038d2e9419

Observation f84953e0-431c-485f-8e50-7f15886fb62a · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:14.800384Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:07.183420Z digest=sha256:6243daf7f08de1f17fa192952595a36a65ab9f30c22190a900e3d9c01eea2364

Observation 9ae0b582-46c3-4baa-992c-1a20d71a8281 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:14.786776Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:07.256175Z digest=sha256:9fbde3768b65f8f99963841491e92793c47197fc5488d557c195ae0a541d4a44

Observation e7985066-e9a0-412a-abe2-f85bdf361fc9 · outbound

This paper cites DeTone, T.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning DeTone, T

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:14.773461Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:07.344579Z digest=sha256:664cec0e5e5ef3353f1e125ef38f4864745c0992a943b3827d11be3671744fe3

Observation 23a8a108-23f0-452d-aa5f-6929a8ed4814 · outbound

This paper cites Learning Factored Representations in a Deep Mixture of Experts.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Learning Factored Representations in a Deep Mixture of Experts

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T17:05:07.449516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:05:07.449516Z digest=sha256:94dc5be551c9a120b942a0c4474497ba349dce6770490b4dd38237664c801870

Observation 38bdc237-93f1-4f8c-981b-d6c10e49cd03 · outbound

This paper cites Fedus, B.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Fedus, B

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:14.759529Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:07.534656Z digest=sha256:a0057837432c324ce30c9c573878d1e92dc634f1f4f8e6ff02d19dfb09bc69dd

Observation 8809213a-3c5b-48e1-b320-6b37c1f0a193 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:14.744678Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:07.628226Z digest=sha256:0017f38367ba75c95297171f92430bcd8daba0dab335cd1ff2eb196f18505360

Observation cc72aed0-703c-4c21-b990-8aac0a22c207 · outbound

This paper cites Gross, M.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Gross, M

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:14.730393Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:07.728671Z digest=sha256:9f1400e65b411288de1c593ec85ff9c22a071c45e28c3d975c4d4a9465667e58

Observation 667f5423-e0f8-4777-a2f8-75dfc7b5fed2 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:14.715203Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:07.820470Z digest=sha256:3a825699cf474c5bfdbc9b99ec6bf5e128f924bac1840340cde401ab481142e8

Observation 9d7ce441-1e6f-459c-921c-dfa17646c544 · outbound

This paper cites Kerbl, G.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Kerbl, G

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:14.700801Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:07.914340Z digest=sha256:62168ae9415b19dafd8dc910079bdbaf2c81adc4ee5fdcac0eaa2e1de2b00f55

Observation 8b350bbc-2552-4153-8c9b-e9073f939897 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:14.684930Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:08.013711Z digest=sha256:d12c2e57e4cbdba365c9988ce220ae4b62f07aedec8e4e2300b700b7d51161a9

Observation 9a8d8dbd-9918-4151-8d44-f9bb3b332d8b · outbound

This paper cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T17:05:08.107725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:05:08.107725Z digest=sha256:e1d8446a48174549b361bc7d210fce7beb726096760e83a92dd1ea34c3fc743f

Observation 5d6cc733-efb6-492e-b75c-8824418f8243 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 16

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:14.670983Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:08.204556Z digest=sha256:2b9cb51d9f5a3e30d4c4732d57206c3eeb0d0759890bd862619c1976a85f9bfe

Observation 614c2f4b-004f-4dd9-aa6b-edca9e6238b8 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 17

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:14.656103Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:08.295178Z digest=sha256:224cdbe1b3148a366549abe7127762ff19c61f062c95d4a55ea5bd72facf9b38

Observation 4d604e8a-c2c2-4ae2-8d9b-eab15c49cdb7 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 18

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:14.640017Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:08.411974Z digest=sha256:d403f547477dfd80ad5b3ecc537499d5efefd1c64a85ff7d6f3dba156ddc74bf

Observation 78295d6d-a2e4-4e8c-8d6f-eeca4e7b874a · outbound

This paper cites Liu and J.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Liu and J

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:14.625136Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:08.510629Z digest=sha256:1c778398d18c2d65df09372d04a05fb3fdcae87cd5ab244b95bbc9cdb9b2e718

Observation 138600bc-893a-467a-9b0f-1d2d7102c455 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 20

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:14.610972Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:08.625613Z digest=sha256:6b11e35e5f2b26ba6798e89c673cbdbd2d786fb4d15fa24a769677f5d4fe4761

Observation 36102517-99c5-4d65-8f7f-d47ef93d163f · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 21

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:14.596334Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:08.740241Z digest=sha256:88c3865a9a818dcd658de55dd3c4a8b731b2400e89af1fb435aacce071495693

Observation 6d0e7634-e488-432d-bffa-9d3ed6b250bd · outbound

This paper cites 3D-MoE: A Mixture-of-Experts Multi-modal LLM for 3D Vision and Pose Diffusion via Rectified Flow.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning 3D-MoE: A Mixture-of-Experts Multi-modal LLM for 3D Vision and Pose Diffusion via Rectified Flow

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T17:05:08.865212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:05:08.865212Z digest=sha256:42a5c8e103c54cf20755d9ec2a0d08d43c27b290cd001dda339bb122a0f37d36

Observation d2fcc370-b518-4999-a58a-d6f3c82f970a · outbound

This paper cites Masoudnia and R.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Masoudnia and R

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:14.490673Z

Source-reported events for the cited work

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

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Observation bfc0a41f-762f-4929-9572-f47fe1c0365c · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:14.291247Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:09.063685Z digest=sha256:dd12cc4b65ef8731bee451877716177c878b61c5d30d4ccbbe5805dcee335648

Observation 154515e0-ede5-4c91-a1ad-5f0c9047625c · outbound

This paper cites Mur-Artal and J.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Mur-Artal and J

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:14.113999Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:09.186934Z digest=sha256:e338ed1afc7f494e62ad1839c1f4d0150e717ee10c775a35407f0890c1dbe4de

Observation cda25f82-3a9c-4e5d-8a5b-c19844dd57c9 · outbound

This paper cites Mur-Artal, J.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Mur-Artal, J

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:13.897387Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:09.278771Z digest=sha256:9464322da134b510c1cbd282f68488a2b41b9fb1a8ca35d42ceac0fe10f11b36

Observation d6974c8a-80ba-469f-abe5-9809c5e0cea1 · outbound

This paper cites Raguram, O.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Raguram, O

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:13.683504Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:09.365929Z digest=sha256:6c1522ea08fc5e285ef948201c264f04308978d636b694bbab842fcb773988e8

Observation 5659a824-7d5a-4702-a031-dce5e50b82d8 · outbound

This paper cites Sarlin, A.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Sarlin, A

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:13.544327Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:09.474224Z digest=sha256:d20ca5b4aa54a5d92f1d1e8392622b85cfc0af379b9523b4e896d597b8b40fa3

Observation bfd172f1-6e8e-4511-940d-f7c89adf1595 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 29

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:13.340002Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:09.563255Z digest=sha256:192e8c6898d705ddbaa632cca57670b2533c89b38fa88ebe9a3ffb2368759a61

Observation 20d315e0-2f70-4f2f-a02c-ced5ec5cbe1d · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-06T17:05:09.652404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:05:09.652404Z digest=sha256:36788f03ecb813919340f89b745755b6cc3a1272cd61a18739679d8a1f8a69e0

Observation efa63a48-08fe-4c71-8b23-286ed3aebc73 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:13.148862Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:09.717526Z digest=sha256:71c6b453d59f1b7aeff9bba0ef4d64c6e7baae4968741a3a7023b00f4ad42b33

Observation 59bfa4bf-4b01-4340-b5a5-340d821b9de7 · outbound

This paper cites Thomee, D.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Thomee, D

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T17:05:09.807263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:05:09.807263Z digest=sha256:febff555f102db630f5a4ebf50b4bbdde562d1332f8f47b3b7aac0686c1f9254

Observation b885d616-9208-41f4-97a5-485145111ce0 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 33

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:12.907363Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:09.894720Z digest=sha256:990968dbd0a63bff58ac968b3b27fdf1c483132453fa645cb7d1db5041f55ddd

Observation 4c1e90f1-1f10-4586-a77a-ec1beee89f29 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:12.835011Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:10.008699Z digest=sha256:a4401b9bf03e70278412bd8db61f828c9644554193f19be765d23a3612512692

Observation b00ed089-6b09-4c09-aea5-6caa2d67e2df · outbound

This paper cites Instance Normalization: The Missing Ingredient for Fast Stylization.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Instance Normalization: The Missing Ingredient for Fast Stylization

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T17:05:10.100895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:05:10.100895Z digest=sha256:f1cbf74e3db19860e3e3abc2594cafa42b58c534a9f4cd1a85be391b0bd92a93

Observation 38638c1a-bf57-43bc-b1b2-b079ac7421c4 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:12.683061Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:10.187497Z digest=sha256:2e26ff3bb88f95bae464a5cbd1fd0ba0d84ec1588323843f7aa2ff07c3137c9e

Observation 7bb6d5b5-56bd-4cc1-9a0d-4cd062ce3a6f · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:12.551891Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:10.277362Z digest=sha256:35149f17e9085b9cfc8af2f97a4821b4f447d2390ffebceb922cd0fdcabeeeb4

Observation a66fe634-601f-4aec-9b47-42a352b2a7d2 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:12.460461Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:10.370710Z digest=sha256:6a5020da330ef085ca18735cef2aad5479b3d5045b8efc28dffe312d284218f3

Observation 00f3dada-9f76-440e-b80e-bfce24116748 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:12.323797Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:10.462595Z digest=sha256:73bd2e27eba54faf29bfe919cd5eed3351d27f4989d02c1f62f5a3dab1b22b4b

Observation 7217a760-1cbd-4035-bd57-a1a4b9df1c2c · outbound

This paper cites Zhang, D.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Zhang, D

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:12.183024Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:10.576563Z digest=sha256:69018b7f154832bcaefc4f62dce8612ad389928f95101d27ac67aeb4b6d914fb

Observation db94ec46-dce6-4eef-9723-ff85515bc918 · outbound

This paper cites Zhang and J.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Zhang and J

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:12.058471Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:10.698570Z digest=sha256:9276b305c563041cba568d4fb5151b3732927c49a298b3a4f3e457d510b11ee7

Observation b6f3eab6-64e1-4dee-a64d-2f51bda28a42 · outbound

This paper cites Zhang, Z.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Zhang, Z

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:11.939539Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:10.759748Z digest=sha256:454c73912046bc18413465b22acea616af3205acedb64f5f0d32e75045aff5d5

Observation ff0b2dd0-e9fe-4e6c-ad4b-29369b2d584b · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:11.837096Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:10.847250Z digest=sha256:7d05f2b8cffc6eb902f3422aa0fc1b07c89656cf050ac1b5b2d1bff624bf99f6

Observation 0ae16223-2aba-4469-8d89-ca24fdd5ab42 · outbound

This paper cites Zhong, G.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Zhong, G

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:05:11.693567Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:10.908116Z digest=sha256:d79dcb5ef14362ff68606f13490fb76ec7a6c1c596eb2d19f0643f8afc5108f6

Observation 509690ce-1428-400b-a392-423593daf8e8 · outbound

This paper cites Domain Generalization with MixStyle.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Domain Generalization with MixStyle

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T17:05:10.992812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:05:10.992812Z digest=sha256:a570798a06aace73260334706f860e5f875172908983e8e685a1b049d0fd8d23

Observation 575a08d5-fd64-4873-8f47-f3cb1311c18b · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:11.549595Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:11.066501Z digest=sha256:320d291a8eb26141480735c4514bf3a7cbd229dabb79260c17fbe7dbea9f0521

Observation 7dff2a03-3d22-4bcb-94d9-901d2f9c28f8 · outbound

This paper cites an unresolved cited work.

CorrMoE: Mixture of Experts with De-stylization Learning for Cross-Scene and Cross-Domain Correspondence Pruning Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:05:11.387916Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:05:11.138353Z digest=sha256:a3c8606ae01d4e0d347f9cc0bc873a1e7350f424498a2d0d699d9bd3aa0d15fd

Pith citing papers

No inbound Pith citation observations are available.