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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 18 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 2026-08-18T06:34:40.430872+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=sha256:231ebb098d2f83a555288c6d62ade838e612c91775c3948d107e17aba07b7b98

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:06.918630Z digest=sha256:341f940d44d26c394e8c5f37579ee4730243ed0d1c74b994b7d0aa00e2797dca

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:07.006076Z digest=sha256:08c415de7a4d8c948f05d6412448e9af89c903432996abd929fea07192a3ab0a

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:07.099880Z digest=sha256:693069664778044121e5d060ba6c73006fa0735174cfe2e60847bae96cd7c8fc

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:07.183420Z digest=sha256:b617ce78134c7a82facd7889f283446ed6e1cc66986416e6adf2495ab3394ff5

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:07.256175Z digest=sha256:f58bc87160095e4202779b5db74dd64bc9d0275fcf0275cafec1b2b197fd5136

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:07.344579Z digest=sha256:e22fbdcd47bcb6e2c9ef78afcecee4bf2764d2dcd567aa93cf64b7c0cecf47de

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=sha256:125250b154bbbfb0fe2c164e2c89d6f0718fc2c6d9de0ff83601222ebc31e91e

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:07.534656Z digest=sha256:a62d223add4ac0c84207b4b991d33c94e440089b3466bd4bcf43301e2aafce0b

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:07.628226Z digest=sha256:786dc030730e13d940d67db932809f6808a8894e512bfa4b5c34c6bdba67bf51

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:07.728671Z digest=sha256:f6579fb118972c53487ac68bbf3ce91529dda2287db036b3f4048f0864427984

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:07.820470Z digest=sha256:36b6f3ecb2fb603b9ac58244390d409b696484f3fa95622daa28146da2e29252

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:07.914340Z digest=sha256:50d5b3aea35814e655c6cd593b0dcfd9d711dc056ec6966275371e2e3fe80a48

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:08.013711Z digest=sha256:23934cae76916f30b5a2c4f23b23b0cd397f922682757a7079d53baa2c69200e

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=sha256:5cb03f9be284ab51f8880553d73daa079c0c376c79b39af0dfef0193cc54ca52

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:08.204556Z digest=sha256:eb66220d09dbf026760cf35fca0b627c4b0afc1187c9c5303ea6e3aefa160282

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:08.295178Z digest=sha256:e625ada55137ea40dd057d9091244359fc2cbc0cb7712e13daaef2d629d0b28a

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 2026-08-18T06:34:40.430872+00:00.

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:08.510629Z digest=sha256:c2ff85d6260ea12462a7624723722aff757e320489748a89e700e92a02730700

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 2026-08-18T06:34:40.430872+00:00.

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:08.740241Z digest=sha256:ccaf15545a182c87c55a6df8e645956e49184bfc01fba6c4a7d2e19402254997

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=sha256:2d9435897f245fea720a76e7bc844fbe354ac172092a6af6a526b04ee8db497d

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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:09.063685Z digest=sha256:465494aeae3ab8a561a64210cf355ae020db79d233d3f1f1b15fa05091f5ab46

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:09.186934Z digest=sha256:08bca34839fb70c25969407969dfbf862ea5e972d0ef4dbb0b7c5daae0c6544a

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:09.278771Z digest=sha256:02a6b61050288dd4712cf7b7729bc82da10217d5cdf83fab781ee3773264021c

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 2026-08-18T06:34:40.430872+00:00.

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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 2026-08-18T06:34:40.430872+00:00.

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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 2026-08-18T06:34:40.430872+00:00.

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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=sha256:6374af3a9514b32e598ebcb4bb7513d3a14e3181db4074322e550fa971fd04ce

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:09.717526Z digest=sha256:25bdc43ad0cbc55509e6acae985891df2e3102e81a7bfcc5ef83aef6daac7e09

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=sha256:3f463eccc079a6866fd412f78b295aeb1a6c84c1538172ea12376ebfb034b92e

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:09.894720Z digest=sha256:9fbdb90b27f26e38deb71228c2538eead3be26856a4de45252f2f609ad4ab11a

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:10.008699Z digest=sha256:bc1667d36acf25788407dfdba172962c3009440483c6bc415b5a457235a4a8ba

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=sha256:589cca81e6d0de6e886acc7a78b98e43991e52d908b0ad95ff95c4a4d3171203

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:10.187497Z digest=sha256:20aa0a9c4494496e24d350c0cdef093663f2c5f736a521ea90162fd38f545967

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:10.277362Z digest=sha256:76d8a2dfd1f10e78179025501c42da01963ce128b9ced509ae1d91430f3e139f

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:10.370710Z digest=sha256:56a2c6ac37feb1ac87789d8e57d87fc1259e3624f5b9df2dee04ad996adc2e4b

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:10.462595Z digest=sha256:ec1cc588c7ed5fd9f811fd140945010340c090e9558dcc0708cdfa96a6c4be5f

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:10.576563Z digest=sha256:2893897a21eb945b00077662780db382494ded82736731b16c842efa182b6a29

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:10.698570Z digest=sha256:36a825c18c27d01a146335d8b2a1d8cb3151b0625613274aabab960a6223c735

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:10.759748Z digest=sha256:6359f7849a2218241a4d5c085f0883e7aa3837d9bfeeebca6ed209200a147a5c

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:10.847250Z digest=sha256:fec67f234c5e971f24a0d1afc7a84f1125f4053764d3145626d99e28fc9931ec

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:10.908116Z digest=sha256:e90da727c5babe8350c2125a81baf0a971b61fa4dc5defba7979eb5b7218f06c

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=sha256:6bc3d029142be245bdf73eeece6b19ae3ac6204cacfd72f39ab6d4b9f70cb2bc

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:11.066501Z digest=sha256:dc41686d0461e355928e1dec0611ca90a60a5be4697d163d07b847baac46d648

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T17:05:11.138353Z digest=sha256:1a77208fd69d5e10e6703ee0546480fa3285ee6659ca215be657f4dca62c14f6

Pith citing papers

No inbound Pith citation observations are available.