Pith. sign in

Paper Citation Record · LEDGER

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images

As of 17 August 2026, this Paper Citation Record lists 100 of 161 outbound references and 0 inbound Pith citation observations for arXiv:2505.18741.

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

pith.paper-citation-record.v1
2505.18741 v1

Coverage vector

measured 100 of 161 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:31:19.307433Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

100 of 161 outbound references displayed

  • verified exact0
  • verified fuzzy16
  • unresolved84
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f33fdd06-22ae-4a81-a32f-0d189b7ebcab · outbound

This paper cites Liu et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Liu et al

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:10.485171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:10.485171Z digest=sha256:dbd7c7866f6ff8802141e67e26bff8bd963773686bf529fbb28027a7602bcab0

Observation b04e4143-47e9-4920-9491-a26d705e2628 · outbound

This paper cites Wang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Wang et al

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:10.555447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:10.555447Z digest=sha256:8abce4b2c1fe26277a726a5c7b0698a13836b9a99af2c252076519d2c4051bdc

Observation 50f8b42b-b43c-4e57-9ad5-08505e67e21e · outbound

This paper cites Kumar et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Kumar et al

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:10.678516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:10.678516Z digest=sha256:1a856c06bac10b472331a008731c8e9b428d52af20147762685b79d2e3342524

Observation c2d58b48-2678-4245-b8c3-8ef228e460cd · outbound

This paper cites Liu et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Liu et al

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:10.775953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:10.775953Z digest=sha256:14ec25cd952408f9fbf7109f43159f67fde28f9530f09c4ad5f9edbda73f9b2e

Observation d5498230-2c32-4ed8-a3c1-2e4ab14850a2 · outbound

This paper cites Ju et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Ju et al

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:10.918285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:10.918285Z digest=sha256:96a8698219252bf6022ec16ff4be95b438f1a8b649981274845005e7f202f775

Observation 20337dee-a59c-41f6-aa6d-c4529086a798 · outbound

This paper cites Jiang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Jiang et al

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:11.049124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:11.049124Z digest=sha256:bf246f383a449097204c525a64b1e88d8cdf1f221b2be2f7dcaace658f4e95c5

Observation 32fc014a-6cae-4d51-a6b6-16aa3b3468cb · outbound

This paper cites Zhao et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Zhao et al

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:11.196514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:11.196514Z digest=sha256:0bf2256ae7170f593c35d5d78c426d82d82bc36011100c3548097fc8df1c9a13

Observation 426537c3-80f4-469e-b65e-22a7f29723a8 · outbound

This paper cites Xu et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Xu et al

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:11.292934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:11.292934Z digest=sha256:f0aa0a87b41f88a0df8b9eb97918a424cca4283b7c6398fdf604dcf3d09a8e53

Observation 77c577d2-022b-4ad9-b69d-e66428b1bf83 · outbound

This paper cites Gong et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Gong et al

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:11.470931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:11.470931Z digest=sha256:2e90f748688ced678d1d8d7bd508f1e5d6792b5f2d30ec8384d37d4ac149dade

Observation 443cee3a-0171-485f-867c-81f5b687f330 · outbound

This paper cites Warburg et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Warburg et al

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:11.600591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:11.600591Z digest=sha256:e0594c865e64991b57b515b9b50a3980daba7ef0336e31c20b2e034e74131eb9

Observation 52ec84da-943e-4794-8726-a1b80d61e469 · outbound

This paper cites Mao et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Mao et al

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:11.706126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:11.706126Z digest=sha256:2e806a6826f74439a3d2e5584440f64699915043f700f814a89ae449d804c9c6

Observation 28f9683e-4878-408f-812e-43b3e0a1a163 · outbound

This paper cites Dokuz et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Dokuz et al

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:11.806714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:11.806714Z digest=sha256:22e4fe51cb770bafecf3863b90946cd459d5b45e03791404ea0a557b3597a28b

Observation 8abc19c3-1eb9-4484-bfb5-a33173c9521e · outbound

This paper cites Liu et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Liu et al

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:11.914773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:11.914773Z digest=sha256:bad5601b42bcd3a8e12a7840a43e141a93681e119d5958f004eb08b049e63d1d

Observation efd64b2e-5a08-47d2-bcdb-0b61d700e0af · outbound

This paper cites Morerio et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Morerio et al

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:12.024867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:12.024867Z digest=sha256:ae9ab5ab0caa27326cf91d4a6b7dbe5f516e231cec59c40b85aaadfff5316cdf

Observation 14836065-a4cf-43f7-bf00-a27e3ca8e66b · outbound

This paper cites Binkowski et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Binkowski et al

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:12.125759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:12.125759Z digest=sha256:645b77239d274a4c0c4eb0f89f3954d6be10e67e12dbeaa5b721ddc8fc6c2f62

Observation bbc1b085-5d28-41a5-a55e-aafcd526ee0e · outbound

This paper cites Kong et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Kong et al

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:12.297570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:12.297570Z digest=sha256:979301d26282086f5568f6dc326b26eee1c2d116d6e0cfea9aab5219cae96472

Observation d1e3a1f0-b450-49cf-937b-8c0648ec1e16 · outbound

This paper cites Wang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Wang et al

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:12.418481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:12.418481Z digest=sha256:89c255fa2ec43b945fc90ead481758854fe25a23b1a1b409b0d55403296faf08

Observation 3a1e4718-28b3-42ea-a493-7aa8ed6b9f21 · outbound

This paper cites Meng et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Meng et al

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:12.555789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:12.555789Z digest=sha256:96c65af69721960368067ee7b9515a9ace3bac0d869d22ea2c1dbbb3b2fdd25b

Observation 9b4528d0-fd8a-4010-9982-d0a60ba5d2af · outbound

This paper cites an unresolved cited work.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Unresolved cited work

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:12.638297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:12.638297Z digest=sha256:0f7e763c670ebbe59412dddf7e4c613089e2a8d3653e508ad59bb41418c5cd5b

Observation af9ee918-0cdb-4bbd-8cc2-6f8139dba789 · outbound

This paper cites an unresolved cited work.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Unresolved cited work

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:12.765396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:12.765396Z digest=sha256:876dfcbfd978e9fb0c011b1615ecb66fcbc7f89513b611fa79daf5aa0e11c263

Observation 6fbeb950-ab83-4a8b-88d3-83539fd7adf7 · outbound

This paper cites Yang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Yang et al

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:12.848088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:12.848088Z digest=sha256:b6c030122d8c3a2a2b3dea7fd2e457a86f5eb9db054e0f089ecfcb838cd84d31

Observation 873d46ce-8bcb-4d07-9e39-fa65a2ada78f · outbound

This paper cites Tang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Tang et al

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:12.961808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:12.961808Z digest=sha256:9f85a3b82083e04b628a41418ede9f7f7c6a028748a6de5e9a1d0ab76fee7e08

Observation 559aa647-acaf-4207-9bc4-c16e5b051a61 · outbound

This paper cites Tang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Tang et al

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:13.110983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:13.110983Z digest=sha256:4a428b216d27b13504e0973af993826af725f933e2fe6a2c25c31bd2db786700

Observation 7fbbb0a0-0558-449d-951b-31811693e721 · outbound

This paper cites Zhang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Zhang et al

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:13.197428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:13.197428Z digest=sha256:029fa30a0c4afe912b21bcb7a635841ac2c77af5b17a438bea321ffeeff34baf

Observation 2296d45f-8192-4905-90fc-be29ec96ce56 · outbound

This paper cites Zhou et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Zhou et al

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:13.283317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:13.283317Z digest=sha256:90f4c07bd7785fb3c7075e1f1994ae3431119bd6d17c0dff93662f88980cd3fc

Observation 7653128d-3c37-46b0-89ae-46aea003ecaf · outbound

This paper cites Han et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Han et al

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:13.369376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:13.369376Z digest=sha256:deb52137d054563476f331ac76e828361642ae1acf622b0d395af59ea61f8d7e

Observation 68ddbe1c-b5b6-4f6e-86df-afe26fe0762f · outbound

This paper cites Ghasedi et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Ghasedi et al

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:13.437266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:13.437266Z digest=sha256:61d46e8db88872d3f3986066f28deaffb470b003cfd0380474a59568cb74ec5b

Observation 23ee58e7-e679-4fa0-915f-e560f9ceeb40 · outbound

This paper cites Gong et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Gong et al

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:13.490152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:13.490152Z digest=sha256:d91b9ae3b5ce016fd71e5577a73a183ec6e5e955a813d7d98891d133baaef4e1

Observation 55db9b49-3403-4856-b4f5-4507d70b8720 · outbound

This paper cites Zhang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Zhang et al

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:13.523076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:13.523076Z digest=sha256:9d9e20e3a5a1400be08a2587bf324ab05e0704b72d068d7b3cb599392a4fc2bc

Observation c19a04c9-e594-4b84-9294-72b75676a1bd · outbound

This paper cites Li et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Li et al

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:13.602893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:13.602893Z digest=sha256:0877a4e1f45fc1ea7fc03596e2343174d62135d148f60129033aaa268b79e8ad

Observation 0816296b-1787-47db-81f0-143b64033a35 · outbound

This paper cites Lin et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Lin et al

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:13.675315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:13.675315Z digest=sha256:0c0fe868dbd997e7667d867cee78297600357e03f9cb98223df30432e3101329

Observation 0e7a0f19-4fee-4818-8d0a-142dac5439de · outbound

This paper cites Tang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Tang et al

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:13.717799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:13.717799Z digest=sha256:9ac0d3f89317d1b572b1f675a2cb82a0cf244bbf4c62b2ac46e0c7d992061dc1

Observation 74a106cc-9e9e-4d98-8760-71b372d95dba · outbound

This paper cites an unresolved cited work.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Unresolved cited work

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:13.776765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:13.776765Z digest=sha256:afa938762e958fd2921e8da4f517b6227440af2270f37909f9b6078cc2895b80

Observation 694fed22-3a7d-4fb3-b9b7-59035cf6df0e · outbound

This paper cites Gal and Z.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Gal and Z

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:13.821524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:13.821524Z digest=sha256:523ce941647caaa14bd79d82cc61b243f7b84177470005b863ce5186060256de

Observation 39fca1f7-42e9-4f13-a3e9-4da77c1c8bda · outbound

This paper cites Teye et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Teye et al

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:13.879379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:13.879379Z digest=sha256:2cadca1b6fa4cebf5511dd9c7a46078eeb574f09a9e5919688e420a9a6f9a5f9

Observation 0b25e100-cc27-4175-a214-f11406af0300 · outbound

This paper cites Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:13.935509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:13.935509Z digest=sha256:079b205b1c4f30cfb8802a9edbe6ac16fb6723d15047bc14825d612d56b2ef1e

Observation 13efe802-b4c6-4e4a-8891-cf7a75d1b276 · outbound

This paper cites Corbi `ere et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Corbi `ere et al

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:13.977657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:13.977657Z digest=sha256:b0f0bd0462c7efd63f0abdd01409ac2fee5bc440bcd54fe964962c50c2beae78

Observation 11ca4ec7-deb1-4653-a910-89159e2c7b46 · outbound

This paper cites Yang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Yang et al

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.032058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.032058Z digest=sha256:2fad119cf6868829029522274a16fa6a0543ad8316b8cac9d3b3ba51de15490e

Observation 46b3ad86-4bfc-42d8-bd95-735d4a7c87c8 · outbound

This paper cites Zhou et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Zhou et al

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.079399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.079399Z digest=sha256:64479d9f203b2da7aab105f4ba8ba41563b62f589f84a22b2636dd37f6f2aeb2

Observation d53426c0-61c9-43f8-9145-226ebfad1dd8 · outbound

This paper cites Tang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Tang et al

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.124178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.124178Z digest=sha256:926a7a37f0e1d4d21befa3966cc874d657f7479d81fa948df176bac09041df17

Observation c822475f-0da2-4783-bcc3-ffadb23b802f · outbound

This paper cites Xia et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Xia et al

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.166174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.166174Z digest=sha256:e8ab7891a727fbb4c4843ce26dd58fe6f47ba7946e94871efde84e1d46a3afdb

Observation 59040362-3a23-44e8-8878-ee8b807a46c5 · outbound

This paper cites Yan et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Yan et al

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.220388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.220388Z digest=sha256:4009e451568a76b593e4d0eff6776c074ea7681622cdbd1e5d279cf4906b8ac6

Observation bb166ac8-798f-4e5b-b825-0f142d70a5f3 · outbound

This paper cites Shen et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Shen et al

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.278721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.278721Z digest=sha256:6612af06f9b5170f33407d02ff94b071eaf09fda67d54488fc5578f621dd50f0

Observation c4dd3e9f-d7ae-40f4-b8e8-8283853377a2 · outbound

This paper cites Peng et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Peng et al

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.324496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.324496Z digest=sha256:8bd6a778dd9b606fb5068a3327d68590b5250c5f4751cfb9744b0998c0267bde

Observation 93c2865c-1bd8-4661-9174-f0389a2d645f · outbound

This paper cites Franchi et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Franchi et al

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.382010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.382010Z digest=sha256:aa09bf950342dcd06b3a28f1370c6a30e01ac3a6b2841953a4fd24d551cca667

Observation 46a26c98-e2b7-4559-8632-56e82e494544 · outbound

This paper cites Won et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Won et al

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.444537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.444537Z digest=sha256:295473e5cdcaea3ea2d21a22d113611f0745c5c30f725861fcde29c02c0a4e39

Observation 5fae3c31-5306-42d0-8b60-18a1c9bf48e4 · outbound

This paper cites Yang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Yang et al

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.495104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.495104Z digest=sha256:8c3e001c17823c24b83c7c34a8fe9a91c93603a243ca5a1e6bd5a3e3776f48d1

Observation 1df14e63-fdf3-494c-9b38-b36790a0a868 · outbound

This paper cites Training region-based object detectors with online hard example mining.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Training region-based object detectors with online hard example mining

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.553246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.553246Z digest=sha256:5993d4e84fc730977d2f3c3af64e18cd4ada7cba683eb922cd78a55b71b18be2

Observation 75b4ade2-47c3-4316-94fd-c1ba54c1547e · outbound

This paper cites Dong et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Dong et al

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.595845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.595845Z digest=sha256:999ace01ec87f4f72139ce4e8c2129b441ea08206798cf477e95e95fba43af73

Observation 77f0c2eb-7606-4e4b-a5df-ab1ee6c347a5 · outbound

This paper cites Sun et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Sun et al

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.644356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.644356Z digest=sha256:2190a6175724e0f088d4c5ad0d8d60914671e09712ceb76248f87e678aa98bb0

Observation cbaaaf86-8d73-4856-a18b-61746da63bd7 · outbound

This paper cites He et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images He et al

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.702905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.702905Z digest=sha256:ae20d4c8665fe838533dc30c2d9c835c6e38bf736068a14393da510051abc119

Observation de70ef48-9147-46c7-ba33-92805919d520 · outbound

This paper cites Xu et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Xu et al

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.746958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.746958Z digest=sha256:b5ef28165aad51d6e233f130cc5a22bc49596bcf9041c1882da876b449aec2f1

Observation 614a650e-41fa-4951-9b06-bdd0e70f1047 · outbound

This paper cites Zhang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Zhang et al

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.813588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.813588Z digest=sha256:02209bc8c7aa03cd2bdafb0ce0017c8c5cf8101fea387f2a9e7fa6ce0b161640

Observation e614fc8f-9530-4ab9-b3a1-4b0aba52a61b · outbound

This paper cites Li et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Li et al

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.874495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.874495Z digest=sha256:26c2c1ed08bb2af2600a2d7a5fe8a838eff83844a5512178047cd4791efc595e

Observation cb0a1050-00f0-47a1-b65d-ef0f28a07dff · outbound

This paper cites Tan et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Tan et al

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:14.971957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:14.971957Z digest=sha256:1585501e131f597025a922b589e6295bdf0c658d51eece78b2a8e3684384c665

Observation f951cbb5-d5e5-46e2-94f0-7edf6e8cf89a · outbound

This paper cites Cui et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Cui et al

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:15.030157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:15.030157Z digest=sha256:3b204ad59a2a687949396c17a3e4e88877e9383aa645e26ee35ab31d35e165b4

Observation 3878cca4-b836-42be-b241-0d9afff37b3b · outbound

This paper cites Hou et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Hou et al

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:15.090581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:15.090581Z digest=sha256:1b1dc5e7bce3233636b8f4fd235e51b88499b0574761b1713cdff43909cf2f21

Observation 6392dc30-93aa-4d6a-9b83-82f1ba8ae498 · outbound

This paper cites Zhou et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Zhou et al

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:15.124650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:15.124650Z digest=sha256:20bac595dfaf4a4c56cdd107a803a9052e6cfcbd2fba40f664ee9850735b232a

Observation a98517cb-9780-4474-8552-ce3492ba94ba · outbound

This paper cites Jiang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Jiang et al

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:15.165213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:15.165213Z digest=sha256:016f581954820f917ce9610d72f1f16a8b8b659ca09795ac3fd211af138eb787

Observation 79cc34c9-cade-405d-a270-40d87ae6c32b · outbound

This paper cites Lin et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Lin et al

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:15.268812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:15.268812Z digest=sha256:c86a4b1dcd5bd8d77b9807b73cb89534db6442dc4e326af6471e3dced34791d0

Observation 00d2f799-e28b-46e5-917f-836c7a643ebd · outbound

This paper cites Ren et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Ren et al

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:15.388692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:15.388692Z digest=sha256:482beede2fce6a715541810add1a44f1a64cbfe23345ec93e0d13da706bd4583

Observation 243064d0-cbd9-4f22-9ebc-5d84a2f1a154 · outbound

This paper cites Cui et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Cui et al

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:15.493109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:15.493109Z digest=sha256:ffec48a58c2cb843d16f06a42adac3af3f7e7c3dfde406af4e09ac6c052b3104

Observation ae3af71f-4a94-4281-922e-3f6e1a5da257 · outbound

This paper cites Huang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Huang et al

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:15.618767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:15.618767Z digest=sha256:f7f439307805da19d45801c885a2e695f79d735f2d195053cb47096428819174

Observation 81f978b3-a069-48ae-9430-1d4f7b998254 · outbound

This paper cites Khan et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Khan et al

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:15.703717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:15.703717Z digest=sha256:22fe070e5fc5d5d74a54d52253404ae063bbeea02a868cdae908d0d1a2a85e77

Observation 8bc7a64a-c714-4333-af92-955a12f7ef47 · outbound

This paper cites Tan et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Tan et al

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:15.803193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:15.803193Z digest=sha256:5cb3093766acf32821a1d57e4c7757c30b905995550a88f992f48644b304abca

Observation f9c0c049-852d-46f7-9ffa-8c8117a477ac · outbound

This paper cites Park et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Park et al

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:15.892780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:15.892780Z digest=sha256:94a8f5856a10fac0ca2b84cdb1acc9974e7c4d59219abee1766e1097936ac492

Observation 40a6e34c-7002-48bd-baad-35b5e87ff44b · outbound

This paper cites Li et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Li et al

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:15.987732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:15.987732Z digest=sha256:7e05018b819ed4afb5ea86c863f2cbf823768cb94186470c940df4755f2193db

Observation 5f167d5e-5224-4ce5-91d2-fcece86e387e · outbound

This paper cites Long-tail learning via logit adjustment.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Long-tail learning via logit adjustment

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:16.065848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:16.065848Z digest=sha256:3cbaacdd5cb8e232e6936b9164b85d7fc485a42af719c74689ac9a0e13d4c9ef

Observation a9b7f880-c754-415e-86b3-ecca0693829d · outbound

This paper cites Hong et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Hong et al

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:16.182647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:16.182647Z digest=sha256:40e8a791f9ef00ea3f1de10ffb19de676b965b7f8ec13396b99d25a608e70f7e

Observation aa795d02-6057-4371-b9be-eb74192d8722 · outbound

This paper cites Tang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Tang et al

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:16.344291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:16.344291Z digest=sha256:df008a7dfae9942a43118e36227e25943c7c4c1815572ff39aea765161e7f176

Observation 21d80975-2553-420e-ba56-3836a5bc1c30 · outbound

This paper cites Zhang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Zhang et al

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:16.472548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:16.472548Z digest=sha256:2e3eb72b4d7bf33fbfd1576d58b683535664f3767155a58d26f559ebf37a4af1

Observation cc2a01bc-4f3d-4c78-965f-d4d276b4fc72 · outbound

This paper cites Cao et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Cao et al

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:16.608859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:16.608859Z digest=sha256:0138dd5a1dfc29024267b7a870dc62e1b6f1a1048bb8af05bc55d9aafc53bffd

Observation 97503ecd-7cc5-4806-9426-9fa9ddcf4f60 · outbound

This paper cites Cao et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Cao et al

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:16.790657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:16.790657Z digest=sha256:39f484c149ef1b9008dff5b5a004a02943b09902f4766027423f2a68691b77b1

Observation 1acb9f3d-11d0-4592-9073-9734bc1ef2bc · outbound

This paper cites Wang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Wang et al

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:16.913323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:16.913323Z digest=sha256:25d797cf33c8898def90c781de7b0f170eaf980d00541132e297a17e6b88fdc3

Observation 72955919-b765-41a1-a1bb-0ae95d3669ff · outbound

This paper cites Zhong et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Zhong et al

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:17.037196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:17.037196Z digest=sha256:5b89f70fbeb6ffe1d75a46bc13c26e9cc2a7394de67a99d1e69186b9ce1a8e64

Observation 3bf9a5dd-68f0-4bb8-8590-9d4d7b0df181 · outbound

This paper cites Zhou et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Zhou et al

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:17.160121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:17.160121Z digest=sha256:dcf91520dffd52886aeb194e089984584bac080f92767bc91820577cf839dfa0

Observation 7b9a9e49-64f7-4cad-bdad-2ce148c88513 · outbound

This paper cites Wang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Wang et al

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:17.259477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:17.259477Z digest=sha256:58215e942b366822233ce4d53cf28a44de9eb9707ba1054a1eb0ed1da0ab713b

Observation 73efa748-2fc4-4845-9e80-37e73668dd64 · outbound

This paper cites Song et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Song et al

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:17.373721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:17.373721Z digest=sha256:feb3ab1abf7e5cb75fccbac1922b6e2bf0ef65aa34a53ea35e908dd9c5ef21de

Observation 245759d6-8c18-4f7b-9817-c845628cd570 · outbound

This paper cites Xiao et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Xiao et al

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:17.487524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:17.487524Z digest=sha256:2cb68aa2a04fc54518c88b6c676be20e8755e1e1e2a416c44bcc5f087ab2e280

Observation e88b62e1-8384-45bd-a22f-6485762af7f3 · outbound

This paper cites Chen et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Chen et al

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:17.614485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:17.614485Z digest=sha256:70e83dc946de31e476b0f5f0ae56277d6b39baec91d5b5f26c9142441def739f

Observation cedaecda-9738-492e-99e5-105576dd7c6d · outbound

This paper cites Goldberger et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Goldberger et al

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:17.727207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:17.727207Z digest=sha256:0cada09e02c161458ab6abbcd4ba1771c61a2996b64e7b0d77d636a1d1b1b8bb

Observation 1a9e8bd4-0425-4136-ab30-beb315653618 · outbound

This paper cites Han et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Han et al

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:17.880033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:17.880033Z digest=sha256:8dc469d8b5ef4eb736b8c8a7aa79a2c0763af7d558a5a25e50a787b8ea6eed12

Observation 9a43474f-d278-4917-a16c-ac98819ddda9 · outbound

This paper cites Cheng et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Cheng et al

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:17.965740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:17.965740Z digest=sha256:4ccb919b457259f378d9e8f424420996a1255f86185784b6e0a5255b59c6df4c

Observation 7c8cb34b-d37f-4bae-a80a-c8179a2f7497 · outbound

This paper cites Jindal et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Jindal et al

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:40.452000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:18.057212Z digest=sha256:ea9732e7c40423054bbf2c66c2a8adaede0a7118896b21e63ceafa23a41cb474

Observation bd51fdc6-9124-4871-b472-43555f67ff0b · outbound

This paper cites Lee et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Lee et al

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:40.285878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:18.163231Z digest=sha256:493fe3ff489161260320fc1853d2c498ab74c93a41b86a9f44160ef6944d43d8

Observation 841788d6-3e8d-43c7-95eb-ce7da8f3b4ad · outbound

This paper cites Zhou et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Zhou et al

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:40.142596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:18.231102Z digest=sha256:97b556249e63d50b6a538e8506c2e9df51ca29cf0220883a4a6dddd78d6176fd

Observation d14fe451-8a56-45b9-9879-6b2a0c1e3872 · outbound

This paper cites Xia et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Xia et al

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:40.005790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:18.302218Z digest=sha256:acd16f0e73ab55219367978163e1db8d8cdb303c3cb38ee66dac1291207efff7

Observation e3958592-fed6-455e-bbbf-122a07c890d6 · outbound

This paper cites Xie et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Xie et al

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:39.864001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:18.376804Z digest=sha256:52b45bd6d9bfac91c9e05139fd0a7b307c46405cf5b23bb1fde6969616d6adb1

Observation 0d9b7a26-961a-4cad-a143-35b0e2efb7d0 · outbound

This paper cites Gong et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Gong et al

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:39.689193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:18.472235Z digest=sha256:30a0e61bebd9ba976df0fe989d69716c4b78bd54f8e3b6c5cc1fea7a9bd08809

Observation db56af5e-132e-47e8-9d58-6497892de690 · outbound

This paper cites Fatras et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Fatras et al

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:39.497953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:18.552347Z digest=sha256:a2130bc493354856c1065a98b2d182bdc370e9d8d303d8634eb0c36daee8244a

Observation 7504817d-c2d3-41f0-9268-59d88ecc35d9 · outbound

This paper cites Yang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Yang et al

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:39.318587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:18.627707Z digest=sha256:b35da5e158463b70f34fa44e27b354be7933f79bbd329af90a6b90710e512a0b

Observation 530c1789-be68-4d57-9b69-7b43699b0be4 · outbound

This paper cites Tanno et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Tanno et al

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:39.131583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:18.706475Z digest=sha256:a7aa50a7537f8669cbe19f67d88be68092a42a51752c852f248fc1f950cecc22

Observation 233699ac-5468-4e13-babc-ed9388f6a002 · outbound

This paper cites Menon et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Menon et al

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:38.891672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:18.787897Z digest=sha256:de91699c8bd723748f93c981cad9a268348672b35d61de9e7abb82051cc49f65

Observation 82aa6f94-ffb0-4da0-b869-c81c7447a70b · outbound

This paper cites Xia et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Xia et al

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:38.625667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:18.882880Z digest=sha256:93e71ea29a37aefbd7b6648844b9f70567606eb54515a89fd083452fdf1d209b

Observation cfb5f403-cc24-43c4-a8c0-0d6f5f724222 · outbound

This paper cites Wei et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Wei et al

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:38.396279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:18.985801Z digest=sha256:f392592e651ee5b05150b9745b489de2189fab1a390685d8d197b302ecfe6fb7

Observation f8396b58-c21e-4ecf-9b52-33c5dc4faf68 · outbound

This paper cites Regularizing Neural Networks by Penalizing Confident Output Distributions.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Regularizing Neural Networks by Penalizing Confident Output Distributions

Reference 96

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:19.089831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:19.089831Z digest=sha256:b6c17e9c2306fbdfff87031b91002e68a6c6b7b75344be9e3653308dfa39bcf2

Observation 8d2e4cff-1ce3-40d0-a9ee-7c774b59dc63 · outbound

This paper cites Lukasik et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Lukasik et al

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:37.991889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:19.133817Z digest=sha256:7a553105c2dede045d6acb9677d2a5a87b9394c17777ef373ab51203758593e9

Observation 3e59d5d2-af7a-49fa-8976-a0279f06ea11 · outbound

This paper cites Wang et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Wang et al

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:37.700456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:19.191992Z digest=sha256:09cf217dc39c4cbf3300d72e68a8e7e1e6c78faf70fde12a090aaa2ee8743528

Observation 322d618b-232b-4b5f-bb5e-aaad863478b3 · outbound

This paper cites Feng et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Feng et al

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:37.409925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:19.240997Z digest=sha256:033cad8039e01d1e154e47bb0608e4d7b5153f4fdde452d5c3e84cc381249710

Observation 4d412a62-3cff-4f5f-afe7-1465f5acbdb5 · outbound

This paper cites Liu et al.

MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images Liu et al

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:37.162748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:31:19.307433Z digest=sha256:0e43943ae3dbccf0ee7437af28340c52a0fb5b0430600a188c6366f23b624e26

Pith citing papers

No inbound Pith citation observations are available.