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Paper Citation Record · LEDGER

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation

As of 9 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2506.06748.

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

pith.paper-citation-record.v1
2506.06748 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:53:10.443418Z

measured 24 of 24 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

24 of 24 outbound references displayed

  • verified exact0
  • verified fuzzy15
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 19a82926-2c95-4aa3-bcea-5bd2d73fed26 · outbound

This paper cites One- shot video object segmentation.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation One- shot video object segmentation

Reference 1

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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 d4b009cf-e521-4bee-b322-0214b6f4f35e · outbound

This paper cites Xmem: Long- term video object segmentation with an atkinson-shiffrin memory model.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation Xmem: Long- term video object segmentation with an atkinson-shiffrin memory model

Reference 2

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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=2026-08-07T05:53:10.372867Z digest=sha256:1e217cf96386f532b4b623408ab366ea810e96e7b4fa0a96a9db964a5fa2ce6b

Observation d25ee1b0-3f5f-43ae-91e3-888e0fe39b4a · outbound

This paper cites Rethink- ing space-time networks with improved memory coverage for efficient video object segmentation.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation Rethink- ing space-time networks with improved memory coverage for efficient video object segmentation

Reference 3

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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 a1c78d10-fc14-446f-8dac-9c7e340d831f · outbound

This paper cites Putting the object back into video object segmentation.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation Putting the object back into video object segmentation

Reference 4

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raw_fallback, observed 2026-08-07T05:53:10.644530Z

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=2026-08-07T05:53:10.379426Z digest=sha256:80472f2fea67807493c94ec4534b1bf151166c3ec5a198c23c2b1868bb6a7423

Observation 941f7b66-6ae6-4f07-8b74-270d4f96a4b5 · outbound

This paper cites Epic-kitchens visor benchmark: Video segmenta- tions and object relations.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation Epic-kitchens visor benchmark: Video segmenta- tions and object relations

Reference 5

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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=2026-08-07T05:53:10.382571Z digest=sha256:673ddd255213282b9e7160da7a5f2d4a9c218d210b69f997a483e3a5239d539f

Observation a1cf217f-134b-4a30-a321-5aeec0587cf2 · outbound

This paper cites MOSE: A new dataset for video object segmentation in complex scenes.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation MOSE: A new dataset for video object segmentation in complex scenes

Reference 6

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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=2026-08-07T05:53:10.385897Z digest=sha256:a250b592e743928eee5e03ff4dd00295d167aa17fa93294f734eb50df98e4c00

Observation fc2dfb4c-ce12-47bb-9e93-18b824d08f2d · outbound

This paper cites SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:53:10.389194Z digest=sha256:1828d405077141fbcaf262fa1d750a41ff7a7e71530a462eabb9b942eda9224e

Observation 1102344f-e822-4535-961d-45abdfe6b9f2 · outbound

This paper cites Deep learning for video object segmentation: a review.Artificial Intelligence Review, 56(1):457–531, 2023.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation Deep learning for video object segmentation: a review.Artificial Intelligence Review, 56(1):457–531, 2023

Reference 8

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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=2026-08-07T05:53:10.392628Z digest=sha256:21c1bfb9ad57d50e7852aa72937087ef8a99292fbb43a5052c90c3869b3c6408

Observation c2a2926a-1205-499e-a68b-6ac7e00dc630 · outbound

This paper cites Ego-exo4d: Understanding skilled human activity from first-and third-person perspectives.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation Ego-exo4d: Understanding skilled human activity from first-and third-person perspectives

Reference 9

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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=2026-08-07T05:53:10.395481Z digest=sha256:be8d1a6f76e6916d48a2c274c99398eb687eea8a6b8564fab9006745f44c6d98

Observation 43f6b820-f8e6-443c-8814-23572813fa5d · outbound

This paper cites LVOS: A Benchmark for Large-scale Long-term Video Object Segmentation.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation LVOS: A Benchmark for Large-scale Long-term Video Object Segmentation

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:53:10.398572Z digest=sha256:e2c23aba0a26be215edf09b5538962d2c29da094c78385113739bd234d990035

Observation 16d95078-7ebb-454b-a0c4-3c27e8b383aa · outbound

This paper cites Video object segmentation with adaptive feature bank and uncertain-region refinement.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation Video object segmentation with adaptive feature bank and uncertain-region refinement

Reference 11

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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 687cdb10-da89-4b1b-b2ee-628cc908583a · outbound

This paper cites Video object segmentation using space-time memory networks.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation Video object segmentation using space-time memory networks

Reference 12

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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=2026-08-07T05:53:10.404328Z digest=sha256:5e0c6e6b4a3f4b90088db0d0a20037ccba4bda7a431fa102d62ec6f7009dd779

Observation ff231224-9342-405b-a099-a12e4d4485d3 · outbound

This paper cites an unresolved cited work.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation Unresolved cited work

Reference 13

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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=2026-08-07T05:53:10.406886Z digest=sha256:59fb9cf6bcd01efd721bc56f5266f6c9b6367d2e2b708cf74d63c09609313700

Observation ad4e75bf-c6ed-4297-a0c7-36e540a42f4e · outbound

This paper cites Hd-epic: A highly-detailed egocentric video dataset.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation Hd-epic: A highly-detailed egocentric video dataset

Reference 14

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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=2026-08-07T05:53:10.410176Z digest=sha256:38630e2ca27ffda456aa89b606adaba48b3dc45908f2939cb4885f99119c0410

Observation e8fba540-06d8-4cbb-bba9-fb6528151569 · outbound

This paper cites An outlook into the fu- ture of egocentric vision.IJCV, 132(11):4880–4936, 2024.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation An outlook into the fu- ture of egocentric vision.IJCV, 132(11):4880–4936, 2024

Reference 15

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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 037fd328-2d0d-4774-8016-4bd121ff6e34 · outbound

This paper cites The 2017 DAVIS Challenge on Video Object Segmentation.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation The 2017 DAVIS Challenge on Video Object Segmentation

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:53:10.415724Z digest=sha256:19479a8505cb354974a9d561fc810129ded11381c4794b24c898b3cf6369d906

Observation f98f7708-bbaa-42eb-8627-2d312e3d8eed · outbound

This paper cites Vi- sion transformers for dense prediction.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation Vi- sion transformers for dense prediction

Reference 17

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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=2026-08-07T05:53:10.419058Z digest=sha256:72bce590a6e67b09aee1d7164b9d83b699d7e71b38f1431b0b30a546f123ecd9

Observation c84fca61-5c02-477e-9a22-5b40a08f1b92 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation SAM 2: Segment Anything in Images and Videos

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:53:10.423028Z digest=sha256:f3374b6dfefd8630859826eb667595249e42fadb0284ab01ee8b5640b81f230f

Observation a9d641a0-7279-4079-8b35-921d99958325 · outbound

This paper cites Hi- era: A hierarchical vision transformer without the bells-and- whistles.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation Hi- era: A hierarchical vision transformer without the bells-and- whistles

Reference 19

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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 290196ea-093f-41f3-87bd-c9a12f9af0f8 · outbound

This paper cites A Distractor-Aware Memory for Visual Object Tracking with SAM2.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation A Distractor-Aware Memory for Visual Object Tracking with SAM2

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:53:10.430158Z digest=sha256:95ed5cdf0a74d329c48526d06d009fdcdeec9d3956abce70399c21c5afa5447d

Observation 70887bb4-34a3-4fe3-af64-a5ec28897730 · outbound

This paper cites Feelvos: Fast end-to-end embedding learning for video object segmenta- tion.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation Feelvos: Fast end-to-end embedding learning for video object segmenta- tion

Reference 21

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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=2026-08-07T05:53:10.434401Z digest=sha256:557069be2f34ce746a8dccb52eaf879f379fac391cc188e962b8379c283eb0b9

Observation 68d8fad7-d0e9-4b5d-bb39-930d446d4197 · outbound

This paper cites YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:53:10.437191Z digest=sha256:3fbf2186ac14a53323d5b9c936ee1203fd260f4411892c1069ec3fb353f781dc

Observation 1f06af49-3be1-4c6d-b98c-c8c3f86b6ab7 · outbound

This paper cites SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 23

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no resolver link, observed 2026-08-07T05:53:10.440098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:53:10.440098Z digest=sha256:40ac3637c72c42821c01e29efb22518cd54a60ccf82cf1045e94ce6280efcd0e

Observation 8407f388-274e-47a0-91f8-bb5cbced8cab · outbound

This paper cites Depth Anything V2.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation Depth Anything V2

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:53:10.443418Z digest=sha256:7122d679f9fec5e0336ef5db4219764801d1de7831af193a8f5cea1d51455806

Pith citing papers

No inbound Pith citation observations are available.