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Paper Citation Record · LEDGER

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 78 of 78 outbound references and 15 inbound Pith citation observations for arXiv:2506.22624.

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

pith.paper-citation-record.v1
2506.22624 v1

Coverage vector

measured 78 of 78 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:05:07.938967Z

measured 93 of 93 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 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:40:24.622372Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T15:09:55.141278Z

Reference resolution

78 of 78 outbound references displayed

  • verified exact2
  • verified fuzzy19
  • unresolved57
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7dc7beca-6e6d-4825-babf-beccf2672657 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:00.190511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:00.190511Z digest=sha256:65245675f1b4027792533426f3e63e84b4361d3dc581cb81198588e46c03fca6

Observation 25b4e56d-5bb3-444d-ab3f-8cff45ed19cf · outbound

This paper cites Qwen2.5-VL Technical Report.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Qwen2.5-VL Technical Report

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:00.315457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:00.315457Z digest=sha256:74d94859a529c17b6efeb8d777b97fffb4f3c3798489b35b9e46a1165bf196c8

Observation 03293463-6f2b-4777-a275-47bd62d18ecd · outbound

This paper cites Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:00.442051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:00.442051Z digest=sha256:f4b5b91a91062950a11843bd443eebf3c90a33229f87cba750fe1f8d6a2ad53f

Observation 376c2248-2d23-4712-9212-1b6f5d56d96d · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:18.407551Z

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=2026-08-06T22:05:00.606554Z digest=sha256:422af2b7c87f3e2a85850e00eaf6bacf5fcef0e520167dcb62eaf8e16c9ee953

Observation 80d85c8e-bfb7-480e-a611-264d3efe73ab · outbound

This paper cites Cheng, I.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Cheng, I

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:18.115855Z

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=2026-08-06T22:05:00.713549Z digest=sha256:1ac8bad0a90d4a9aabcc8b54af1a34e624cd6646727f9a84fdd42faf8d266268

Observation 89f6b5cd-a1d8-4709-ac63-e239b580dc92 · outbound

This paper cites Cheng, A.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Cheng, A

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:17.944950Z

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=2026-08-06T22:05:00.754556Z digest=sha256:17b557bd3a45f5f6a53333e04c89d04ef3d1303858fbb22e12e9e43ac8ab0359

Observation b236546d-f0d3-4fca-9653-c338202a26f2 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:17.754130Z

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=2026-08-06T22:05:00.859810Z digest=sha256:83154dab90e44e1d3253895636ec0762a83aaee76ad94da42a3bfcb578d9f16e

Observation 44740271-a294-48cc-9ebf-c8dac74201b4 · outbound

This paper cites FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:00.945471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:00.945471Z digest=sha256:4532fa75438e7f6b25da13afd12b1e22a1c6abf9c18959955db05b0364ae733c

Observation 06c92e87-8fc0-4f86-8c78-311fa1c86391 · outbound

This paper cites Fan, M.-M.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Fan, M.-M

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:17.541632Z

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=2026-08-06T22:05:01.017455Z digest=sha256:a1ba38accfde292eed5ab7edf78a663d6fe4b3fe2fb8191b458815f5e95d3c56

Observation bed1fd0f-121f-4d79-b29b-e080aab63ce0 · outbound

This paper cites Enhanced-alignment Measure for Binary Foreground Map Evaluation.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Enhanced-alignment Measure for Binary Foreground Map Evaluation

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:01.096230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:01.096230Z digest=sha256:7a35291803532d30bb59f20cf60044330bab6e0eb7cefdc890956cb0a80341c9

Observation 0ab4c526-4c19-4f4b-a279-36e45566b393 · outbound

This paper cites Fan, G.-P.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Fan, G.-P

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:17.422520Z

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=2026-08-06T22:05:01.182278Z digest=sha256:672b9a2b4ebe475f279edf7a1c18dbb09f944063a357c8a83a65f9df320ea662

Observation 5b5a2a8b-34ab-4b29-9627-2b1c77dc12a2 · outbound

This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:01.282421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:01.282421Z digest=sha256:99a73af8cb0cb5dafe9a69bf738825cb3ef340d22202611368ce302dda515c89

Observation c8f4875f-189e-4ff4-9fc5-97670d162bd9 · outbound

This paper cites Gemini 2.5 technical report.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Gemini 2.5 technical report

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:15.406544Z

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=2026-08-06T22:05:01.391199Z digest=sha256:b5e0708f8f83da5ac4b39a6a220a3d92eb0f771e08ec8fb4151a0bed10966146

Observation ca555a10-b3cc-4c2f-950e-fa756798ce28 · outbound

This paper cites INT: Instance-Specific Negative Mining for Task-Generic Promptable Segmentation.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning INT: Instance-Specific Negative Mining for Task-Generic Promptable Segmentation

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:01.481274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:01.481274Z digest=sha256:d4c138f852e5c7b568673c3fce6734e07e1ed4132ad95ed3af52b03f821fa991

Observation ffc0aea7-c8f2-40fc-8241-960a9f7bab12 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:15.130210Z

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=2026-08-06T22:05:01.638691Z digest=sha256:773536f2ae644989e6e41c82bc4b6e92bc15dd08a49520328c2aee7ac802d3f8

Observation 93477e1d-e58f-442e-9b7f-7905c27c641d · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:01.737335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:01.737335Z digest=sha256:fb4e4085b728d988cfef3f1ae406603178327ef65e38edee6bc1e3406b00f273

Observation a8f0a385-72e5-4b01-8780-05b4cbe14336 · outbound

This paper cites Huang, H.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Huang, H

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:14.928881Z

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=2026-08-06T22:05:01.886390Z digest=sha256:2dfbdf9bf51b3b50b9e8700fa6030897268f6bb862586e6f52d3d987d467e60c

Observation bbe0f0bd-4261-48fa-8bcb-9510bbbaab0a · outbound

This paper cites Kazemzadeh, V.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Kazemzadeh, V

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:14.674011Z

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=2026-08-06T22:05:02.011710Z digest=sha256:99ad67802446a8ea2212455280ba815d1cbe05f90ed959e818b1eff1ef507077

Observation 813ee955-bbd8-4cef-a268-555e9d26d956 · outbound

This paper cites Kembhavi, M.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Kembhavi, M

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:14.389215Z

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=2026-08-06T22:05:02.134623Z digest=sha256:965fa083aa50d9d84d3ab1444427a8be6e2b9308c3746df77ca9be3a516673f7

Observation 5e71fdc0-4c76-4591-87b2-07caf5e6daf7 · outbound

This paper cites Kirillov, K.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Kirillov, K

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:14.228314Z

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=2026-08-06T22:05:02.268493Z digest=sha256:08bdf3eb31bd10a22bc06c6304cb7b730761c288b3f08076c09ce805db50ad00

Observation d69aabb9-d670-4429-a89a-ed838f84116c · outbound

This paper cites Kirillov, E.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Kirillov, E

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:14.162388Z

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=2026-08-06T22:05:02.410474Z digest=sha256:495d7ef4e722d26371aa069e6fa1edce84e71311afffe4a6726ab9733b69e4e9

Observation a5fa6c03-83ba-4dc7-a1d6-4f8adc587240 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 22

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:14.083484Z

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=2026-08-06T22:05:02.529943Z digest=sha256:4e0c74ca79636121e47030797b660111b820a01da4d9e027e4803c5e31d4e0de

Observation eeb10d2c-24f3-4540-9e38-8f60648ec27c · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:13.977657Z

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=2026-08-06T22:05:02.758778Z digest=sha256:2fabed7fb483d21d0c670543f40e37632f3a4c53e3a6cafcc1c92133ddcbf0b6

Observation 26551b81-b019-4df2-9089-3d5ef598e521 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:13.879159Z

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=2026-08-06T22:05:03.083919Z digest=sha256:084605df334879542a077e6404e0c51f75909892bbb2245e47623cf572de0861

Observation 08a73dea-31f8-4b50-9a5e-0b22ad18ea84 · outbound

This paper cites Li and Y.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Li and Y

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:13.775567Z

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=2026-08-06T22:05:03.238936Z digest=sha256:765ad0351e6e0531725ced8f5a7427a24fceb73a2c6869386ba5237912f6b5f7

Observation bc1d245d-35e5-46af-a574-77e7870aa15a · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:13.709924Z

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=2026-08-06T22:05:03.421647Z digest=sha256:d41bab0f51be2d55d1f2361f1ff09922526d23f1448ff0d252797142030499e9

Observation b52a8d6d-1c93-461a-8105-af22f40a8d2c · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:13.584096Z

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=2026-08-06T22:05:03.628284Z digest=sha256:324520ace1a882108f9c28a53b37601d551d0c6ece691a241686a441c82d1c4c

Observation fb6451c5-b25e-4d00-91a0-582eaf0002cf · outbound

This paper cites Evaluating Object Hallucination in Large Vision-Language Models.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Evaluating Object Hallucination in Large Vision-Language Models

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:03.760109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:03.760109Z digest=sha256:76b2b38b5b297096010f40fc58ae8515b85183b355b6b14099462e3fa4c868da

Observation 5110abff-78f2-4422-8c4c-bdf6d950b630 · outbound

This paper cites Liang, B.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Liang, B

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:13.494461Z

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=2026-08-06T22:05:03.869436Z digest=sha256:7c5d639b14ffcdc9ebe3b17101bd044731ebcf91612c086da49d0f1cd27cfc7f

Observation 366f756d-e613-48ea-b10c-1f54f0ef0577 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:13.412935Z

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=2026-08-06T22:05:03.955853Z digest=sha256:93b66bf10f5672fe1184f851f4db0bfba1cfd2e146af1b50ba5203dc11e5e6bd

Observation 115adc5a-fdac-44ed-bc19-86b36b5282bc · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:13.282809Z

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=2026-08-06T22:05:04.077292Z digest=sha256:ebb15548c19f96dedd3984e4dfa581a4b58bc6e10388fecd620cb437d5d7f901

Observation 0482ccea-967a-4af9-b385-b2ecf81ce0b5 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:13.164315Z

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=2026-08-06T22:05:04.203758Z digest=sha256:ac454c5257b06a7372c34a3f07b1d5dfcda4faaab9e59713e69630ae9e4cfc54

Observation 5a22f3c2-b504-4854-99e5-c28b068e3a94 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 33

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:13.087113Z

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=2026-08-06T22:05:04.359518Z digest=sha256:62308127fb5397145441c940bc2aab006049c2f3815a4fba36679048c00afdbc

Observation 53a0d13b-7810-4167-986a-c36bbfa53bb5 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:12.946800Z

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=2026-08-06T22:05:04.483682Z digest=sha256:8ee2b15112c21e4f8c81c23a7c1bf143cf824d8a2cafb1bc86a21fbc4a6c63c1

Observation 99cd89a7-178e-4e16-907c-4d2dc4543a2a · outbound

This paper cites Explicit Visual Prompting for Universal Foreground Segmentations.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Explicit Visual Prompting for Universal Foreground Segmentations

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:04.571713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:04.571713Z digest=sha256:89228cca18f6abdf68a6a9c51af7d496660e4f9e3f31289f3e6f99f668fc959a

Observation 84c20159-0c7a-48ce-8a47-abe3078e0d65 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:12.833752Z

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=2026-08-06T22:05:04.658492Z digest=sha256:254abf3488aa6e8c0ee3a1f08261163b48e240db9ca758650a0ecac9371d4185

Observation 2951a004-e108-4673-829e-ead5c545cf32 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:12.720399Z

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=2026-08-06T22:05:04.719710Z digest=sha256:c3aa969e883c970a7b94f4080051a76b0b3dbd9dd428c35df42bb9c7b0961690

Observation 86bf326a-10d8-4610-b57b-b1c1deefe17e · outbound

This paper cites Receptive Field Broadening and Boosting for Salient Object Detection.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Receptive Field Broadening and Boosting for Salient Object Detection

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:05:08.331611Z

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=2026-08-06T22:05:04.784458Z digest=sha256:fe95d8b70dea9c8098c3c2112eb9f979aea18a5b18c0616ee338579656e44150

Observation f9a3ae7b-a4ec-466c-93c9-39d5d2c6bdab · outbound

This paper cites Mei, G.-P.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Mei, G.-P

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:12.617898Z

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=2026-08-06T22:05:04.873879Z digest=sha256:6f6a09fc6c37a6572abb20ca389b98d588505ce47af69bba18c4a8a3b750496a

Observation d4410dbf-64db-43a1-92eb-aff789d5857c · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:04.953524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:04.953524Z digest=sha256:39f85763ba95a48bc67303fab29c02d78482d6b59e802561c67295a80b8a50c9

Observation 6b165d70-eecb-4472-a556-8a07c0c34f4a · outbound

This paper cites Gpt-4 technical report, 2023.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Gpt-4 technical report, 2023

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:05.017771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:05.017771Z digest=sha256:eb3fa5f9ff23556cb25240481068c9c2a0e1dd6b7e1972bad558c7fcd1cc40a7

Observation daaff96d-a2cd-4064-997c-9e8d431f174c · outbound

This paper cites Ouyang, J.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Ouyang, J

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:12.416379Z

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=2026-08-06T22:05:05.089116Z digest=sha256:697de26938610be37b6ed1dc5121f63625c4460578b7d3e74b67dae02b15a30e

Observation fd50a310-66ca-4654-8744-4d4efcdf15f3 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:12.209479Z

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=2026-08-06T22:05:05.170630Z digest=sha256:f2e3c4456f46865158914b3d33c2e1b195cf9d7d235af8881c30912c47ecf6b7

Observation cbdfed3e-2b1b-4ebc-9fea-4faba3014afa · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:12.019336Z

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=2026-08-06T22:05:05.251369Z digest=sha256:11266765173c0265217c8b64bcc4e9bb4beb6462667160425e4c68961cf88f6d

Observation f20d9082-b47d-4020-958c-1dbd127e98a0 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:11.849203Z

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=2026-08-06T22:05:05.336674Z digest=sha256:977746411d223f7b5282153f43b8a5a6bad5f7f99efc45f0e76619dffb2414a8

Observation 7fe82e73-d740-4191-b0e9-d96ca5910031 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:05.414038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:05.414038Z digest=sha256:f7c77deeaa9196f0235225679c4f667e28b8611e8ec20889c2fa9d3a8c7d0f8f

Observation 97d5a88b-e647-43a8-a159-383be9b11090 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:11.681487Z

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=2026-08-06T22:05:05.476476Z digest=sha256:e4a8b4c9378af2e08a71e8d7624f11c5db87083efcbafae374c5782855093281

Observation a140b7dd-1963-4afd-8a63-e6abae0865d3 · outbound

This paper cites Rafailov, A.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Rafailov, A

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:11.534871Z

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=2026-08-06T22:05:05.571158Z digest=sha256:08f58233f3d73a2c7fb89256ead2d718815de166806f922c7a487d485e922cba

Observation cb0f6f8f-08a8-4561-a2b4-2c7177dc7968 · outbound

This paper cites Rasheed, M.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Rasheed, M

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:11.380478Z

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=2026-08-06T22:05:05.655711Z digest=sha256:baa56175a2bd7565e76786c25b678142e69e0882fae340afd6d50a1c9985bc3b

Observation ba523420-a15e-4226-8ec2-c17a795003a3 · outbound

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

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning SAM 2: Segment Anything in Images and Videos

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:05.729515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:05.729515Z digest=sha256:9034fd4003f5b839eace6a73e4b5795d12c87cefe5a2bd892370e1b4c40e9eaa

Observation 757f367f-aea5-4bca-b087-08ab4b22b085 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:05.811967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:05.811967Z digest=sha256:b9cf4b819e6f683365df737da74f95a3ac618361d4067ab70c88da6326b2915a

Observation f5e515d4-b762-45d9-beca-ca53fbe46fa0 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:11.206635Z

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=2026-08-06T22:05:05.869882Z digest=sha256:c20efe28e322eb2cfd3f6a98500b00f317226b22b2b0b6111ccd3079f73c0821

Observation 75d5f02e-472e-482e-94e9-c49dc058c9bb · outbound

This paper cites Proximal Policy Optimization Algorithms.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:05.928652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:05.928652Z digest=sha256:4a2c38c43499f580e878f4bc9d8ac46eb799b38ba35a830a84784f25ca2c5971

Observation 9987584d-c8cc-4fc4-9a92-31abc180564b · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:05.995795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:05.995795Z digest=sha256:ae525805c03d477522401c3571bbdfa11ebcb58cc01753392a86270c30effcb7

Observation 71cfac1f-1c5d-4198-8642-2dffaff6a5f3 · outbound

This paper cites VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:06.057656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:06.057656Z digest=sha256:8b2c73caaec1957516bc796efff7bfc039e777ed61ce8c94b7ceea445f737fa0

Observation 4e33c840-69b4-4a27-a03f-360eef4624a2 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:11.033454Z

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=2026-08-06T22:05:06.149291Z digest=sha256:c4551138d284cea834dea061ee59320f245a256e7a1b667e51460897092e58a5

Observation a89573ef-52e4-46ce-9045-43942730105b · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:10.865873Z

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=2026-08-06T22:05:06.219784Z digest=sha256:c8759c8defb6d6249cc16154b8ea9b0d692c6746b32d5d03ad666fb53dd7478c

Observation d891fdbb-e9c4-4340-b99b-eb9b570e4a40 · outbound

This paper cites SimpleAR: Pushing the Frontier of Autoregressive Visual Generation through Pretraining, SFT, and RL.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning SimpleAR: Pushing the Frontier of Autoregressive Visual Generation through Pretraining, SFT, and RL

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:06.287557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:06.287557Z digest=sha256:2be9db22336548550e87dc48670613947c126f99b44fda2896647dda0c621229

Observation 911e1a4c-c050-450c-8372-f63fab161b66 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:10.700537Z

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=2026-08-06T22:05:06.378784Z digest=sha256:e9009c5d17999c6089ceb988154638882c5d296f8b6aedb7f58b936ad242856b

Observation 69d4dc70-1e4f-4c08-8247-8d2abb5dea18 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:06.442646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:06.442646Z digest=sha256:f8506b71426b0c9ce562aaa4c9dd20643e3fcc86bc440648961a1201f1c58591

Observation affeea84-a165-4dfd-b83b-17ee1274a3ce · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 61

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:10.517019Z

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=2026-08-06T22:05:06.508984Z digest=sha256:6f1309b3741e2f1eee8bcbc2b0bc4ffc0ef79a36972a8266bfbc9fd986350081

Observation 7dadbe38-ea8c-431b-917a-0465bdd0b7eb · outbound

This paper cites mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:06.610830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:06.610830Z digest=sha256:a2ddfd056f78f47ea4c50501ecb2806f118076147145d10ca78ca53585f9b168

Observation 9a76b0b9-3ae7-4e61-af67-0e609236fce1 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 63

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:10.344784Z

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=2026-08-06T22:05:06.680117Z digest=sha256:d30dfd1ec648fefc7f58d15e5cbcf31812792ed2a7b1b6d93b480d30ba82b3d0

Observation e2a7cf4f-597b-4b70-bd57-effefa4178b3 · outbound

This paper cites Pix2Cap-COCO: Advancing Visual Comprehension via Pixel-Level Captioning.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Pix2Cap-COCO: Advancing Visual Comprehension via Pixel-Level Captioning

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:06.775331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:06.775331Z digest=sha256:497eecae61f235f2ad403741052df8f010a1e7e7929b6a596c6b87fb0921d8dc

Observation 6d19b9fa-8d57-451f-8152-3513d5016cc2 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 65

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:10.140694Z

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=2026-08-06T22:05:06.886683Z digest=sha256:632bf22b10f05e5d17eb460066fd34d8e7f8074b36a72b2ade60736e957f5cc7

Observation 2648d18b-9793-44e9-b855-1be7c3e09fbb · outbound

This paper cites Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:06.966364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:06.966364Z digest=sha256:06f7cbf0318dadfb6c5cc7aee9e582263b361b689e0a49a21c9e9df9e0f6e5d9

Observation 6987020d-e079-4c73-a11d-a101e48bd1b1 · outbound

This paper cites Unified Unsupervised Salient Object Detection via Knowledge Transfer.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unified Unsupervised Salient Object Detection via Knowledge Transfer

Reference 67

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:05:08.151336Z

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=2026-08-06T22:05:07.046562Z digest=sha256:f2d9beba5fa9e77fbcff3bdc0fdf4ec07eb9ea20c0b2c4ac126ef5eeea29d5ef

Observation 7b0e3e24-1022-4056-9714-2e758a7fc14e · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 68

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:09.946655Z

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=2026-08-06T22:05:07.150521Z digest=sha256:9248c5f9102329d5a593a73bd78a73e4691761d9264e7e19965ae8607a9a51cd

Observation 6692ba8c-894e-4d38-ae51-2a7b4eb52432 · outbound

This paper cites Zhang, P.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Zhang, P

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:09.785897Z

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=2026-08-06T22:05:07.222991Z digest=sha256:b93c67c8f5a350fcc5b8ac5b998766cfd2eec2220e4ade0678a7836892488141

Observation e37a2ab1-3435-43c6-976e-abf8becad9f3 · outbound

This paper cites Zhang, X.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Zhang, X

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:09.545506Z

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=2026-08-06T22:05:07.326673Z digest=sha256:c31c6984731efcad8aaaf93afc86cdb5406d7b9c1ffc6d7d5298aec6c81f033f

Observation 773c2860-b542-4f6e-a3d2-2c71c3acce28 · outbound

This paper cites Pixel-SAIL: Single Transformer For Pixel-Grounded Understanding.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Pixel-SAIL: Single Transformer For Pixel-Grounded Understanding

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:07.431761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:07.431761Z digest=sha256:3087453cbf66356cb112161305c17cff5b2b0b4e3a718165c57982b700735675

Observation 65793925-1609-41ce-8330-d2438413bb99 · outbound

This paper cites Bilateral Reference for High-Resolution Dichotomous Image Segmentation.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Bilateral Reference for High-Resolution Dichotomous Image Segmentation

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:07.517794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:07.517794Z digest=sha256:a23a7da2c35d217002ad90eba96ab0ac5c6060e43651d40daf02952bb1f19845

Observation 46e694a4-02f0-4df3-a4ce-c26c43bdedca · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 73

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:09.345769Z

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=2026-08-06T22:05:07.610056Z digest=sha256:0d15221d549a26f234ef40dfb158184c5711cffbed18c319eb6a75c237a2323e

Observation 74e12274-9a3a-4387-81d5-b27135e47230 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 74

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:09.172584Z

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=2026-08-06T22:05:07.683333Z digest=sha256:295d44edf6cb2aa8f25362906b10d168fc89e208240e543c92b1fae2ee1ea96f

Observation 35cd1f84-a5cd-45bc-b911-4ac214088c78 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 75

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:09.031541Z

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=2026-08-06T22:05:07.729824Z digest=sha256:66c0098b7ae4491d4421724566ca07f3acc5ede03e97c14b6ac568e5a7a5312c

Observation e8d7591d-dd03-49b0-a8da-c10ebb336b30 · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 76

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:08.871347Z

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=2026-08-06T22:05:07.781511Z digest=sha256:30cfc016d3cff62047f044ddab00617fceb93e24c6d79164a4b7b5200cf8ab43

Observation f705fb45-5f53-4ed8-b062-c5dcb7e89b6f · outbound

This paper cites Zou, Z.-Y.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Zou, Z.-Y

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:05:08.712818Z

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=2026-08-06T22:05:07.866821Z digest=sha256:f45469e6091176a3f9091ded02d44f22e568abdf7bde3e808655e81424455119

Observation be68da25-f8c3-49ea-87f1-83e9d37d662f · outbound

This paper cites an unresolved cited work.

Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning Unresolved cited work

Reference 78

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:05:08.528436Z

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=2026-08-06T22:05:07.938967Z digest=sha256:20b33851bc5e5f442e90688a8cad4603262ce69757fd4923f4811b37a0aabc09

Pith citing papers

Observation 6e4c2dfb-a5d4-4c37-9590-aaa7aa4c7f26 · inbound

OneThinker: All-in-one Reasoning Model for Image and Video cites this paper.

OneThinker: All-in-one Reasoning Model for Image and Video Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-17T02:11:26.509628Z

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=2026-05-17T02:09:39.820651Z digest=sha256:50156d493247cfcd286662beeca752744a56f5955b5ab3b43f41484909940643

Observation d009603d-e471-436a-a08f-6cf6bfb19429 · inbound

Grounding Everything in Tokens for Multimodal Large Language Models cites this paper.

Grounding Everything in Tokens for Multimodal Large Language Models Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

Reference 79

Resolution
verified exact
arxiv_id, observed 2026-05-16T23:31:21.858937Z

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=2026-05-16T23:31:05.422935Z digest=sha256:90a156525924b741cb572d25b0d8f203a5c9277e4e0d2663d3867912e810af6c

Observation 42a8e0c2-8d4e-4560-9ce0-109ab909b33f · inbound

CamReasoner: Reinforcing Camera Movement Understanding via Structured Spatial Reasoning cites this paper.

CamReasoner: Reinforcing Camera Movement Understanding via Structured Spatial Reasoning Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-16T10:02:42.546134Z

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=2026-05-16T10:02:20.477517Z digest=sha256:93b17f0199c90728164ad75a3bd38fb234662d5cf3104671f5aaafcba2fc8ca5

Observation 0425aa8a-758b-4fd4-82b6-a490fbb76b0d · inbound

PhySe-RPO: Physics and Semantics Guided Relative Policy Optimization for Diffusion-Based Surgical Smoke Removal cites this paper.

PhySe-RPO: Physics and Semantics Guided Relative Policy Optimization for Diffusion-Based Surgical Smoke Removal Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-15T01:23:26.851591Z

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=2026-05-15T01:22:42.691009Z digest=sha256:1e86ea97a352c643c64d42374f6f265357e986d871408cfa6b2401a93040c6c8

Observation e5c5ffc0-e27b-4d6c-a5ce-f95954fec128 · inbound

From Web to Pixels: Bringing Agentic Search into Visual Perception cites this paper.

From Web to Pixels: Bringing Agentic Search into Visual Perception Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-13T05:52:22.835766Z

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=2026-05-13T05:47:43.959052Z digest=sha256:39d1c7444fdf55af8189146026a552f63a387ebca815012c0d197c4f46dd8c39

Observation 34480fa5-a0d1-4ad1-9c44-7ab8a5547b53 · inbound

EARL: Towards a Unified Analysis-Guided Reinforcement Learning Framework for Egocentric Interaction Reasoning and Pixel Grounding cites this paper.

EARL: Towards a Unified Analysis-Guided Reinforcement Learning Framework for Egocentric Interaction Reasoning and Pixel Grounding Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-06-30T21:35:04.649311Z

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=2026-06-30T21:29:27.063028Z digest=sha256:c5ec0ace30ece607326b3dd951f61234cc14d11dcf8e745b2df0de7ece31d9a8

Observation b122e021-87b4-4e8d-8b21-cf855026b162 · inbound

From Failure to Feedback: Group Revision Unlocks Hard Cases in Object-Level Grounding cites this paper.

From Failure to Feedback: Group Revision Unlocks Hard Cases in Object-Level Grounding Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

Reference 89

Resolution
verified exact
arxiv_id, observed 2026-05-20T18:43:38.872907Z

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=2026-05-20T18:39:11.904941Z digest=sha256:262af1c597883614394175e2ff7f80d07d54acbb158bee9ea8dcff76181d6db9

Observation 0beefd03-c983-4d47-8f8b-3d16e5353938 · inbound

ConceptSeg-R1: Segment Any Concept via Meta-Reinforcement Learning cites this paper.

ConceptSeg-R1: Segment Any Concept via Meta-Reinforcement Learning Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-21T07:19:46.744672Z

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=2026-05-21T07:18:57.039115Z digest=sha256:0b628fe31ea0147c136966eab36d17b9d352b1fd42c2f6362ee84a7446d66faf

Observation 4e218475-fdce-4fb5-9bd6-fd84fcd0ef27 · inbound

Reason Twice: Segmentation via Candidate Discovery and Comparative Reasoning cites this paper.

Reason Twice: Segmentation via Candidate Discovery and Comparative Reasoning Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

Reference 86

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T00:47:30.593795Z

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=2026-06-27T17:01:13.745646Z digest=sha256:9d2b7eedb5f73004b294749df386783575edd1e565aa55ffe9c706edb3fac267

Observation 4b0469fe-4e32-4809-86dc-37bac88be12e · inbound

From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models cites this paper.

From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

Reference 184

Resolution
verified exact
arxiv_id, observed 2026-07-04T15:09:55.143041Z

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=2026-06-26T01:50:54.242508Z digest=sha256:4fdc0441741f76a3accc3d6b8c8b4feb7316a5395ef7e43ad457c8d1ca7ebd56

Observation aeb08340-f578-4a72-811d-37b6b5ead7fa · inbound

InstanceControl: Controllable Complex Image Generation without Instance Labeling cites this paper.

InstanceControl: Controllable Complex Image Generation without Instance Labeling Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

Reference 58

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T10:15:45.115913Z

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=2026-07-01T05:37:41.030752Z digest=sha256:d08fa4563ca390f6826347873b167ae5d290e8c84a0ee7a3b6de9f96c53b932e

Observation fabb9667-b9ff-43d1-96a4-6c21ec988b9b · inbound

DGSeg: Dynamic Gating of Semantic-Spatial Guided Predictions for Reasoning Segmentation cites this paper.

DGSeg: Dynamic Gating of Semantic-Spatial Guided Predictions for Reasoning Segmentation Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

Reference 54

Resolution
unresolved
no resolver link, observed 2026-07-11T13:38:03.546834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T13:38:03.546834Z digest=sha256:082d45c5863074532d4c7a78426bc5655d903a075837a79c07ea0af46d2b9225

Observation 3b4f2d61-e713-411c-b1bc-8bc5382f92cf · inbound

Actor as Its Own Critic: Unifying Region Understanding and Localization via CycleGRPO cites this paper.

Actor as Its Own Critic: Unifying Region Understanding and Localization via CycleGRPO Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

Reference 63

Resolution
unresolved
no resolver link, observed 2026-07-14T04:38:05.237334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T04:38:05.237334Z digest=sha256:e92c3bfef3420a2bbe10a9c0aa14affd93b6ed955d38cfab9652a1d8f9363863

Observation 639507ed-9b7e-4705-962b-49046b2b9c0b · inbound

Reasoning-Guided Part-Level Visual Grounding via Reinforcement Learning cites this paper.

Reasoning-Guided Part-Level Visual Grounding via Reinforcement Learning Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-01T23:38:51.142831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T23:38:51.142831Z digest=sha256:c4d0ea5137f16228f1fbd578ce9b46cf5128d3c5eebe3e927fe1414446f256f6

Observation eb6095bd-e7df-4d00-ba3c-c8db8b8a89fa · inbound

Credit the Right Box: Marginal Contribution Assignment for Structured Visual Perception cites this paper.

Credit the Right Box: Marginal Contribution Assignment for Structured Visual Perception Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-06T00:40:24.622372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:40:24.622372Z digest=sha256:faa7e55fedef6d371ec0b909052f7b0cc706291ead656ac9ee6497f81386c3f6