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Paper Citation Record · LEDGER

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

As of 7 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 2026-08-07T06:34:17.273281+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=sha256:9e13d442b84f83b30fe20e431dc6e013cbe38fa9165d67d912639986247efbab

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=sha256:7a46c4678e2735b27a70e8691bcda8915830b3ab153f81abe1647a53bac44f26

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:adefabcbeea8c5e616eb8ccbe7ac6811d70bc5ae44954cd0fbb3b32c1342b6ff

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:00.606554Z digest=sha256:0708707909cc8efb94f92f68ab9ba8b12d51fc4f010553562682273bd1cc6518

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:00.713549Z digest=sha256:da2d60511e1aa96d0272edefdfac5333732d13e4b50004aa04e4ba580adf6241

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:00.754556Z digest=sha256:681b5eac538f2e84c4fccfffe80b2e2680e36e921468ce96cc8a499c4724d6e5

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:00.859810Z digest=sha256:06494d84d4e09398e86d52bbefc7da39c2fe01f4ed04056f7ea0c6d0bad9d9c0

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:b8251d5e2bc70813c444227f8ae9f0abc0b87f7803b6ea099d10219609ccab20

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:01.017455Z digest=sha256:2100ce7bb6c3881d371442bac14cd2699be458cabc4842eee836e15d36f74479

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=sha256:589d03deb2b128f882699d9dd75db6f6f534c8eb6b9c1b6f9c8aca5a42402415

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:01.182278Z digest=sha256:3fa2bf170c24dea537479a9849955f844a1230fe62043802cfcb008183ecb612

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:c4105f6254df96d7e4d1dbf7948cb80a15a3f8fa45007c7fc0ce21232d3a15dd

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:01.391199Z digest=sha256:617d654d6cb912d5febdb67dd519eed450eeb40a6c49e01c3b851b3dbcecb919

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:fce6df2da137d6951e9becd506d79456981da8e51565c8ddebd1a7ecc062eea2

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:01.638691Z digest=sha256:fd79c0471064dfce33bba323e9dd105e17c2fb06839af7c7bf2e85c4cd543c8c

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:ab90221e05c2b2d9cd8f57363226218ffbb6642ea1e9c5f53bbcab7f1e618d37

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:01.886390Z digest=sha256:0fc3407c7a331c7b92e9376b6378aaf051fe67932ed466134e78f7e458d5d83e

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:02.011710Z digest=sha256:e25d1a2e8f4d87e7c39f127a895744b7c31bb9c32f7b486184a4f11c406ba7fe

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:02.134623Z digest=sha256:516793ca5541ca5a000e552068df5d2c56eb04aad0f07128919d5ef8c3723748

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:02.268493Z digest=sha256:6e34d9b8a5a06f879b14289df016db131a380ef00cb46fca9778bcff8ccbcd2b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:02.410474Z digest=sha256:a123d450f8f7de8c25dd7c7cf11606fd4b188cdb402c9e6b2176a2cc6177c7c5

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:02.529943Z digest=sha256:34c5e211a39c8e528fdcf799efd9ed9ae952e7a6a0699dca02d4ffad6534319f

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:02.758778Z digest=sha256:09d6a6c15f3b2e85cd8afdb952922c3003990d31443b7ee10f0e464132c47d99

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:03.083919Z digest=sha256:5f9df1029ef52646a74c1dbbac14cc62b31b2fbc248f392ec3ad90e58959c5be

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:03.238936Z digest=sha256:a01e632d41cf6b37cada74eb409112a885f5bb9b9d900f7d29ca7f3d0de02a09

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:03.421647Z digest=sha256:13666076f33e68bfef677ae2c1bb8fad2fffd33edf9bd15b2ddba01fd2f798a0

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:03.628284Z digest=sha256:8af761a73f93764215ad4d6dc0b62edfe7baec3fa70691df111b34e17902fc40

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=sha256:5357d035502b7847fc5e7abc9af931b4f36b767ea3d317d9e55da7f1ca90939f

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:03.869436Z digest=sha256:de05663ac2556df47a6f9f5158b126b037ae29b3d1cb69894e88c3a38c813e57

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:03.955853Z digest=sha256:663d04ffb665fe94e8fc23522251e1bf221e22d6764d0df2fab2dadba4ffc66c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:04.077292Z digest=sha256:d66d90ee42a823f43c3f6a4bc4e16c387d72d7764357a221457f84dd79084588

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:04.203758Z digest=sha256:a887314d1eebdd6a4e5269c12ffe9a200441b1f7fb867faed885c376cadcf74b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:04.359518Z digest=sha256:83241dcc2f7c7caa11f3fbf45a55e45c987f830f38a9e51aa022833b629d4bfa

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:04.483682Z digest=sha256:d379820878104a743e0240732fdb3f1f7f08a49891a01d0a11587a2716f72d5a

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=sha256:194947e490ca95fbd2b744dcac671f1234c0f92dc1cfd31cb7ed1813808f9010

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:04.658492Z digest=sha256:d0a06d2ebf0005c8a477b1ca89e3a12157617b928cbc4293f13568eb506575ad

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:04.719710Z digest=sha256:a560eae1ce7733280e5605b5decc8745c59cc400923eec77ca268908e39ea1c0

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:04.784458Z digest=sha256:c3ed1004bace21a812ff6997edcef8dcfd2433af5f6c277fdaae7d1299bd8447

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:04.873879Z digest=sha256:e6298afe7eaca7deb3856187e28f2dd8d29fda9da2034590d4047fc2c94cbe44

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=sha256:62a3ade270dd6591cf9c9e1626b6a8cf0e93d69cf47284887bc02ff65f2c13e3

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:ffbe1afa2bd4353cfa773e40fe7b3fa79414c2ce4a5698c48bbc4e4b2e23fcad

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:05.089116Z digest=sha256:34c586ce17d8b3874a00ada43c0f6a5d65c1545f577417fcd596b487e7bba253

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:05.170630Z digest=sha256:4894147fb924a40937205cb0ef0ff90e74498719d508bfe1660eeae5b4578669

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:05.251369Z digest=sha256:ddc84b61e597399cea6190e4262971cf4f47055e19e75687e472328c80856296

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:05.336674Z digest=sha256:fb2d3d94e06c3e2a277df661064ecb2d21c3cd0f982eabdd066c03cb2d3e0095

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=sha256:2c742ad9216a7e9bbb5535f0c967f4f6e0d6e1ee366deeda3d0fec51921218fb

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:05.476476Z digest=sha256:25bd7ab9596777c1275c6f29052046e57a1ef0889a797c6815ae33edc157460f

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:05.571158Z digest=sha256:14ea08cbbafc906a96706f7a8be0aa697f780afe6580aa59ac9bac2c671fc15b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:05.655711Z digest=sha256:f667d86c7a87e6bf8ffdf1751135167365eacd7e1b77f2926e95e3d0f1761c98

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=sha256:51b3d4ba72aefca6f44ddeb856aacceac39cf8b267e98581cdad7804dce467a2

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=sha256:358822a5766bb69254d3b8b23c9c989ba22e35f81b4c8cc190f02a160339396c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:05.869882Z digest=sha256:9bf78f96c2545a673bad6e0ed90f8a4827b1735bc79aa45ccbc04275e796fa1d

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=sha256:73749444043d9bd61ed3350d0519f4032060303362405e87d44dd13528413b13

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=sha256:8034bee31dce92bdfc5b6655872298a3f5eacc8d1ce624a24b0ed6ded68f948c

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:f5acafa7250af752eb581704fc3a293ae2776e3f43a499d1a2c1b79b6008f2bd

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:06.149291Z digest=sha256:cade11261b9fe817b8d63ac0bafd15d16e47ce9b0b0eb6f56d97224195a4cd90

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:06.219784Z digest=sha256:80ad88e2050174c6c39a313c1c92c2f11ca73566018e825fec1d006f87293626

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:d617076a9ac9a8a65a6cc58c80a991707af6cfd0fad0a1c2384e0f46fc7cc633

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:06.378784Z digest=sha256:09ccf9e4f6ae8c0c433bc712af10199a16e8afe40241d317821c79a59605fb00

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=sha256:8b22811f46ea80f40fd173700c73579b153d4ae8d96fe620dc473affb7860a49

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:06.508984Z digest=sha256:41ae6df2c70fabb39889f0756680c62ac85e63b5ec18a6896fd52d39b467d9b8

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=sha256:782df4d0b520b1d0c678d057c6f10b7f4603d0fdf439ca41e71cb96728de0e25

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:06.680117Z digest=sha256:17afa0a14f77ef7d2a478b8e978ccb96cfc2714916dfb8267d89b687efa9fd2f

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:ce329ff2c62f0860c5a2c4a6829f6ffb9ec4a6b3298ebd244ebdea303c66c63b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:06.886683Z digest=sha256:edd548b0a174bd03a5c9a0dc30e99f3e61437221f7b71d8e1351045fa7d1237f

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=sha256:84678056cbe332a0b7243cdb6077398a6f5fe62d39a624304f35d40c3f52ccd9

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:07.046562Z digest=sha256:b2fe364136e820a2e3aa9de106eb04c686774fcfbb95935c20f95c33c6dc433b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:07.150521Z digest=sha256:c0ee4f3e5d126f45652efdf6194c97ebe1b1343224b4e5a01466e87270312b25

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:07.222991Z digest=sha256:109b4908bd327cfeaa576d38dc1ef60ed8f861550f0e44142b0e2d27f6b755a8

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:07.326673Z digest=sha256:b4ef90e1079ec6b57b082eda9703b786051cecbc2b22b92d483bbaf701fc7718

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:eb58d81892f4710a9bcf6a39e4d44b9f0413cbdf26be12f3680a350dbf250971

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=sha256:3538edde5b3919a2f0d3edbe896e9e696d6d665b89a37430f1c09953e25e2234

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:07.610056Z digest=sha256:0bf99a716d7eeb1795b7f28e9f843a74d20a3a4cead45bf50d7cff31b927b59c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:07.683333Z digest=sha256:893e4da596049855998ecd089236aa533d8a58212fd6f8303613d6d50d0c3707

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:07.729824Z digest=sha256:a3f1e4cd90e06ec157045039acb20752fe92238e248a51f6cd7423c4e08cf533

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:07.781511Z digest=sha256:98e59966b2ec1a165bd7e91a205cad4e3aa63cbae750b454d1fdc04ad43a87ef

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:07.866821Z digest=sha256:aefaf48bb10cd005ae571b31d2b1fbbf8f57bbc8aa42c150d7fa8f5e18264aae

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:05:07.938967Z digest=sha256:60294a55335e08a37ffc82978a20476b0687e57a72f92fae7bb7364e6843696b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-17T02:09:39.820651Z digest=sha256:a971154ae76c232ea84fc251a340626f5d457c1df8a273ef6e5a44c0b573d4d9

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-16T23:31:05.422935Z digest=sha256:67f70eb4f378839b171e7529903b03e249bb8b03133c90d272dbebb10dc6c200

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-16T10:02:20.477517Z digest=sha256:20fa1f232486ed8bb96e7588f82d223308ca896eb9be441152c3d8437a6ac7dd

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T01:22:42.691009Z digest=sha256:c885e88ec741327b9ae239627f405610198b08b98adfda44ac1ddb5640c4168d

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-13T05:47:43.959052Z digest=sha256:1b45871aba0ee8043e2cbd544706e44c7e8a7fa061b27fe37e5ba82ff7ccb897

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T21:29:27.063028Z digest=sha256:aba22a13866105f8fa336654bcadd75103580e029a4c8a976a1e0aa815ff6b41

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-20T18:39:11.904941Z digest=sha256:bb424b256a5d25641631be82104ee940cb5f8ed34c5641a875c820abb63cfa24

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T07:18:57.039115Z digest=sha256:7f37317b65549a7436fa6507fbbee12789a61444edf4549476aa8662d9501f64

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T17:01:13.745646Z digest=sha256:cb5d58bf23fd3f56adfe24822412f726853e3a82d7fbcf8d376e9adc8ea641ed

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T01:50:54.242508Z digest=sha256:f93285dce5a3ed51ee2885bf762aeed4de53f7b68bcbc7c178e4cd34908c0132

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-01T05:37:41.030752Z digest=sha256:bda86acb40bef4d2280f71707b0b599aaa58ad89d1b30759f9df318d2b2bba52

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=sha256:2b7a2d164ce26be100520ddf9ece66e552b7f1e9e4948e23d2af92abeb481eae

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:de0ada1283331ea071f8f6a9886c8cc73f4ade954651be34aa60957c8467168f

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=sha256:0154fcad70a3fc98eedb01724207787c4e7c918fd23efba5e21396c9ad6b4d7c

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:c4b75acf09850f1732f427973124e7a45fb0794b3436bea0f0d24105e6f1a518