Paper Citation Record · LEDGER

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

As of 19 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 2026-08-19T06:32:44.657259+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.

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.

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.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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.

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 2026-08-19T06:32:44.657259+00:00.

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.

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 2026-08-19T06:32:44.657259+00:00.

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.

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 2026-08-19T06:32:44.657259+00:00.

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.

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 2026-08-19T06:32:44.657259+00:00.

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.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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.

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.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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.

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.

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 2026-08-19T06:32:44.657259+00:00.

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.

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.

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.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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.

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 2026-08-19T06:32:44.657259+00:00.

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.

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 2026-08-19T06:32:44.657259+00:00.

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.

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 2026-08-19T06:32:44.657259+00:00.

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.

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 2026-08-19T06:32:44.657259+00:00.

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.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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.

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.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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.

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.

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.

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.