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Paper Citation Record · LEDGER

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation

As of 14 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2606.09871.

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

pith.paper-citation-record.v1
2606.09871 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T10:32:39.790036Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

  • verified exact15
  • verified fuzzy0
  • unresolved23
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2f6f8420-c1b8-4f85-a7e9-5f457d104e0b · outbound

This paper cites Qwen3-VL Technical Report.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Qwen3-VL Technical Report

Reference 1

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local_arxiv, observed 2026-07-02T02:56:28.798021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 64092096-0849-4d05-94d5-52bdee043be7 · outbound

This paper cites METEOR: An automatic metric for MT evaluation with improved correlation with human judgments.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation METEOR: An automatic metric for MT evaluation with improved correlation with human judgments

Reference 2

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:b7de9da00f25141cb368fd0502ad6f9ba7c3df5956cc87015de1748113ecba74

Observation c191b8d7-0163-49e2-b822-820f041e25d3 · outbound

This paper cites SciBERT: A pretrained language model for scientific text.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation SciBERT: A pretrained language model for scientific text

Reference 3

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:e330ca1ff639917af289f2b64743af90b824172dcfe95e3a8ba4ac51e5c197e7

Observation 40c08b2d-178d-45e6-a8aa-ad59b71d752d · outbound

This paper cites R1-v: Reinforcing super generalization ability in vision-language models with less than $3.https://github.com/Deep-Agent/R1-V, 2025.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation R1-v: Reinforcing super generalization ability in vision-language models with less than $3.https://github.com/Deep-Agent/R1-V, 2025

Reference 4

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:91fea68379bb55c6eae251f3dbce15d364e0577e618e21d8f73fc6798452bfb4

Observation ce423fa1-35ef-4723-92ce-bcba801cbb08 · outbound

This paper cites Self-Guided Process Reward Optimization with Redefined Step-wise Advantage for Process Reinforcement Learning.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Self-Guided Process Reward Optimization with Redefined Step-wise Advantage for Process Reinforcement Learning

Reference 5

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arxiv_id, observed 2026-07-27T01:21:11.025340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:d4d739f9155d127e769df8e7e1d01b4ccf79c02263ceed6ea591fb93344ff434

Observation 98bce25d-fee3-4eda-90f6-ecbe8035b3f4 · outbound

This paper cites Group-in-group policy optimization for LLM agent training.Advances in Neural Information Processing Systems, 2025.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Group-in-group policy optimization for LLM agent training.Advances in Neural Information Processing Systems, 2025

Reference 6

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:a2ee3b28534216f253f69cb4cc26baa0411f450daaf5b6bd9d1ba67a847ad08c

Observation 424cdf34-d1c4-4ff5-9f94-17f9d5cabc21 · outbound

This paper cites Segmental advantage estimation: Enhancing ppo for long-context llm training.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Segmental advantage estimation: Enhancing ppo for long-context llm training

Reference 7

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arxiv_id, observed 2026-07-02T02:56:28.794467Z

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:2c13d0b94d8e4a1178959bd3005c459526024629cddd454adb41c3fd5749292e

Observation 50c012bb-1347-45b0-b2ed-d5ea318cb45f · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 8

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local_arxiv, observed 2026-07-02T02:56:28.826738Z

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:892cf3ac40a0ef2e9e1e35f1506ea582e2dd50fbd73fad5c5be3381d83254ebd

Observation 44154644-ebe2-41c1-8ac2-6c750a04e900 · outbound

This paper cites Segment policy optimization: Effective segment- level credit assignment in RL for large language models.Advances in Neural Information Processing Systems, 2025.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Segment policy optimization: Effective segment- level credit assignment in RL for large language models.Advances in Neural Information Processing Systems, 2025

Reference 9

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:c129dd45b287e16508952687a449a321e4eec63d94ee6c5150e91b72ced45c33

Observation 5b40e274-386d-4e79-96c9-3b65441facd5 · outbound

This paper cites mTORC2 signalling regulates M2 macrophage differentiation in response to helminth infection and adaptive thermogenesis.Nature communications, 8(1):14208, 2017.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation mTORC2 signalling regulates M2 macrophage differentiation in response to helminth infection and adaptive thermogenesis.Nature communications, 8(1):14208, 2017

Reference 10

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:c83e5b241035507cd1cdc457f346ffaf2617038f93c39ba5982d44a1e5780e56

Observation 1febbb65-4ea4-4570-adc0-03fe00401683 · outbound

This paper cites SciCap: Generating captions for scientific figures.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation SciCap: Generating captions for scientific figures

Reference 11

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:d3aa6fbc0c5258fd16caa349f5ffe54650b55e5f108f08766c67d07b9dcf8bf5

Observation 272a04cd-f221-4461-acf3-76e5c0292e71 · outbound

This paper cites Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Reference 12

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local_arxiv, observed 2026-07-02T02:56:28.814795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:ffa2ea1ebee991d662c43c1bed3cbc0842a61aec65af6ac835db4a2d39d60b0f

Observation 9523071e-95d9-4c3e-bf8f-2a202d8c51c4 · outbound

This paper cites GPT-4o System Card.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation GPT-4o System Card

Reference 13

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local_arxiv, observed 2026-07-02T02:56:28.809123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:3d75f3cec79de5205719373aedd9f1d03a7114fea92457dd5a87885525417bf7

Observation cd5c1bdd-c898-43dd-9639-55b508bea31f · outbound

This paper cites Mimic-cxr, a de-identified publicly available database of chest radiographs with free-text reports.Scientific data, 6(1):317, 2019.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Mimic-cxr, a de-identified publicly available database of chest radiographs with free-text reports.Scientific data, 6(1):317, 2019

Reference 14

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:ee1032201b5e3a21e62de38bd254232d5aa74ebe920de9dbb5669f244ed62cfe

Observation fd83b978-2273-4778-8f51-6cad4c030acb · outbound

This paper cites Vrsbench: A versatile vision-language benchmark dataset for remote sensing image understanding.Advances in Neural Information Processing Systems, 37:3229– 3242, 2024.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Vrsbench: A versatile vision-language benchmark dataset for remote sensing image understanding.Advances in Neural Information Processing Systems, 37:3229– 3242, 2024

Reference 15

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:f79527d7cadaa64ba3eb6bd386906e5f4918983d3ac6c97384b22586eb2cdf71

Observation 1ea6e62e-83bb-4ad5-a82f-79c5854e6327 · outbound

This paper cites Hybrid retrieval-generation reinforced agent for medical image report generation.Advances in neural information processing systems, 31, 2018.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Hybrid retrieval-generation reinforced agent for medical image report generation.Advances in neural information processing systems, 31, 2018

Reference 16

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:bc639beab8e69516deed5edaf8e63ace1525b22c87b0c01d5f2ea744eebea9d2

Observation f580ae4d-a537-42ed-94cb-ee6e016c79c2 · outbound

This paper cites MMSci: A Dataset for Graduate-Level Multi-Discipline Multimodal Scientific Understanding.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation MMSci: A Dataset for Graduate-Level Multi-Discipline Multimodal Scientific Understanding

Reference 17

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arxiv_id, observed 2026-07-02T02:56:28.805174Z

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:2bd5ebcc7088c215b544e7a3572e3e86057e67b30a2dbb5983a46306e3000ec2

Observation 66070811-0be9-40a5-9c68-3fb2ad5f9af5 · outbound

This paper cites Photolatently modulable hydrogels using unilamellar titania nanosheets as photocatalytic crosslinkers.Nature Communications, 4 (1):2029, 2013.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Photolatently modulable hydrogels using unilamellar titania nanosheets as photocatalytic crosslinkers.Nature Communications, 4 (1):2029, 2013

Reference 18

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:4920f5f273d36725452fc58de6e43411569af9fc9357820e41253c12fa720a61

Observation 8e9a8d43-ddfa-49f3-9cce-be5421a2b16a · outbound

This paper cites Improved image captioning via policy gradient optimization of spider.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Improved image captioning via policy gradient optimization of spider

Reference 19

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:7dc86c2e08c5bc5f2bcf19de9e03e33112b26c5b5cc541404a49cca5a39a7363

Observation 15a827ee-9d62-4169-8db1-25b795a265d6 · outbound

This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Understanding R1-Zero-Like Training: A Critical Perspective

Reference 20

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local_arxiv, observed 2026-07-02T02:56:28.823260Z

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:fc4d3e306866815fc225a5c796c161092d020f1e160a3a5716c3e65e3ae14a8e

Observation 13b1bb5b-58d1-472f-be2f-03b125245104 · outbound

This paper cites Decoupled Weight Decay Regularization.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Decoupled Weight Decay Regularization

Reference 21

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local_arxiv, observed 2026-07-02T02:56:28.818694Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:054c3835c35c691dd90c18f69af85551aa1ca12f82f4a5fc21416b2a11474890

Observation 20eb58a8-e4a8-483a-b1bf-098f5844d14d · outbound

This paper cites DOCCI: Descriptions of Connected and Contrasting Images.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation DOCCI: Descriptions of Connected and Contrasting Images

Reference 22

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:a045c4b20d7e39b634bad752599b7cbfeff542c84d172eef5817e80feaf5d7b5

Observation 2bd9c1b6-a60c-425a-8964-2de01429f16b · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Bleu: a method for automatic evaluation of machine translation

Reference 23

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:ab20f9d1afa6b4a0d4e9f0a8a89f181a95b28776b2ca79a1ee2f6142b9a3ce01

Observation 2b5ad5c6-cdca-41db-931f-a65896672aa3 · outbound

This paper cites Blockwise advantage estimation for multi-objective rl with verifiable rewards.arXiv preprint arXiv:2602.10231, 2026.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Blockwise advantage estimation for multi-objective rl with verifiable rewards.arXiv preprint arXiv:2602.10231, 2026

Reference 24

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arxiv_id, observed 2026-07-02T02:56:28.820028Z

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:6e5f8d1a92a9325cc2d41280aaf9c826d5cd7a68c110fa21613dea7ddde4722a

Observation 8368d3aa-781d-4dc5-a227-81fdbe174a8d · outbound

This paper cites LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL

Reference 25

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local_arxiv, observed 2026-07-02T02:56:28.830302Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:4dccc92c5e1d2de268758ce8bbc38237aae0b865b43a587b25832ab87c7b4416

Observation 8e742842-48a1-49d1-8d78-c5f46e5dbeb4 · outbound

This paper cites Self-critical sequence training for image captioning.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Self-critical sequence training for image captioning

Reference 26

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:f40930ccea6aad8a5d7749765a9c315a49dec5469edb7159a72c09dd4ed57cb8

Observation 7be6383e-d37f-49bc-b4d2-3a8123baa1f4 · outbound

This paper cites Proximal Policy Optimization Algorithms.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Proximal Policy Optimization Algorithms

Reference 27

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local_arxiv, observed 2026-07-02T02:56:28.812511Z

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:dfd67a8b05c759897053ecbbb06dc16f3c4bf5b6d3cefd3a8230401c6c058b34

Observation ddee583b-3a7e-42c6-ae23-46d22750a1ed · outbound

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

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 28

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local_arxiv, observed 2026-07-02T02:56:28.833633Z

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:8d65e44817a9c0ff816ca743729d130b143f6523fd1482c4c7ebc91d34c15e21

Observation b28a1d9e-d121-4590-ad96-fd3e4694fdd5 · outbound

This paper cites A picture is worth more than 77 text tokens: Evaluating clip-style models on dense captions.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation A picture is worth more than 77 text tokens: Evaluating clip-style models on dense captions

Reference 29

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:5c5e6cbf4ed89eba3ddfdc3688c344460ecde5a18f145cc954ae55c08f0c1f66

Observation 93f6d554-9ef5-4931-9acf-18069346d222 · outbound

This paper cites Cider: Consensus-based image description evaluation.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Cider: Consensus-based image description evaluation

Reference 30

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:15eba71e7949f6dcf06f7d0cd167818d93715e704812769fd3b358d2cb649797

Observation 766777f8-a70b-4d70-93eb-5990e0475588 · outbound

This paper cites Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Reference 31

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local_arxiv, observed 2026-07-02T02:56:28.787289Z

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:cfdafcb44deb14fa17ca8539ff6eee618f01c5e51699b54f9bc0642515385043

Observation 189c3fc9-a4ca-46df-83fe-5a5b5eeb7fed · outbound

This paper cites Bartscore: Evaluating generated text as text generation.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Bartscore: Evaluating generated text as text generation

Reference 32

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:38cf0b26540ad5784d1f8e5c7ec6824621d9487d82979a17859e9150a3b3ba67

Observation 323d30ed-ae4d-4ad1-9fb4-f38185be8dc7 · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation BERTScore: Evaluating Text Generation with BERT

Reference 33

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local_arxiv, observed 2026-07-02T02:56:28.837017Z

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source=pdf_text observed=2026-06-28T10:32:39.790036Z digest=sha256:2f0181b9e6fbffd59740e68634a9017a1ec90c8ba61840da71645837b976b0b9

Observation 6468ba4c-c22d-4b2a-bfc4-badc8c8345ff · outbound

This paper cites Describe each panel.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Describe each panel

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ae8bed49-fc06-4c55-8f65-5d1cbb944ef3 · outbound

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SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Unresolved cited work

Reference 35

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e2951d76-3560-4755-81b3-f6e7f7b98549 · outbound

This paper cites an unresolved cited work.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Unresolved cited work

Reference 36

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation accuracy

Reference 37

Resolution
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Source-reported events for the cited work

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Observation 73a0a4cf-11e3-4da0-a4e1-81927d81cd7f · outbound

This paper cites an unresolved cited work.

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Unresolved cited work

Reference 38

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation Unresolved cited work

Reference 39

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a76fb032-bd2e-4fde-8b05-045bd73ca8ec · outbound

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Reference 40

Resolution
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arxiv_id, observed 2026-07-02T02:56:28.797729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Pith citing papers

No inbound Pith citation observations are available.