Paper Citation Record · LEDGER

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning

As of 11 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 2 inbound Pith citation observations for arXiv:2508.06125.

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

pith.paper-citation-record.v1
2508.06125 v1

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:58:40.901060Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T13:13:57.599970Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T05:47:41.745200Z

Reference resolution

63 of 63 outbound references displayed

verified exact2
verified fuzzy27
unresolved33
parse uncertain0
malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5e3188e3-386c-4c21-9782-4ab79c49b35a · outbound

This paper cites GPT-4 Technical Report.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning GPT-4 Technical Report

Reference 1

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Observation 9f187492-904b-4d1b-ae95-48249658e748 · outbound

This paper cites Meteor: An automatic metric for mt evaluation with improved correlation with hu- man judgments.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Meteor: An automatic metric for mt evaluation with improved correlation with hu- man judgments

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:58:48.647640Z

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Observation 81029bf8-c384-4591-b8db-6149b0d2cb01 · outbound

This paper cites ShareGPT4V: Improving Large Multi-Modal Models with Better Captions.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning ShareGPT4V: Improving Large Multi-Modal Models with Better Captions

Reference 3

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Observation da60b3e5-d993-46ec-b9e0-2c35daee4b04 · outbound

This paper cites Microsoft COCO Captions: Data Collection and Evaluation Server.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Microsoft COCO Captions: Data Collection and Evaluation Server

Reference 4

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Observation 54adc342-0533-4de7-98ec-c65214ca9fa3 · outbound

This paper cites How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites

Reference 5

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Observation 91375458-db5f-4dd4-b3d5-57eaf63c1781 · outbound

This paper cites Meshed-memory transformer for image cap- tioning.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Meshed-memory transformer for image cap- tioning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T22:58:33.847904Z

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Observation 7bd57807-a7c1-4248-af0a-f4f95a150ad8 · outbound

This paper cites Cross-domain image captioning with dis- criminative finetuning.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Cross-domain image captioning with dis- criminative finetuning

Reference 7

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Observation f4df095d-74b4-4c46-ba70-32982931c397 · outbound

This paper cites Benchmarking and Improving Detail Image Caption.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Benchmarking and Improving Detail Image Caption

Reference 8

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Observation 20e663f2-2d1a-4896-be48-dd4eba14e8d2 · outbound

This paper cites VILA$^2$: VILA Augmented VILA.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning VILA$^2$: VILA Augmented VILA

Reference 9

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Observation 3bb6d37e-5fe3-4eee-ba19-fa80475479ff · outbound

This paper cites The Capacity for Moral Self-Correction in Large Language Models.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning The Capacity for Moral Self-Correction in Large Language Models

Reference 10

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Observation 63882c2d-434b-4b7d-ae1f-80fc475e7235 · outbound

This paper cites GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements

Reference 11

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Observation 2540fa4c-3e07-4c8f-815c-a1408909e327 · outbound

This paper cites Self-Correction is More than Refinement: A Learning Framework for Visual and Language Reasoning Tasks.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Self-Correction is More than Refinement: A Learning Framework for Visual and Language Reasoning Tasks

Reference 12

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Observation 06beefce-f4e2-438e-98c5-055501d80fba · outbound

This paper cites A topic-level self-correctional ap- proach to mitigate hallucinations in mllms.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning A topic-level self-correctional ap- proach to mitigate hallucinations in mllms

Reference 13

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Observation b91d7e3c-1ff0-4f04-993b-0eb487e04923 · outbound

This paper cites CLIPScore: A Reference-free Evaluation Metric for Image Captioning.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Reference 14

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Observation d374d9dd-bcc8-483e-b97a-32676950de1c · outbound

This paper cites Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions

Reference 15

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Observation 37921116-0a10-4ca5-ab78-f61a39f1545b · outbound

This paper cites Lora: Low-rank adaptation of large language models.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Lora: Low-rank adaptation of large language models

Reference 16

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Observation 00203f23-2d0f-4019-9c19-e14d37591905 · outbound

This paper cites Large Language Models Cannot Self-Correct Reasoning Yet.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Large Language Models Cannot Self-Correct Reasoning Yet

Reference 17

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Observation 3a743dbd-9b49-4019-a201-28a5b9079e57 · outbound

This paper cites Attention on attention for image captioning.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Attention on attention for image captioning

Reference 18

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Observation ea6d09f7-4d09-4c89-865f-0c382b07344a · outbound

This paper cites When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs

Reference 19

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Observation 4685203a-1490-4f17-bcf3-cebe0123f324 · outbound

This paper cites Training Language Models to Self-Correct via Reinforcement Learning.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Training Language Models to Self-Correct via Reinforcement Learning

Reference 20

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Observation c4a0e725-8dca-46cc-a87e-50b4e00b0c9c · outbound

This paper cites QACE: Asking Questions to Evaluate an Image Caption.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning QACE: Asking Questions to Evaluate an Image Caption

Reference 21

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Observation 799cc422-8eb3-49af-a754-0a55aa35e79b · outbound

This paper cites Fleur: An explainable reference-free evaluation metric for image cap- tioning using a large multimodal model.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Fleur: An explainable reference-free evaluation metric for image cap- tioning using a large multimodal model

Reference 22

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Observation 0a8e2c5b-f20b-4ba8-bc43-6cd5433ca931 · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation

Reference 23

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 24

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Observation 243f5353-fe70-4540-9a9e-2fe480bc6f85 · outbound

This paper cites FACTUAL: A Benchmark for Faithful and Consistent Textual Scene Graph Parsing.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning FACTUAL: A Benchmark for Faithful and Consistent Textual Scene Graph Parsing

Reference 25

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Observation 75eef57d-30b7-43ab-9547-73adf55f69ef · outbound

This paper cites Mon- key: Image resolution and text label are important things for large multi-modal models.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Mon- key: Image resolution and text label are important things for large multi-modal models

Reference 26

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Observation 2799051a-0be3-4f43-b590-fc8bc919b5c3 · outbound

This paper cites Playground v3: Improving Text-to-Image Alignment with Deep-Fusion Large Language Models.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Playground v3: Improving Text-to-Image Alignment with Deep-Fusion Large Language Models

Reference 27

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Attention correctness in neural image captioning

Reference 28

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Observation 505f2ecf-d03b-4ad9-9120-e598a5047645 · outbound

This paper cites Improved baselines with visual instruction tuning.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Improved baselines with visual instruction tuning

Reference 29

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Observation 37e799a1-e9e0-4b04-881d-a42c76960982 · outbound

This paper cites Improved image captioning via policy gra- dient optimization of spider.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Improved image captioning via policy gra- dient optimization of spider

Reference 30

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This paper cites OmniCaptioner: One Captioner to Rule Them All.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning OmniCaptioner: One Captioner to Rule Them All

Reference 31

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Self-refine: It- erative refinement with self-feedback

Reference 32

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning DOCCI: Descriptions of Connected and Contrasting Images

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Automat- ically correcting large language models: Surveying the land- scape of diverse automated correction strategies

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Bleu: a method for automatic evaluation of machine translation

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Connecting vision and lan- guage with localized narratives

Reference 36

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Observation 91ebfb98-f1e2-4576-9d57-331776b8c3f2 · outbound

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Is moral self-correction an innate capability of large language models? a mechanistic analysis to self-correction

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Recursive Introspection: Teaching Language Model Agents How to Self-Improve

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Learning transferable visual models from natural language supervi- sion

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Direct preference optimization: Your language model is secretly a reward model

Reference 40

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Direct preference optimization: Your language model is secretly a reward model

Reference 41

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Glamm: Pixel grounding large multimodal model

Reference 42

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Positive-augmented contrastive learning for image and video captioning evaluation

Reference 43

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Bridge: Bridging gaps in image captioning evalua- tion with stronger visual cues

Reference 44

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This paper cites InternAgent: When Agent Becomes the Scientist -- Building Closed-Loop System from Hypothesis to Verification.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning InternAgent: When Agent Becomes the Scientist -- Building Closed-Loop System from Hypothesis to Verification

Reference 45

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning A picture is worth more than 77 text tokens: Evaluating clip-style models on dense captions

Reference 46

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Cider: Consensus-based image description evalua- tion

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:58:44.398320Z

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This paper cites Show and tell: A neural image caption gen- erator.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Show and tell: A neural image caption gen- erator

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:58:44.133064Z

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This paper cites GIT: A Generative Image-to-text Transformer for Vision and Language.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning GIT: A Generative Image-to-text Transformer for Vision and Language

Reference 49

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 50

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This paper cites Caption Anything: Interactive Image Description with Diverse Multimodal Controls.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Caption Anything: Interactive Image Description with Diverse Multimodal Controls

Reference 51

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Observation 2a05045c-dd8d-48e8-8b85-dbd2e8d22b01 · outbound

This paper cites CogVLM: Visual Expert for Pretrained Language Models.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning CogVLM: Visual Expert for Pretrained Language Models

Reference 52

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Observation a0a86057-9ea6-4940-a317-98ab80e2f66f · outbound

This paper cites Generating Sequences by Learning to Self-Correct.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Generating Sequences by Learning to Self-Correct

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-05T22:58:39.580049Z

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Observation 5ce173ae-a26d-4bbe-821d-8178f49ad673 · outbound

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Painting with words: Elevating detailed image cap- tioning with benchmark and alignment learning

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:58:43.799450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 06973013-4ceb-4e65-9981-10885271bcc2 · outbound

This paper cites From image descriptions to visual denotations: New similarity metrics for semantic inference over event descrip- tions.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning From image descriptions to visual denotations: New similarity metrics for semantic inference over event descrip- tions

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:58:43.538357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 286c0451-cefe-417d-b5b2-539ff841a4cc · outbound

This paper cites Dolphin: Moving Towards Closed-loop Auto-research through Thinking, Practice, and Feedback.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Dolphin: Moving Towards Closed-loop Auto-research through Thinking, Practice, and Feedback

Reference 56

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Observation a4143063-826d-4d87-8f4b-d3928d2c9a17 · outbound

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Llamafac- tory: Unified efficient fine-tuning of 100+ language mod- els

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:58:43.308003Z

Source-reported events for the cited work

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Observation f019cea8-0459-4f92-9edc-ef2aa042c1d1 · outbound

This paper cites For relation evaluation, we prompt open-source language models to answer the given questions based on the candi- date captions.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning For relation evaluation, we prompt open-source language models to answer the given questions based on the candi- date captions

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:58:43.061158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 428c3552-a994-4ef9-81e8-7a21593a6f4d · outbound

This paper cites We randomly select 100 images in DOCCI500 and ask 4 hu- man annotators to sort the captions provided by 4 differ- ent models, while considering both precision and recall.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning We randomly select 100 images in DOCCI500 and ask 4 hu- man annotators to sort the captions provided by 4 differ- ent models, while considering both precision and recall

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:58:42.872936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c2004cf0-d76e-4d56-98cf-8b8a7def2239 · outbound

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SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Unresolved cited work

Reference 60

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Source-reported events for the cited work

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Observation fda26ee6-9fde-4241-a578-41c2aa1e3087 · outbound

This paper cites Same-Domain.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Same-Domain

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:58:42.425937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 735b9408-4ed1-4bcf-a845-1b810bb084be · outbound

This paper cites an unresolved cited work.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-05T22:58:42.154224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 66ef2bd3-43ed-49b6-8f6b-afe224ba9a46 · outbound

This paper cites Because the training process includ- ing generating annotations for two rounds, the training time is relatively long.

SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning Because the training process includ- ing generating annotations for two rounds, the training time is relatively long

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:58:41.900996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

Observation 13681d6c-ab6c-4375-8891-fa98f517130c · inbound

VCap: Hypergeometric Rewards for Weak-to-Strong Visual Captioning cites this paper.

VCap: Hypergeometric Rewards for Weak-to-Strong Visual Captioning SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-06-29T13:23:28.464514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 32df02c4-e8c5-432c-9613-d439311c6804 · inbound

Modeling Complex Behaviors: Multi-Personality Composition and Dynamic Switching in Vision-Language Models cites this paper.

Modeling Complex Behaviors: Multi-Personality Composition and Dynamic Switching in Vision-Language Models SC-Captioner: Improving Image Captioning with Self-Correction by Reinforcement Learning

Reference 104

Resolution: verified exact; arxiv_id, observed 2026-07-03T05:47:41.747057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.