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Paper Citation Record · LEDGER

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA

As of 9 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2607.17834.

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

pith.paper-citation-record.v1
2607.17834 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T16:57:32.887608Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

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Source: cited_works

Reference resolution

30 of 30 outbound references displayed

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External citation measurements

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Outbound references

Observation c226c4d6-8743-48bd-9b8b-6e39f5d219fa · outbound

This paper cites VQA: Visual question answering,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA VQA: Visual question answering,

Reference 1

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Observation a0b8df16-3cb7-4e2c-8aaf-02a910a9f57b · outbound

This paper cites Medical visual question answering: A survey,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA Medical visual question answering: A survey,

Reference 2

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Observation 7588d7a5-0c30-4e5f-9445-c71634231bb5 · outbound

This paper cites EndoBench: A comprehensive evaluation of multi-modal large language models for endoscopy analysis,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA EndoBench: A comprehensive evaluation of multi-modal large language models for endoscopy analysis,

Reference 3

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source=pdf_text observed=2026-08-01T16:57:30.392641Z digest=sha256:57abf5a9f272bc5878d0b3e94f66d9eec414108dcbbfd2828a8c565c867f8ed0

Observation 8efd54df-b6e2-4fc6-bbec-7266b15ba063 · outbound

This paper cites Kvasir-VQA: A text-image pair gi tract dataset,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA Kvasir-VQA: A text-image pair gi tract dataset,

Reference 4

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source=pdf_text observed=2026-08-01T16:57:30.507401Z digest=sha256:d505b4ebcc0ac1f58bf1d1f87ecf2f0f20ad3c18b4850fafd29c9cf0bf3a481b

Observation e4faedd8-0162-413c-94cc-6b6cde36c72b · outbound

This paper cites Kvasir-VQA-x1: A Multimodal Dataset for Medical Reasoning and Robust MedVQA in Gastrointestinal Endoscopy.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA Kvasir-VQA-x1: A Multimodal Dataset for Medical Reasoning and Robust MedVQA in Gastrointestinal Endoscopy

Reference 5

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source=pdf_text observed=2026-08-01T16:57:30.636879Z digest=sha256:188351454a997518589627f350499ffd16a6b668d85483fd132972254506d96a

Observation fc0eb9c2-6684-44f7-a85e-eb33fe6f65c0 · outbound

This paper cites A dataset of clinically generated visual questions and answers about radiology images,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA A dataset of clinically generated visual questions and answers about radiology images,

Reference 6

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source=pdf_text observed=2026-08-01T16:57:30.759344Z digest=sha256:185e537d2959cc7f18b9e2d8588c4aedc521dd64d9a0cd7cff72ae0ea7ce3d32

Observation 13ecf9ea-2aff-4da9-bddf-4357eeb8c9f2 · outbound

This paper cites SLAKE: A semantically-labeled knowledge-enhanced dataset for medical visual question answering,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA SLAKE: A semantically-labeled knowledge-enhanced dataset for medical visual question answering,

Reference 7

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source=pdf_text observed=2026-08-01T16:57:30.837145Z digest=sha256:cc7e61153d34b4c36cabb936b5e4a437b5130b7e78ba1c6ceb01e23eca3a3a80

Observation 0d86f0d9-a5c4-4074-ac96-ece0213df90a · outbound

This paper cites PathVQA: 30000+ Questions for Medical Visual Question Answering.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA PathVQA: 30000+ Questions for Medical Visual Question Answering

Reference 8

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Observation 0f808a84-0563-41da-bd2a-bbc15ac094c5 · outbound

This paper cites Gastric-X: A multimodal multi-phase benchmark dataset for advancing vision-language models in gastric cancer analysis,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA Gastric-X: A multimodal multi-phase benchmark dataset for advancing vision-language models in gastric cancer analysis,

Reference 9

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Observation db7da7da-3c37-4341-aca2-c6eee986dffc · outbound

This paper cites Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025

Reference 10

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Observation 74a4b3a4-e836-491a-b8b2-90fbe4f12fc0 · outbound

This paper cites SQuINTing at VQA models: Introspecting VQA models with sub-questions,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA SQuINTing at VQA models: Introspecting VQA models with sub-questions,

Reference 11

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Observation 4b249f0d-93bb-4a93-9202-43022fd45f11 · outbound

This paper cites GQA: A new dataset for real- world visual reasoning and compositional question answering,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA GQA: A new dataset for real- world visual reasoning and compositional question answering,

Reference 12

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Observation cf4500e2-5de4-4bec-aea0-d5fdf2414192 · outbound

This paper cites FActScore: Fine-grained atomic eval- uation of factual precision in long form text generation,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA FActScore: Fine-grained atomic eval- uation of factual precision in long form text generation,

Reference 13

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Observation e8ff2250-0596-4bee-860d-e771419965a4 · outbound

This paper cites FaithScore: Fine-grained evaluations of hallucinations in large vision-language models,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA FaithScore: Fine-grained evaluations of hallucinations in large vision-language models,

Reference 14

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Observation 01dc26f3-4482-408c-b211-f889a69e0e33 · outbound

This paper cites Evaluating object hallucination in large vision-language models,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA Evaluating object hallucination in large vision-language models,

Reference 15

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Observation f1bc5eee-e0b1-4352-a770-c174d69ebae3 · outbound

This paper cites SurgViVQA: Temporally grounded video question answering for surgical scene understanding,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA SurgViVQA: Temporally grounded video question answering for surgical scene understanding,

Reference 16

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Observation 5dfea074-c306-41b4-b149-055e26de5cc5 · outbound

This paper cites SOrT- ing VQA Models: Contrastive gradient learning for improved consistency,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA SOrT- ing VQA Models: Contrastive gradient learning for improved consistency,

Reference 17

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Observation c18ab17b-d6b4-417e-8ad3-8a879bfe374f · outbound

This paper cites Self-consistency improves chain of thought reasoning in language models,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA Self-consistency improves chain of thought reasoning in language models,

Reference 18

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Observation 5399dae0-f9cf-4776-826b-772e8e4f90ca · outbound

This paper cites SelfCheckGPT: Zero-resource black-box hallucination detection for generative large language models,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA SelfCheckGPT: Zero-resource black-box hallucination detection for generative large language models,

Reference 19

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Observation c06feab4-bebe-4064-807e-32a6c9601e79 · outbound

This paper cites EndoCogniAgent: Closed-Loop Agentic Reasoning with Self-Consistency Validation for Endoscopic Diagnosis.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA EndoCogniAgent: Closed-Loop Agentic Reasoning with Self-Consistency Validation for Endoscopic Diagnosis

Reference 20

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Observation 96c323b5-3c29-4b2d-9806-3668349ca33a · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 21

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Observation 5fd35ddb-1b5a-4314-a2e9-965536bca052 · outbound

This paper cites Qwen2.5-VL Technical Report.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA Qwen2.5-VL Technical Report

Reference 22

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Observation 8c0b1bff-2845-445d-822b-b12f32f4dfa9 · outbound

This paper cites Qwen3-VL Technical Report.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA Qwen3-VL Technical Report

Reference 23

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Observation 4fd063ac-3bc3-4847-8aff-5f839cc11f9b · outbound

This paper cites MedGemma Technical Report.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA MedGemma Technical Report

Reference 24

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Observation 49e8a40b-ba03-42f8-a806-0e46509b089a · outbound

This paper cites Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning

Reference 25

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Observation 2418b604-cf9f-4f8c-bb49-0317d304ba3f · outbound

This paper cites LLaV A-Med: Training a large language-and-vision assistant for biomedicine in one day,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA LLaV A-Med: Training a large language-and-vision assistant for biomedicine in one day,

Reference 26

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Observation 9f02fa70-90ac-4710-a0bf-cc547e1c9f19 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA LoRA: Low-Rank Adaptation of Large Language Models

Reference 27

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Observation 0138a730-b715-4916-994f-82cd3726ece4 · outbound

This paper cites Introducing GPT-5.5,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA Introducing GPT-5.5,

Reference 28

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Observation 0205a04a-0f89-4a80-be9f-b9d06b64c46c · outbound

This paper cites Grok 4.20,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA Grok 4.20,

Reference 29

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Observation a6729660-0267-40d7-a6a0-3b8e74616e57 · outbound

This paper cites Introducing Claude Opus 4.7,.

Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA Introducing Claude Opus 4.7,

Reference 30

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Pith citing papers

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