Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:57:51.244796Z
Paper Citation Record · LEDGER
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025
As of 10 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 1 inbound Pith citation observation for arXiv:2507.14544.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T16:57:31.114754Z
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
27 of 27 outbound references displayed
- verified exact2
- verified fuzzy15
- unresolved7
- parse uncertain0
- malformed identifier0
- metadata mismatch3
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation ed17e8bd-9b45-4cc5-b20f-4ed2d5ae7b98 · outbound
This paper cites Vqa: Visual question an- swering.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Vqa: Visual question an- swering
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:57:51.715301Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 917e16fc-b3fd-496a-a4c1-591ffb87165f · outbound
This paper cites Prompt to Polyp: Medical Text-Conditioned Image Synthesis with Diffusion Models.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Prompt to Polyp: Medical Text-Conditioned Image Synthesis with Diffusion Models
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:57:51.182017Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a5c61c48-ebcc-41e9-bced-86d5c1f9d7f1 · outbound
This paper cites Exploratory data analysis.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Exploratory data analysis
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:57:51.708624Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 19671860-56d1-4ab7-8524-a1604c3096d2 · outbound
This paper cites Mapping medical image-text to a joint space via masked modeling.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Mapping medical image-text to a joint space via masked modeling
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:57:51.701691Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 4452c226-e998-4c73-9871-6ea9c39b2f39 · outbound
This paper cites Vision- language transformer and query generation for referring segmentation.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Vision- language transformer and query generation for referring segmentation
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:57:51.694595Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 0c7a4cd1-cc89-4c54-b125-36b774af5824 · outbound
This paper cites an unresolved cited work.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Unresolved cited work
Reference 6
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T15:57:51.687329Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 1722c8a3-45d2-4679-8dc0-42c7e77181c4 · outbound
This paper cites Bridging Multimedia Modalities: Enhanced Multimodal AI Understanding and Intelligent Agents.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Bridging Multimedia Modalities: Enhanced Multimodal AI Understanding and Intelligent Agents
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:57:51.679840Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation f0beebc1-9999-4b7e-97b3-738c0a256f0c · outbound
This paper cites Kvasir-VQA-x1: A Multimodal Dataset for Medical Reasoning and Robust MedVQA in Gastrointestinal Endoscopy.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Kvasir-VQA-x1: A Multimodal Dataset for Medical Reasoning and Robust MedVQA in Gastrointestinal Endoscopy
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:57:51.206063Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 86233827-70c9-4c20-85fb-799eb5c066fa · outbound
This paper cites Hicks, Vajira Thambawita, P ˚ al Halvorsen, and Michael A.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Hicks, Vajira Thambawita, P ˚ al Halvorsen, and Michael A
Reference 9
- Resolution
- metadata mismatch
- raw_fallback, observed 2026-08-06T15:57:51.376598Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation e741dce1-0bcc-4023-93c1-4a08f0304e2c · outbound
This paper cites Making the v in vqa matter: Elevating the role of image under- standing in visual question answering.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Making the v in vqa matter: Elevating the role of image under- standing in visual question answering
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:57:51.665240Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation b96e36bc-40d1-4992-98fc-e17246fb0c95 · outbound
This paper cites Unk-vqa: A dataset and a probe into the abstention ability of multi- modal large models.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Unk-vqa: A dataset and a probe into the abstention ability of multi- modal large models
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:57:51.657327Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation e42d92b9-b616-42be-a79a-447daed339a4 · outbound
This paper cites Unboxing the black box of attention mech- anisms in remote sensing big data using xai.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Unboxing the black box of attention mech- anisms in remote sensing big data using xai
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:57:51.648487Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ad9fce89-40e2-408d-a07f-17520ca1cfe4 · outbound
This paper cites an unresolved cited work.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Unresolved cited work
Reference 13
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T15:57:51.639196Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 52fce76b-5efc-4398-a560-1fd2926a21f2 · outbound
This paper cites A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Models.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Models
Reference 14
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T15:57:51.314658Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation eec7c4a0-b5c2-4e0c-9742-c6425111f476 · outbound
This paper cites A dataset of clinically generated visual questions and answers about radiology images.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 A dataset of clinically generated visual questions and answers about radiology images
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:57:51.629812Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ad66af8a-1587-48ad-bde3-2ae49004b792 · outbound
This paper cites Blip: Bootstrap- ping language-image pre-training for unified vision-language understanding and generation.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Blip: Bootstrap- ping language-image pre-training for unified vision-language understanding and generation
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:57:51.620877Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 9ceb7cfb-2943-4faf-b52d-6e4488ce4327 · outbound
This paper cites Contrastive pre-training and representation distillation for medical visual question answering based on radiology images.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Contrastive pre-training and representation distillation for medical visual question answering based on radiology images
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:57:51.611629Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 056a0cdb-ad1e-4a66-b930-761fe3d5ccc5 · outbound
This paper cites Slake: A semantically-labeled knowledge-enhanced dataset for medical vi- sual question answering.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Slake: A semantically-labeled knowledge-enhanced dataset for medical vi- sual question answering
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:57:51.602511Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 96e95a63-8207-4aca-8982-c9ecab8c1d1f · outbound
This paper cites Improved base- lines with visual instruction tuning.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Improved base- lines with visual instruction tuning
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:57:51.592236Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 07196891-9335-457c-8edd-c9ce5cd95e30 · outbound
This paper cites Florence-2: Advancing a unified representation for a variety of vision tasks.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Florence-2: Advancing a unified representation for a variety of vision tasks
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:57:51.235217Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ec70c0d9-9ccf-41fc-883a-365e7fb63635 · outbound
This paper cites A survey of efficient fine-tuning methods for vision-language models—prompt and adapter.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 A survey of efficient fine-tuning methods for vision-language models—prompt and adapter
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:57:51.575920Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a61747b3-7918-4215-8f59-8b2ab5cda85c · outbound
This paper cites Multi-modal concept align- ment pre-training for generative medical visual question answering.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Multi-modal concept align- ment pre-training for generative medical visual question answering
Reference 22
- Resolution
- verified exact
- doi, observed 2026-08-06T15:57:51.271628Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 952f75b6-7fa7-4b3e-90e0-63aea0e300d9 · outbound
This paper cites VQA and Visual Reasoning: An Overview of Recent Datasets, Methods and Challenges.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 VQA and Visual Reasoning: An Overview of Recent Datasets, Methods and Challenges
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:57:51.242123Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2b306bd7-60f4-46a7-abd9-7848f0f9f7fe · outbound
This paper cites Medical visual question answering via conditional reasoning.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Medical visual question answering via conditional reasoning
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T15:57:51.565319Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ef7d4920-9ac2-4e48-bbe3-717594c224ec · outbound
This paper cites an unresolved cited work.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Unresolved cited work
Reference 699
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T15:57:51.672540Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 9f4fee1c-b771-45d2-8480-77092804978e · outbound
This paper cites an unresolved cited work.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Unresolved cited work
Reference 2023
- Resolution
- metadata mismatch
- raw_fallback, observed 2026-08-06T15:57:51.473870Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 031d157a-5c45-47c9-a918-6be118d30dd0 · outbound
This paper cites an unresolved cited work.
Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 Unresolved cited work
Reference 2024
- Resolution
- metadata mismatch
- raw_fallback, observed 2026-08-06T15:57:51.556209Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Pith citing papers
Observation db7da7da-3c37-4341-aca2-c6eee986dffc · inbound
Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA cites this paper.
Measuring and Improving Complex-Atomic Answer Consistency in Endoscopic VQA Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T16:57:31.114754Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.