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Paper Citation Record · LEDGER

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering

As of 23 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2509.09159.

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

pith.paper-citation-record.v1
2509.09159 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:37:52.424689Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

23 of 23 outbound references displayed

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External citation measurements

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Outbound references

Observation a07b7c29-e279-4a51-a306-2446feb57729 · outbound

This paper cites Ok-vqa: A visual question answering benchmark requiring external knowledge,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Ok-vqa: A visual question answering benchmark requiring external knowledge,

Reference 1

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source=pdf_text observed=2026-08-04T19:37:50.894535Z digest=sha256:de7eba2f8538d95bc652c05cf8c55285654bb52b0420da199155b6c16bc655dc

Observation 83efb83a-0e4e-4ca4-a9f9-82e756f27b18 · outbound

This paper cites Vqa: Visual question answering,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Vqa: Visual question answering,

Reference 2

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source=pdf_text observed=2026-08-04T19:37:50.974484Z digest=sha256:442e53c78f8f7639238c0163b211d07c3ca21e04d04f210466f5ec93f6f79be5

Observation 34b58d61-907a-4d50-a040-4981d09ab56d · outbound

This paper cites Krisp: Integrating implicit and symbolic knowledge for open-domain knowledge-based vqa,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Krisp: Integrating implicit and symbolic knowledge for open-domain knowledge-based vqa,

Reference 3

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source=pdf_text observed=2026-08-04T19:37:51.042425Z digest=sha256:5d4486dd008c11c7ec9260d8654b3f717b701d2f53cfa21bc4e0dddb4ddd5cc6

Observation c3eb1eec-27db-40ee-b3e8-274736133fbb · outbound

This paper cites Weakly- supervised visual-retriever-reader for knowledge-based question answer- ing,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Weakly- supervised visual-retriever-reader for knowledge-based question answer- ing,

Reference 4

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source=pdf_text observed=2026-08-04T19:37:51.129782Z digest=sha256:a8bf451ee6c02f2113e53ff4dd80208ffde3f486ce67ab5bd6c41228bee13fe8

Observation f4044ebb-6b00-4c76-86b0-faa91bc68fe1 · outbound

This paper cites Conceptnet—a practical commonsense reasoning tool-kit,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Conceptnet—a practical commonsense reasoning tool-kit,

Reference 5

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source=pdf_text observed=2026-08-04T19:37:51.230318Z digest=sha256:5d6b725258bdc3196bf5530a849365ed9bbb450be9b1afecf19971b4cb140a01

Observation 88ddd3c4-4808-4004-83d7-e4ac348c7447 · outbound

This paper cites Wikidata: a free collaborative knowledgebase,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Wikidata: a free collaborative knowledgebase,

Reference 6

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source=pdf_text observed=2026-08-04T19:37:51.302400Z digest=sha256:dbd8c5c32f187a5ca8e2f5874c7353352ee651985fa01a711f9c2ba56852e6bc

Observation bb1bee8b-9f69-4c29-8575-f1c0f40c141c · outbound

This paper cites An empirical study of gpt-3 for few- shot knowledge-based vqa,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering An empirical study of gpt-3 for few- shot knowledge-based vqa,

Reference 7

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source=pdf_text observed=2026-08-04T19:37:51.376819Z digest=sha256:34f52a34608baa08ceaeccb145ac30829e13728f66bb51bd44231e8146a4b003

Observation 5e64fde6-2148-4d1a-9d92-bbca0b6975cd · outbound

This paper cites Promptcap: Prompt-guided image captioning for vqa with gpt-3,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Promptcap: Prompt-guided image captioning for vqa with gpt-3,

Reference 8

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source=pdf_text observed=2026-08-04T19:37:51.433327Z digest=sha256:e01533397678c90a803c6417085b47b4d46a9e00fad6dbb78b2c53a190666277

Observation 0d8122c5-af46-4644-a04a-ac0aa88072fd · outbound

This paper cites Prompting large language models with answer heuristics for knowledge-based visual question answering,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Prompting large language models with answer heuristics for knowledge-based visual question answering,

Reference 9

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source=pdf_text observed=2026-08-04T19:37:51.513128Z digest=sha256:f7c54a976d85fb6838d88d4a6a32d116f61090433f5857e5a7d37441de0a5e46

Observation c106c386-860e-4a63-9b91-e974ff84ceef · outbound

This paper cites A simple baseline for knowledge-based visual question answering,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering A simple baseline for knowledge-based visual question answering,

Reference 10

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source=pdf_text observed=2026-08-04T19:37:51.557955Z digest=sha256:0f1b92861e9b3e2d1152e71a8046443411612a14f120b888ee27d301a1e3553c

Observation e3c08c35-b567-4df0-a0eb-ef9653f3374c · outbound

This paper cites Knowledge Acquisition Disentanglement for Knowledge-based Visual Question Answering with Large Language Models.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Knowledge Acquisition Disentanglement for Knowledge-based Visual Question Answering with Large Language Models

Reference 11

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source=pdf_text observed=2026-08-04T19:37:51.602950Z digest=sha256:ee7fb029fc6fe79e42d0c94588c5f4d12438946ad961ff998cfbdc7bf1f6ae20

Observation 6a878b65-fb04-4602-9f6f-9322ad66edc8 · outbound

This paper cites Retrieval augmented visual question answering with outside knowledge,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Retrieval augmented visual question answering with outside knowledge,

Reference 12

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source=pdf_text observed=2026-08-04T19:37:51.680808Z digest=sha256:6817ef020a90ac16f27886a795ae7b0f32af30ee30d8f98ab3d9260435183423

Observation 25b138ef-8e71-408b-a634-c3d59b477a30 · outbound

This paper cites Self-bootstrapped visual-language model for knowledge selection and question answering,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Self-bootstrapped visual-language model for knowledge selection and question answering,

Reference 13

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source=pdf_text observed=2026-08-04T19:37:51.761216Z digest=sha256:7e5bfa17e730d279f57c2a41777b105797754ff48373ea522fed044573c251fa

Observation 28ebc970-51e9-4b4e-91e3-876325b098ac · outbound

This paper cites A-okvqa: A benchmark for visual question answering using world knowledge,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering A-okvqa: A benchmark for visual question answering using world knowledge,

Reference 14

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source=pdf_text observed=2026-08-04T19:37:51.820163Z digest=sha256:b9df3d81cb1859da8ca9737eba08ef88cd83977e44a23b4fbe92bf85232a8bf5

Observation c8a9a941-a485-47f3-9629-af419ca41048 · outbound

This paper cites Kat: A knowledge augmented transformer for vision-and-language,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Kat: A knowledge augmented transformer for vision-and-language,

Reference 15

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source=pdf_text observed=2026-08-04T19:37:51.905895Z digest=sha256:b9ccf187eea819c0f6d64d9fdf42cbd5e8d268ead687f42322d2ada5d07db97b

Observation 24a25799-80d1-4f9a-b8cd-06ccd8688ecc · outbound

This paper cites Revive: regional visual representation matters in knowledge-based visual question answering,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Revive: regional visual representation matters in knowledge-based visual question answering,

Reference 16

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source=pdf_text observed=2026-08-04T19:37:51.972528Z digest=sha256:375ff882660bdbac034dd70dc44abad6432e47f8b92a3b0ccf4ac481d94d184c

Observation 14299f28-0bee-4a3d-a19e-391a7673054b · outbound

This paper cites Fine-grained late-interaction multi-modal retrieval for retrieval augmented visual question answering,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Fine-grained late-interaction multi-modal retrieval for retrieval augmented visual question answering,

Reference 17

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source=pdf_text observed=2026-08-04T19:37:52.017873Z digest=sha256:bb3ed84d8b6efef2f1e0b35ac33dfce2bfbff4f8164178b947e559c5168e362b

Observation 96d9d140-9daa-4875-a113-9ee803e1b01b · outbound

This paper cites Deep modular co-attention networks for visual question answering,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Deep modular co-attention networks for visual question answering,

Reference 18

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source=pdf_text observed=2026-08-04T19:37:52.068855Z digest=sha256:8ff4ad08c70b96977ff394c7306daa85b8e05c689f58c3de88111907577c1395

Observation 4382623b-ad3e-4775-8909-551f8e7d2edf · outbound

This paper cites Plug-and-play vqa: Zero-shot vqa by conjoining large pretrained models with zero training,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Plug-and-play vqa: Zero-shot vqa by conjoining large pretrained models with zero training,

Reference 19

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source=pdf_text observed=2026-08-04T19:37:52.128504Z digest=sha256:9503638dea1c9aa4e239b4d96ae2d8780c7b732be85541f1cc6a491dd43384ad

Observation 072cbfb6-5098-4b8a-8bbe-c4d8ffdaa415 · outbound

This paper cites Webly supervised concept expansion for general purpose vision models,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Webly supervised concept expansion for general purpose vision models,

Reference 20

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source=pdf_text observed=2026-08-04T19:37:52.211170Z digest=sha256:a02f5ec49295369b771de862de7b281294a7d6a7d919f503accd7b6ed99108e7

Observation 5b0c9225-d55c-4870-991a-b3b0090de48c · outbound

This paper cites The Llama 3 Herd of Models.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering The Llama 3 Herd of Models

Reference 21

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source=pdf_text observed=2026-08-04T19:37:52.258305Z digest=sha256:d8d3c33e22bc8ccbdef43090d67c1bb1546ccedfca7f966a16a393bfaf4065bd

Observation 22279ef3-9385-4098-8cb8-ca5894b5eac9 · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 22

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source=pdf_text observed=2026-08-04T19:37:52.344454Z digest=sha256:cda64bcf270f73e8afe33d9666ef601785e2f67ef9667bbc43465543742eb9c8

Observation 06d52617-1243-4fcc-bdd8-f52df4398ec3 · outbound

This paper cites Instructblip: towards general-purpose vision-language models with instruction tuning,.

A Knowledge Noise Mitigation Framework for Knowledge-based Visual Question Answering Instructblip: towards general-purpose vision-language models with instruction tuning,

Reference 23

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source=pdf_text observed=2026-08-04T19:37:52.424689Z digest=sha256:a240d6f889225b8eba6ab92bd0b53297f9c448c4aec4dbea039ce66c6add7f8d

Pith citing papers

No inbound Pith citation observations are available.