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Paper Citation Record · LEDGER

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models

As of 10 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2502.09645.

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

pith.paper-citation-record.v1
2502.09645 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:46:05.866175Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

41 of 41 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0cb3596c-8fff-4242-beb3-f0728aa9dde3 · outbound

This paper cites In: International Conference on Machine Learning, pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: International Conference on Machine Learning, pp

Reference 1

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Observation 4cbec034-ab51-4541-b109-5b7628c9cf2d · outbound

This paper cites In: International Conference on Machine Learning, pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: International Conference on Machine Learning, pp

Reference 2

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Observation 95791069-766b-4743-8d66-3dd5e4f46ea2 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 3

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This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 4

Resolution
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Observation cd0d84a6-8f9e-4df4-9616-804e21b3d612 · outbound

This paper cites Acta Psychologica, 1–7 (2014).

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models Acta Psychologica, 1–7 (2014)

Reference 5

Resolution
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Observation a77c7ae5-f97a-4601-8e04-6dc2ea7d378d · outbound

This paper cites In: Proceed- ings of the 12th Joint Conference on Lexical and Computational Semantics, pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Proceed- ings of the 12th Joint Conference on Lexical and Computational Semantics, pp

Reference 6

Resolution
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Observation 5cbafe91-67a0-4733-a5db-93a7d9dd3456 · outbound

This paper cites In: Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track (2023).

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track (2023)

Reference 7

Resolution
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Observation 922d83da-77e1-474c-94b9-16d1dd697c80 · outbound

This paper cites Learn "No" to Say "Yes" Better: Improving Vision-Language Models via Negations.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models Learn "No" to Say "Yes" Better: Improving Vision-Language Models via Negations

Reference 8

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This paper cites In: The Thirty-eighth Annual Conference on Neural Informa- tion Processing Systems (2024).

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: The Thirty-eighth Annual Conference on Neural Informa- tion Processing Systems (2024)

Reference 9

Resolution
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Observation edb260f7-0b6e-4624-9ae5-0fcfa8b97e43 · outbound

This paper cites In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, pp

Reference 10

Resolution
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Observation 7a72be38-5f15-481a-b02d-d58a0fe0316e · outbound

This paper cites In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp

Reference 11

Resolution
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Observation 2d26e154-4b57-41f7-add5-5cbe230c8c4f · outbound

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From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models guesswhat?! dialogues as a case study

Reference 12

Resolution
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This paper cites In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pp

Reference 13

Resolution
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This paper cites In: Ger- man Conference on Artificial Intelligence (K¨ unstliche Intelligenz), pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Ger- man Conference on Artificial Intelligence (K¨ unstliche Intelligenz), pp

Reference 14

Resolution
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This paper cites 2022 ieee.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models 2022 ieee

Reference 15

Resolution
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This paper cites Investigating and Addressing Hallucinations of LLMs in Tasks Involving Negation.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models Investigating and Addressing Hallucinations of LLMs in Tasks Involving Negation

Reference 16

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This paper cites In: Pro- ceedings of the Joint International Conference on Computational Linguistics, Language Resources and Evaluation, pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Pro- ceedings of the Joint International Conference on Computational Linguistics, Language Resources and Evaluation, pp

Reference 17

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This paper cites JMIR Med Inform 2023;11:e46348 (2023).

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models JMIR Med Inform 2023;11:e46348 (2023)

Reference 18

Resolution
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This paper cites Language and linguistics compass 1(5), 552–570 (2007) 15.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models Language and linguistics compass 1(5), 552–570 (2007) 15

Reference 19

Resolution
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This paper cites In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, pp

Reference 20

Resolution
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This paper cites Transactions of the Association for Computational Linguistics 8, 34–48 (2020).

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models Transactions of the Association for Computational Linguistics 8, 34–48 (2020)

Reference 21

Resolution
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This paper cites IEEE transactions on affective computing 10(3), 374–393 (2017).

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models IEEE transactions on affective computing 10(3), 374–393 (2017)

Reference 22

Resolution
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This paper cites PhD thesis, University of Oxford (1978).

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models PhD thesis, University of Oxford (1978)

Reference 23

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This paper cites Natural Language & Linguistic Theory, 775–825 (2020).

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models Natural Language & Linguistic Theory, 775–825 (2020)

Reference 24

Resolution
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From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models looking at

Reference 25

Resolution
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This paper cites Psychological bulletin 138(3), 427 (2012).

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models Psychological bulletin 138(3), 427 (2012)

Reference 26

Resolution
verified fuzzy
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This paper cites Journal of Psycholinguistic Research 50(6), 1511–1534 (2021).

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models Journal of Psycholinguistic Research 50(6), 1511–1534 (2021)

Reference 27

Resolution
verified fuzzy
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This paper cites Advances in neural information processing systems 35, 24824–24837 (2022).

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models Advances in neural information processing systems 35, 24824–24837 (2022)

Reference 28

Resolution
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Unavailable: canonical work link unavailable.

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This paper cites In: The Twelfth International Conference on Learning Representations (2024).

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: The Twelfth International Conference on Learning Representations (2024)

Reference 29

Resolution
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This paper cites In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp

Reference 30

Resolution
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From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models Unresolved cited work

Reference 31

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This paper cites In: Proceedings of the ACM International Conference on Multimedia, 16 pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Proceedings of the ACM International Conference on Multimedia, 16 pp

Reference 32

Resolution
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Observation 62f66f11-d435-46da-aabe-5ea9aaa6a2ad · outbound

This paper cites Pengi: An Audio Language Model for Audio Tasks.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models Pengi: An Audio Language Model for Audio Tasks

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-08T14:46:05.826188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T14:46:05.826188Z digest=sha256:edc9699c31aa08a76f623820a08df10ab6e359b81c844a11a489d603fe12de37

Observation b145106a-5068-410f-925b-b26c182da3e3 · outbound

This paper cites GAMA: A Large Audio-Language Model with Advanced Audio Understanding and Complex Reasoning Abilities.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models GAMA: A Large Audio-Language Model with Advanced Audio Understanding and Complex Reasoning Abilities

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-08T14:46:05.831117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T14:46:05.831117Z digest=sha256:39d3dfdd267e6562795a56c6b90919a4526b955b6189b87e5e985895f85afb61

Observation f82e1333-e9c1-442d-add4-3d3f8b8b7e2a · outbound

This paper cites In: Findings of the Association for Computational Linguistics, pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Findings of the Association for Computational Linguistics, pp

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T14:46:06.069501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T14:46:05.836475Z digest=sha256:b9d10e0441619cc7edd8e24bd0c9d7296fa01975c87885f7dfdbf6976b4ad202

Observation facda2a3-8050-4464-8ffc-bd4094059314 · outbound

This paper cites In: Findings of the Association for Computational Linguistics, pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Findings of the Association for Computational Linguistics, pp

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T14:46:06.051460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T14:46:05.841249Z digest=sha256:fcf40448101652e25ef684adfb30c1f52a2c0a17ca04fd260ea587974be7ae4f

Observation 5b55cfbc-e8e9-4799-9074-1970eb956f71 · outbound

This paper cites In: Findings of the Association for Computational Linguistics, pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Findings of the Association for Computational Linguistics, pp

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T14:46:06.035374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T14:46:05.846695Z digest=sha256:dac94c31027355665db465f8d8c26c48d1184fbdb5d72e0a201725b282fceee2

Observation 467c7cd6-04d5-4e95-8914-b9f67cd1bf4f · outbound

This paper cites ECCV (2024).

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models ECCV (2024)

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T14:46:06.019457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T14:46:05.851477Z digest=sha256:4ca053a98e68c5ba005eb29cca2dfe43bd4f32a70ce6cf4fcdc3396b14a78178

Observation 91da3d42-c9ce-4efd-be91-5454104c2b32 · outbound

This paper cites In: Findings of the Association for Computational Linguistics, pp.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models In: Findings of the Association for Computational Linguistics, pp

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T14:46:06.003064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T14:46:05.856265Z digest=sha256:f459962b262b6aed2bc204cb61bce9c947f79e2f23cb321bf96a281003bfe862

Observation 51e4b3de-02a3-4418-a56e-27b3e73fc7dd · outbound

This paper cites Qtok: A Comprehensive Framework for Evaluating Multilingual Tokenizer Quality in Large Language Models.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models Qtok: A Comprehensive Framework for Evaluating Multilingual Tokenizer Quality in Large Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-08T14:46:05.860919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T14:46:05.860919Z digest=sha256:fd9c737b015efb934ecd2930a0ff9266037dd365d9229586e86c1b6d19040d29

Observation 3b382a4b-4be3-45a4-a7f4-d802ce8395e5 · outbound

This paper cites Neurocomputing 284, 171–176 (2018) 17.

From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models Neurocomputing 284, 171–176 (2018) 17

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T14:46:05.985712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T14:46:05.866175Z digest=sha256:b1793216ada1fa29c32a35030595090633cb01e8625ca756d3ef2c051bcb1ed9

Pith citing papers

No inbound Pith citation observations are available.