Paper Citation Record · LEDGER

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution

As of 8 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2607.17712.

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

pith.paper-citation-record.v1
2607.17712 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T17:16:52.990950Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

35 of 35 outbound references displayed

verified exact3
verified fuzzy0
unresolved31
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 755dc927-e54f-4ef6-901b-ad47bf243902 · outbound

This paper cites Learning to detect cross- modal negation: An analysis of latent representations and an attention- based solution,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Learning to detect cross- modal negation: An analysis of latent representations and an attention- based solution,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:48.978958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d05db44-c333-4cff-93d2-95ac2cf3cecb · outbound

This paper cites Negation,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Negation,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:49.083943Z

Source-reported events for the cited work

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Observation c66b7f62-076f-4288-8c1a-9b3ecd79758b · outbound

This paper cites Disentangling inhibition and prediction in negation processing,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Disentangling inhibition and prediction in negation processing,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:49.192930Z

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Unavailable: canonical work link unavailable.

Observation d5a46070-10b6-45e7-902e-4477b87d0c50 · outbound

This paper cites Vision-language models do not understand negation,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Vision-language models do not understand negation,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:49.258173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba0b10ad-bce1-4914-8808-6c1245457883 · outbound

This paper cites How does “not left.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution How does “not left

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:49.360332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d489bb5-47b9-489a-a2a6-c1578a17ea4f · outbound

This paper cites Negation as conflict: Conflict adaptation following negating vertical spatial words,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Negation as conflict: Conflict adaptation following negating vertical spatial words,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:49.409582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4da7667-85dd-4101-aa1e-21cacbf7516c · outbound

This paper cites Primordial Black-Hole Mimicker in Quadratic Gravity as Dark Matter.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Primordial Black-Hole Mimicker in Quadratic Gravity as Dark Matter

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:49.472768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bdcf615-91dd-4ec4-80d6-788139d587d1 · outbound

This paper cites V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:49.539776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a29561ed-e094-462d-b623-8ed01fb29d3c · outbound

This paper cites Qwen2.5-VL Technical Report.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Qwen2.5-VL Technical Report

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:49.546695Z

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Unavailable: canonical work link unavailable.

Observation b320dcd9-512e-44ab-af96-d1736afacdc1 · outbound

This paper cites A simple algorithm for identifying negated findings and diseases in discharge summaries,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution A simple algorithm for identifying negated findings and diseases in discharge summaries,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:49.660639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47a0595c-34b7-4454-bbb9-73d9d18bb0ff · outbound

This paper cites Deepen: A negation detection system for clinical text incorporating dependency relation into negex,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Deepen: A negation detection system for clinical text incorporating dependency relation into negex,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:49.826317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31c916fd-83e3-4982-93cd-faef3bc8cea4 · outbound

This paper cites NegBio: a high-performance tool for negation and uncertainty detection in radiology reports.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution NegBio: a high-performance tool for negation and uncertainty detection in radiology reports

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:50.029178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b58e1e4d-c4ae-45e9-b6ad-b5dac83d3993 · outbound

This paper cites UiO1: Constituent-based discriminative ranking for negation resolution,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution UiO1: Constituent-based discriminative ranking for negation resolution,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:50.181252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ba1046d-6acb-4ad1-a846-45788036db3c · outbound

This paper cites A machine-learning approach to negation and speculation detection for sentiment analysis,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution A machine-learning approach to negation and speculation detection for sentiment analysis,

Reference 14

Resolution: verified exact; doi, observed 2026-08-01T17:18:28.029934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4ea27dc5-d11c-465a-9393-7b4a767ad9aa · outbound

This paper cites Automatic negation detection in narrative pathology reports,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Automatic negation detection in narrative pathology reports,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:50.486174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6d12302-cd12-40e5-99cf-1bf7b37b00ea · outbound

This paper cites NegBERT: A Transfer Learning Approach for Negation Detection and Scope Resolution.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution NegBERT: A Transfer Learning Approach for Negation Detection and Scope Resolution

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:50.619125Z

Source-reported events for the cited work

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Observation 810ab825-a636-4b03-aa36-d676d890ea03 · outbound

This paper cites Improving negation detection with negation-focused pre-training.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Improving negation detection with negation-focused pre-training

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:50.742453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00d9c9d7-5bb1-4619-8f25-4683e34862e7 · outbound

This paper cites Speculation and negation identification via unified machine reading comprehension frameworks with lexical and syntactic data augmentation,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Speculation and negation identification via unified machine reading comprehension frameworks with lexical and syntactic data augmentation,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:50.826427Z

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Observation 26cc3f9a-194b-44cd-8f36-0cb380caa835 · outbound

This paper cites Thunder- nubench: A benchmark for llms’ sentence-level negation understanding,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Thunder- nubench: A benchmark for llms’ sentence-level negation understanding,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:50.927417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60e30cf5-a068-43e7-8096-347ea13ef380 · outbound

This paper cites Towards the roots of the negation problem: A multilingual NLI dataset and model scaling analysis,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Towards the roots of the negation problem: A multilingual NLI dataset and model scaling analysis,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:51.186659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation adea5d6f-33c6-4627-943b-7ae761f78f92 · outbound

This paper cites Thunder-NUBench: A Benchmark for LLMs' Sentence-Level Negation Understanding.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Thunder-NUBench: A Benchmark for LLMs' Sentence-Level Negation Understanding

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:51.049308Z

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Unavailable: canonical work link unavailable.

Observation 2c64eea7-e61a-45fb-8aab-116964fe7197 · outbound

This paper cites A review on negation role in twitter sentiment analysis,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution A review on negation role in twitter sentiment analysis,

Reference 22

Resolution: verified exact; doi, observed 2026-08-01T17:18:27.959204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f8a516c0-393b-49ba-a975-182cf6397271 · outbound

This paper cites Negation scope detection for Twitter sentiment analysis,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Negation scope detection for Twitter sentiment analysis,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:51.265985Z

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Unavailable: canonical work link unavailable.

Observation db2c8fbd-0389-4d6a-923a-f9f2f965e3cc · outbound

This paper cites Context matters: A pragmatic study of PLMs’ negation understanding,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Context matters: A pragmatic study of PLMs’ negation understanding,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:51.572325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1123a94b-98eb-4b88-a7a6-f0d40c1dcc16 · outbound

This paper cites Can negation be depicted? comparing human and machine understanding of visual representations,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Can negation be depicted? comparing human and machine understanding of visual representations,

Reference 25

Resolution: verified exact; doi, observed 2026-08-01T17:18:27.848760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dcfa4eed-6398-435f-a864-91ff91728b16 · outbound

This paper cites X-pool: Cross-modal language-video attention for text-video retrieval,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution X-pool: Cross-modal language-video attention for text-video retrieval,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:51.937998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5a32c30-4174-49a4-b350-719565c3f5b0 · outbound

This paper cites LINKED: Eliciting, filtering and integrating knowledge in large language model for commonsense reasoning,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution LINKED: Eliciting, filtering and integrating knowledge in large language model for commonsense reasoning,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:52.111531Z

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Unavailable: canonical work link unavailable.

Observation 0277fcc0-3422-41a9-ad1b-ead4a2624d18 · outbound

This paper cites Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:51.809690Z

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Unavailable: canonical work link unavailable.

Observation 037bd44e-3e4d-4bf9-9449-51853ebdf1f8 · outbound

This paper cites The "something something" video database for learning and evaluating visual common sense.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution The "something something" video database for learning and evaluating visual common sense

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:52.452286Z

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Unavailable: canonical work link unavailable.

Observation 5ae56ebe-c922-4260-8741-f3b4d5dfee9f · outbound

This paper cites FLAVA: A Foundational Language And Vision Alignment Model.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution FLAVA: A Foundational Language And Vision Alignment Model

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:52.653162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4191095-1beb-4fa3-b31e-63a47735b954 · outbound

This paper cites Extending a parliamentary corpus with mps’ tweets: Automatic annotation and evaluation using multipartweet,.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Extending a parliamentary corpus with mps’ tweets: Automatic annotation and evaluation using multipartweet,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:52.269946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 841174b5-935d-4963-b20b-82765a41a5c9 · outbound

This paper cites text_negation.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution text_negation

Reference 32

Resolution: malformed identifier; no resolver link, observed 2026-08-01T17:16:52.990950Z

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Observation 48119d92-f026-4b63-bd4f-afa42d52fbe7 · outbound

This paper cites an unresolved cited work.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Unresolved cited work

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:52.829223Z

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Unavailable: canonical work link unavailable.

Observation 64c36674-3a95-4912-9f7c-3014d8fc0d3a · outbound

This paper cites Vision-Language Models Do Not Understand Negation.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Vision-Language Models Do Not Understand Negation

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:49.314099Z

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Observation b12a625a-3508-4f72-b862-73805c7c9860 · outbound

This paper cites Available: https://aclanthology.org/2022.acl-long.315/.

Learning to Detect Cross-Modal Negation: An Analysis of Latent Representations and an Attention-Based Solution Available: https://aclanthology.org/2022.acl-long.315/

Reference 4621

Resolution: unresolved; no resolver link, observed 2026-08-01T17:16:51.722586Z

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Pith citing papers

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