Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T11:07:46.368829Z
Paper Citation Record · LEDGER
As of 13 August 2026, this Paper Citation Record lists 80 of 80 outbound references and 0 inbound Pith citation observations for arXiv:2608.09772.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T11:07:46.368829Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
80 of 80 outbound references displayed
External citation measurements
No source-named external measurement is stored.
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) , pages=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Aho and Jeffrey D
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Chandra and Dexter C
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Scalable training of
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Tetreault , title =
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data , Volume =
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models cortex , volume=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models arXiv preprint arXiv:2412.14613 , year=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Unresolved cited work
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the 34th ACM International Conference on Information and Knowledge Management , pages=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Sarcasm and the Space Structuring Model , year =
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Communications of the ACM , volume=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the 24th ACM international conference on Multimedia , pages=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the 57th annual meeting of the association for computational linguistics , pages=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the 60th annual meeting of the association for computational linguistics (volume 1: Long papers) , pages=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the 20th international conference on multimodal interaction: adjunct , pages=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models how long did you marinate in it? multimodal sarcasm explanation , author=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Findings of the Association for Computational Linguistics: EMNLP 2020 , pages=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the 32nd ACM International Conference on Multimedia , pages=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models International conference on machine learning , pages=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Unresolved cited work
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models IEEE Transactions on Affective Computing , volume=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models A Survey of Multimodal Sarcasm Detection
Reference 30
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models GPT-4 Technical Report
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the AAAI Conference on Artificial Intelligence , volume=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Benchmarking Reasoning Robustness in Large Language Models
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , pages=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models arXiv preprint arXiv:2509.22437 , year=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models On the Foundations of Shortcut Learning
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the Computer Vision and Pattern Recognition Conference , pages=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models arXiv preprint arXiv:2602.15183 , year=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the AAAI Conference on Artificial Intelligence , volume=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the 57th annual meeting of the association for computational linguistics , pages=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , pages =
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models How Do Vision-Language Models Process Conflicting Information Across Modalities?
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models VLMs Need Words: Vision Language Models Ignore Visual Detail In Favor of Semantic Anchors
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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges
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Observation 17e945b9-15dd-490a-af73-ffbdaabcee80 · outbound
PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models Advances in neural information processing systems , volume=
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