Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-10T00:33:39.960170Z
Paper Citation Record · LEDGER
As of 5 August 2026, this Paper Citation Record lists 100 of 190 outbound references and 1 inbound Pith citation observation for arXiv:2604.20366.
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 2026-05-10T00:33:39.960170Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-01T08:35:09.009897Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-01T08:35:33.345007Z
100 of 190 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 08925db3-74ea-4fe7-b20a-12abb3108fec · outbound
Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Aho and Jeffrey D
Reference 1
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Unresolved cited work
Reference 2
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Chandra and Dexter C
Reference 3
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Scalable training of
Reference 4
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Observation c0b5dbfe-e0ce-41e2-b99d-824277e29a8f · outbound
Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Unresolved cited work
Reference 5
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Tetreault , title =
Reference 6
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Observation 25661c6d-4b48-4bf3-9e8c-64c227f188b0 · outbound
Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data , Volume =
Reference 7
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation CoRR , volume =
Reference 8
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation CoRR , volume =
Reference 9
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Zou , title =
Reference 10
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation CoRR , volume =
Reference 11
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Black Box Few-Shot Adaptation for Vision-Language models , journal =
Reference 12
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Observation 3e21fd6e-0ab5-494f-9008-41ea2519affa · outbound
Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation ECCV , year =
Reference 13
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation ImageNet
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories , booktitle =
Reference 15
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation CVPR , year =
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Observation 2218bb55-b8fe-4cc8-9474-cbc1b91aec2c · outbound
Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Unresolved cited work
Reference 17
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Blaschko and Andrea Vedaldi , title =
Reference 18
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Automated Flower Classification over a Large Number of Classes , booktitle =
Reference 19
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation ECCV , year =
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Parkhi and Andrea Vedaldi and Andrew Zisserman and C
Reference 21
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation 3D Object Representations for Fine-Grained Categorization , booktitle =
Reference 22
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Ehinger and Aude Oliva and Antonio Torralba , title =
Reference 23
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation CoRR , volume =
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation ICML , year =
Reference 25
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Kingma and Jimmy Ba , title =
Reference 26
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Observation 6f417805-b71a-45d3-9d96-06ca4317671b · outbound
Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation CoRR , volume =
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation IJCV , volume =
Reference 28
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Unresolved cited work
Reference 29
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Advances in Neural Information Processing Systems , pages=
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation ICCV , year=
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation CVPR , year =
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation CoRR , volume =
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Unresolved cited work
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Flamingo: a Visual Language Model for Few-Shot Learning , booktitle =
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Open-vocabulary Object Detection via Vision and Language Knowledge Distillation , booktitle =
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation CVPR , year =
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Observation cef672fb-b1fa-46d4-8d78-d3133f8d6738 · outbound
Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Bermano , title =
Reference 40
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Unresolved cited work
Reference 41
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Unresolved cited work
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Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Connectionist Temporal Fusion for Sign Language Translation , booktitle =
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