Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:41:45.954845Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 86 of 86 outbound references and 0 inbound Pith citation observations for arXiv:2506.01738.
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 2026-08-07T11:41:45.954845Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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
86 of 86 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 48efcff6-b4d3-4560-a46e-732fc4eec187 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset ITU-R Rec
Reference 1
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Reference 5
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Reference 10
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Reference 11
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Observation da309fbb-8f42-4730-9f76-6cfe4d68660d · outbound
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Reference 12
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Observation ea5582a3-46c1-4ca1-9f97-1a1d62e78854 · outbound
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Reference 13
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Observation 8c226f87-0456-4b1d-9e68-395cb1ef0a5c · outbound
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Reference 14
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STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Perceptual quality assessment of smartphone photography
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STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset A simple approach to ordinal classification
Reference 16
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Observation 24e83b33-aa71-4fa0-8ffc-e42d6f7a8ee9 · outbound
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Reference 17
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Observation 9c5a68cd-2626-4884-a9d0-6a05f6d20b59 · outbound
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Reference 18
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Observation 649e96d6-3324-450f-b7b5-b1f4cea2561b · outbound
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Reference 19
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Observation 6a65e19f-7b0d-44cc-aa1e-24025548fbb1 · outbound
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Reference 20
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Observation 8c9b9920-cef3-432d-967c-ab24b197084d · outbound
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Reference 21
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Observation 1da7bc38-b928-46e8-a733-7b34303b89da · outbound
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Reference 22
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Observation 39c9ac2c-97d3-4230-953d-1473c0e0e4c4 · outbound
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Reference 23
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Observation 985d1775-92d3-4c97-bd3e-c530f280ea3a · outbound
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Reference 24
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Observation 59b23d50-0a81-49ec-9d74-b6ea1e1e2429 · outbound
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Reference 25
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Observation 8c7517d0-cd52-4539-b581-0f1c95718f29 · outbound
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Reference 26
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Observation 11113140-16c8-4c23-abf7-a76ebf07b908 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset LISA: Reasoning Segmentation via Large Language Model
Reference 27
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Observation 61b40e72-401c-46d6-9a4b-816daf181223 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Deep repulsive clustering of ordered data based on order- identity decomposition
Reference 28
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Observation 113dcc0b-fad4-46ac-8cf9-748009a0180e · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Age and gender classification using convolutional neural networks
Reference 29
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Observation a836edaf-6aff-4960-be37-2024856d5f8e · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models
Reference 30
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Observation f3fc91f8-d063-44f5-a936-c406e46da75c · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset BLIP: Bootstrapping language- image pre-training for unified vision-language understanding and generation
Reference 31
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Observation 6482919f-604b-4732-877d-10ed51c8d8bc · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Ordinal regression by extended binary classification
Reference 32
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Observation a9fe9de4-a93b-44d3-8c5d-1da25cbe8919 · outbound
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Reference 33
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Observation b2d9d653-4984-43c2-9b5e-d940b56c2178 · outbound
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Reference 34
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Observation fe0280de-c759-4176-aace-871854251637 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models
Reference 35
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Observation a8f9fd7c-c5e6-4541-aff0-6861c7c48f53 · outbound
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Reference 36
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Observation 99318978-0529-4e63-aa6d-15e2379e510d · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Improved baselines with visual instruction tuning, 2023
Reference 37
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Observation d04adafd-e419-4e3b-8384-63bd96708557 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Visual instruction tuning
Reference 38
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Observation f05ad454-8b4e-474d-8b1e-1dd97ba32072 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset DeepDRiD: Diabetic retinopathy—grading and image quality estimation challenge
Reference 39
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Observation a51759ff-de48-4db9-8acd-b1465fc88e45 · outbound
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Reference 40
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Reference 41
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Observation 32379c1d-cf7e-42e1-a5a1-db02b10451d9 · outbound
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Reference 42
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Observation f3d060e5-8a46-4f45-aa6c-994af158da1c · outbound
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Reference 43
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Observation 4049f57e-15af-4d21-b845-67b4af4e8ae6 · outbound
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Reference 44
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Observation dbc733e0-8470-4bf6-bec1-56048caec544 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset StraIT: Non-autoregressive Generation with Stratified Image Transformer
Reference 45
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Observation 7e1af7ad-deaa-41ad-aa0c-d9c05000eadd · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Learning transferable visual models from natural language supervision
Reference 46
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Observation 3fe8e758-c5ea-4192-9e92-490f9f1182d8 · outbound
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Reference 47
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Reference 48
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Observation a1a457e0-91e4-48f4-a7b8-0e3d694dfd4b · outbound
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Reference 49
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Observation 40ead950-642b-44f2-98de-764ac4f42131 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Moving window regression: A novel approach to ordinal regression
Reference 50
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Observation 1d3cd1f5-3aaa-496d-909a-079da2fbccb0 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Gemini: A Family of Highly Capable Multimodal Models
Reference 51
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Observation 9cbd0fc9-79b0-4e4f-84db-c627044890c4 · outbound
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Reference 52
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Reference 53
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Observation 29f86852-257e-40d0-9f73-bf1aa80748a5 · outbound
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Reference 54
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Observation 3b8c0aeb-1a16-42fb-97e6-11fe07fa9861 · outbound
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Reference 55
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Observation f506f633-26e2-4ae6-bae8-859db88fab4f · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset VisionLLM: Large language model is also an open-ended decoder for vision-centric tasks
Reference 56
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Observation 1896a52f-be55-47eb-8670-0135fce85bea · outbound
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Reference 57
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Observation e0bbe672-2ec6-4d8e-b133-43e072b6d21b · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Q-Bench: A benchmark for general-purpose foundation models on low-level vision
Reference 58
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Observation d46953ed-94ab-4b7f-9676-3bdd2604202f · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models
Reference 59
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Observation 84741159-a626-41a1-a0a5-87d135d9fb88 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels
Reference 60
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Observation 5473ffa8-f4fe-4703-8b8c-60865f78cf0e · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action
Reference 61
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Observation 7aa4ca83-908f-4536-b33d-39453273bcd2 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
Reference 62
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Observation ffe94371-9feb-4a6e-becc-1e14a431a0cb · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset GPT4RoI: Instruction Tuning Large Language Model on Region-of-Interest
Reference 63
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Observation 564fd652-22a4-4708-b7b7-8a337c2951de · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Age progression/regression by conditional adver- sarial autoencoder
Reference 64
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Observation 83d50c66-a655-4fc1-80d8-e27d84467c49 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models
Reference 65
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Observation b081692f-0a49-4923-9733-6e860d28dc38 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset MoVA: Adapting Mixture of Vision Experts to Multimodal Context
Reference 66
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Unavailable: canonical work link unavailable.
Observation 496e8e50-3964-4823-8868-44b4310db3dd · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
Reference 67
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Observation 1142e179-4943-42af-a3d8-81bc5ea1ca6e · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset (a) Did you state the full set of assumptions of all theoretical results? [NA] (b) Did you include complete proofs of all theoretical results? [NA]
Reference 68
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Observation c42ac8c5-e19b-470d-8ad3-c531492b1ae4 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset for benchmarks)
Reference 69
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Observation 86d22b7b-b7a4-4b70-bc07-c3653a0d7a5f · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
Reference 70
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Observation 23e7e30c-9d78-4db0-b27d-5cbf4195a047 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
Reference 71
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Observation 4604e6fb-c779-4566-9d37-410edb684d02 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
Reference 73
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Observation df9f9520-4d43-4c3d-b6f0-0a8b61caf085 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
Reference 74
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Observation 4b5387d3-9e16-4442-ab5c-103de4c64e3e · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
Reference 75
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Observation f20801d4-b345-4311-8bf3-c24ea2c6424b · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
Reference 76
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Observation 881dc3e8-d910-46e3-a13b-1c21df372d46 · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
Reference 77
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Observation 9d1349cf-50a5-4a9e-81ff-874683d6d11d · outbound
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
Reference 78
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STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
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STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
Reference 80
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STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
Reference 81
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STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
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STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
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STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
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STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
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STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Unresolved cited work
Reference 86
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STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset Answer: [Coarse answer], [Predicted Phase] 11 F Limitations The definitions of labels for different domain tasks are quite diverse
Reference 87
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STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset To conserve GPU memory during fine-tuning, we employ FSDP (Full Shard Data Parallel) with ZeRO3-style
Reference 128
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