Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:01:25.978139Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2505.20236.
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 2026-08-07T14:01:25.978139Z
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
44 of 44 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 577c4f42-b60b-44d0-bc42-e6663dffb170 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Pixtral 12B
Reference 1
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Observation d8bd690b-7249-45e7-9db2-74af12102b38 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Qwen2.5-VL Technical Report
Reference 2
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Observation 368f3ad0-0e61-4f1a-be60-79e97a696b23 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 3
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Observation 46b8f820-b59d-47cc-9e92-8bb0df96f279 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models VoiceBench: Benchmarking LLM-Based Voice Assistants
Reference 4
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Observation 0a8a4407-06e2-42a4-a39d-1c84d66a1c4a · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 5
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Observation c52f5b08-33f5-4921-a7eb-fdd7fb77eefd · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Skywork R1V2: Multimodal Hybrid Reinforcement Learning for Reasoning
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Observation 0584dd42-db82-4da3-bdb9-921479950611 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 7
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Observation 520fad86-b4f8-4cbc-82cd-e83f17e10919 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 8
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Observation 839f82ac-2372-4ace-ae8b-7ca6f029ae5a · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models IsoBench: Benchmarking Multimodal Foundation Models on Isomorphic Representations
Reference 9
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Observation a0186ef2-f6bd-45a8-b24c-b4e3f6cb4faa · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models The Llama 3 Herd of Models
Reference 10
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Observation fbe1f2cb-9467-4b61-be0e-41a1325d5fe6 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 11
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Observation 783aeaef-3f43-4248-90a0-ca1006418410 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 12
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Observation 2bf9ee16-4a31-4cbb-a89b-bbbe64aa3707 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Video-MMMU: Evaluating Knowledge Acquisition from Multi-Discipline Professional Videos
Reference 13
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Observation f7a87000-bebd-4d58-9554-fd88f6ea092e · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Kimi-VL Technical Report
Reference 14
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Unavailable: canonical work link unavailable.
Observation 660bbce5-be51-4d44-8c54-537bd684d169 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation
Reference 15
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Observation d4e6d02b-185a-47c8-b668-a2626a337952 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models LLaVA-OneVision: Easy Visual Task Transfer
Reference 16
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Observation 8db16a5d-58ee-48fd-b298-057a8c3876c4 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 17
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Observation 12de5b99-01a3-4278-83ce-e0e4dd4be166 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Text as Images: Can Multimodal Large Language Models Follow Printed Instructions in Pixels?
Reference 18
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Observation 5fa8cfb7-796a-42b6-932c-c9a508807abb · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Teaching Models to Express Their Uncertainty in Words
Reference 19
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Observation 31ac3cbe-04e4-4174-ae7b-6b35555b57ab · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 20
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Observation 9b1faf96-b556-46f0-a79c-9c9a84189980 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 21
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Observation 421bfe05-7e31-41b5-ad92-4b487724c3f8 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Cross the Gap: Exposing the Intra-modal Misalignment in CLIP via Modality Inversion
Reference 22
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Observation bda0b752-27ba-482c-a26b-fef51d8d9cea · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities
Reference 23
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Observation 784c145e-d28b-486f-8ede-99c514aad554 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Competitive Programming with Large Reasoning Models
Reference 24
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Unavailable: canonical work link unavailable.
Observation 1369b012-4f31-40f6-beb0-002c58439b0d · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models GPT-4o System Card
Reference 25
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Observation 299fdc9e-7526-4e0d-aac4-2a71948a3229 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models OpenAI o1 System Card
Reference 26
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Observation 73f42e94-ba71-46a6-9b1d-6bc050c3a39c · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 27
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Unavailable: canonical work link unavailable.
Observation f0e75ab4-d008-43ec-b0e7-367f2f3232d2 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Vibe-Eval: A hard evaluation suite for measuring progress of multimodal language models
Reference 28
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Unavailable: canonical work link unavailable.
Observation 29f1d055-0c40-4292-bd67-dbf5c2773828 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Skywork R1V: Pioneering Multimodal Reasoning with Chain-of-Thought
Reference 29
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Observation 4c7c4b9e-7866-42ff-b8c3-bd4ba4b8fde3 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 30
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Unavailable: canonical work link unavailable.
Observation 96363283-fa5d-4d18-81af-988b2ada11e7 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 31
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Observation f9d64c17-4280-444f-b441-c7b5b070541e · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 32
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Observation a72a6b96-0e25-4210-bb07-e86db1b9b0f8 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 33
Source-reported events for the cited work
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Observation 65e97d08-87bc-493e-a73f-9e4b9d3f9984 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models VisualSimpleQA: A Benchmark for Decoupled Evaluation of Large Vision-Language Models in Fact-Seeking Question Answering
Reference 34
Source-reported events for the cited work
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Observation 49fca5c3-60ad-4a8b-8911-1f4f555b816d · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs
Reference 35
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Observation 0023d82c-4754-4593-bf77-e98fe5ffe04f · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 36
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Observation 32e8d7ba-05ad-43b1-b1ed-a0a1ee967a4e · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models On Verbalized Confidence Scores for LLMs
Reference 37
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Observation e2430b32-9e4a-421e-8186-4e9ec2ca701e · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark
Reference 38
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Observation e87c8039-d94f-47b3-bd9c-671458260439 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Unresolved cited work
Reference 39
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Observation c62b61a3-1ded-4373-b33f-4ac3ef07d44f · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Object-Level Verbalized Confidence Calibration in Vision-Language Models via Semantic Perturbation
Reference 40
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Observation 38df3b57-ede7-4009-858b-2ca0244844da · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models Instruction-Following Evaluation for Large Language Models
Reference 41
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Observation bbe0ee83-2b7a-4ec4-b01a-5d9eb00677f7 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Reference 42
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Unavailable: canonical work link unavailable.
Observation 634c2005-6315-4346-a502-bac238a50906 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models online" 'onlinestring :=
Reference 43
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Observation deb1b7ee-7405-4a9c-bcc0-52673db637c7 · outbound
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models write newline
Reference 44
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No inbound Pith citation observations are available.