Paper Citation Record · LEDGER

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage

As of 14 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 4 inbound Pith citation observations for arXiv:2412.15484.

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

pith.paper-citation-record.v1
2412.15484 v4

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:26:27.777304Z

measured 64 of 64 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:26:18.843059Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T00:17:29.017556Z

Reference resolution

60 of 60 outbound references displayed

verified exact0
verified fuzzy17
unresolved43
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 13794f31-db06-4959-89af-35ff75a8e765 · outbound

This paper cites GPT-4 Technical Report.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage GPT-4 Technical Report

Reference 1

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Source-reported events for the cited work

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Observation d969e1f0-d713-4961-b08b-cf88a20f6cb0 · outbound

This paper cites Llama 3 model card.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Llama 3 model card

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T11:26:27.611236Z

Source-reported events for the cited work

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Observation e73edd62-b464-4876-a4e2-0ae2301dd801 · outbound

This paper cites and Lavie, A.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage and Lavie, A

Reference 3

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Observation 26711d55-6b4b-4135-adf8-716fb3a0a8b2 · outbound

This paper cites Language Models are Few-Shot Learners.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Language Models are Few-Shot Learners

Reference 4

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Source-reported events for the cited work

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Observation 18c03a80-2577-415f-b5f0-2975e3a93ffc · outbound

This paper cites Clair: Evaluating image captions with large language models.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Clair: Evaluating image captions with large language models

Reference 5

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Observation 55d7c217-ef28-41ea-b2ab-fc8f1e74e81e · outbound

This paper cites Are We on the Right Way for Evaluating Large Vision-Language Models?.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Are We on the Right Way for Evaluating Large Vision-Language Models?

Reference 6

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Source-reported events for the cited work

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Observation 910363c6-ac62-44b9-8f6a-8b69a7030d61 · outbound

This paper cites How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites

Reference 7

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Observation 2713d1f7-686d-4f01-ac45-9abb6baff0f2 · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

Reference 8

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Source-reported events for the cited work

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Observation ec94c0ec-f2ca-4375-a7a2-5a634b673983 · outbound

This paper cites Efficient and Effective Text Encoding for Chinese LLaMA and Alpaca.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Efficient and Effective Text Encoding for Chinese LLaMA and Alpaca

Reference 9

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Source-reported events for the cited work

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Observation aaeeac2e-f225-4aa2-a8d8-c5e28025d2c8 · outbound

This paper cites Instruct BLIP : Towards general-purpose vision-language models with instruction tuning.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Instruct BLIP : Towards general-purpose vision-language models with instruction tuning

Reference 10

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Observation 302ada15-5c9f-4496-a6b7-5971401e8e94 · outbound

This paper cites VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models

Reference 11

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Observation ad362396-15af-4ad9-aa7b-314bf0cd21f2 · outbound

This paper cites ImageInWords: Unlocking Hyper-Detailed Image Descriptions.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage ImageInWords: Unlocking Hyper-Detailed Image Descriptions

Reference 12

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Observation a6caa144-c09d-427e-9444-1adfc074046a · outbound

This paper cites S., Lin, T.-Y., Liu, M.-Y., and Cui, Y.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage S., Lin, T.-Y., Liu, M.-Y., and Cui, Y

Reference 13

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Source-reported events for the cited work

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Observation f6647f82-f181-4143-895e-7fd82a42df78 · outbound

This paper cites Hallusionbench: an advanced diagnostic suite for entangled language hallucination and visual illusion in large vision-language models.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Hallusionbench: an advanced diagnostic suite for entangled language hallucination and visual illusion in large vision-language models

Reference 14

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Observation 329f3145-8682-4acf-abba-751820cf40b8 · outbound

This paper cites Clipscore: A reference-free evaluation metric for image captioning.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Clipscore: A reference-free evaluation metric for image captioning

Reference 15

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Observation ac6c0219-a870-4e5f-88b8-671f20d212ef · outbound

This paper cites Z., Sohel, F., Shiratuddin, M.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Z., Sohel, F., Shiratuddin, M

Reference 16

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Source-reported events for the cited work

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Observation f1558ded-ab1d-432b-8f30-3204fcf561c5 · outbound

This paper cites Opera: Alleviating hallucination in multi-modal large language models via over-trust penalty and retrospection-allocation.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Opera: Alleviating hallucination in multi-modal large language models via over-trust penalty and retrospection-allocation

Reference 17

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Observation 20741046-4c54-4e5e-a3db-757ed355ff83 · outbound

This paper cites F aith S core: Fine-grained evaluations of hallucinations in large vision-language models.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage F aith S core: Fine-grained evaluations of hallucinations in large vision-language models

Reference 18

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Observation 92c03982-9592-4fa0-8566-8fba264fa55d · outbound

This paper cites Visual Attention Never Fades: Selective Progressive Attention ReCalibration for Detailed Image Captioning in Multimodal Large Language Models.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Visual Attention Never Fades: Selective Progressive Attention ReCalibration for Detailed Image Captioning in Multimodal Large Language Models

Reference 19

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Observation 52533384-95f4-4dfa-8860-aa345239dce9 · outbound

This paper cites A diagram is worth a dozen images.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage A diagram is worth a dozen images

Reference 20

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Observation 0aabc5b8-e974-4b39-9c2a-74adb0a9912a · outbound

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage What matters when building vision-language models?

Reference 21

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This paper cites Volcano: Mitigating multimodal hallucination through self-feedback guided revision.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Volcano: Mitigating multimodal hallucination through self-feedback guided revision

Reference 22

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Observation 6d068fd7-f495-4e9e-be4a-5e10c8d9817f · outbound

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Mitigating object hallucinations in large vision-language models through visual contrastive decoding

Reference 23

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This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 24

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Observation d5c38698-9bbe-492e-bf47-c751068b0acb · outbound

This paper cites Evaluating Object Hallucination in Large Vision-Language Models.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Evaluating Object Hallucination in Large Vision-Language Models

Reference 25

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Rouge: A package for automatic evaluation of summaries

Reference 26

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Mitigating hallucination in large multi-modal models via robust instruction tuning

Reference 27

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Observation 48d4fff8-92fd-4cc0-b216-5b506e9ad961 · outbound

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Unresolved cited work

Reference 28

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Unresolved cited work

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 30

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Paying More Attention to Image: A Training-Free Method for Alleviating Hallucination in LVLMs

Reference 31

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage MMBench: Is Your Multi-modal Model an All-around Player?

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Self-refine: Iterative refinement with self-feedback

Reference 35

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage On faithfulness and factuality in abstractive summarization

Reference 36

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage FA ct S core: Fine-grained atomic evaluation of factual precision in long form text generation

Reference 37

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage DOCCI: Descriptions of Connected and Contrasting Images

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Bleu: a method for automatic evaluation of machine translation

Reference 39

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Aloha: A new measure for hallucination in captioning models

Reference 40

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al

Reference 41

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 42

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage A picture is worth more than 77 text tokens: Evaluating clip-style models on dense captions

Reference 43

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Attention is all you need

Reference 44

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Cider: Consensus-based image description evaluation

Reference 45

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Show and tell: A neural image caption generator

Reference 46

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage V., Chi, E

Reference 47

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Observation 5304c74a-5b2b-4eb0-836d-ac3a3730c39f · outbound

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Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Show, attend and tell: Neural image caption generation with visual attention

Reference 48

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This paper cites MiniCPM-V: A GPT-4V Level MLLM on Your Phone.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage MiniCPM-V: A GPT-4V Level MLLM on Your Phone

Reference 49

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This paper cites A Survey on Multimodal Large Language Models.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage A Survey on Multimodal Large Language Models

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This paper cites Woodpecker: Hallucination Correction for Multimodal Large Language Models.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Woodpecker: Hallucination Correction for Multimodal Large Language Models

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This paper cites MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

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This paper cites Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi

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This paper cites When and why vision-language models behave like bags-of-words, and what to do about it? In The Eleventh International Conference on Learning Representations, 2023.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage When and why vision-language models behave like bags-of-words, and what to do about it? In The Eleventh International Conference on Learning Representations, 2023

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This paper cites Enhancing uncertainty-based hallucination detection with stronger focus.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Enhancing uncertainty-based hallucination detection with stronger focus

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:26:27.990593Z

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This paper cites Knowing what llms do not know: A simple yet effective self-detection method.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Knowing what llms do not know: A simple yet effective self-detection method

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:26:27.982195Z

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This paper cites Investigating and mitigating the multimodal hallucination snowballing in large vision-language models.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Investigating and mitigating the multimodal hallucination snowballing in large vision-language models

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:26:27.972116Z

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This paper cites Analyzing and mitigating object hallucination in large vision-language models.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage Analyzing and mitigating object hallucination in large vision-language models

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:26:27.963823Z

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This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

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This paper cites write newline.

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage write newline

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-11T11:26:27.777304Z

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Pith citing papers

Observation 4984a3af-918b-41e9-a7cf-d6276e863dae · inbound

Visual Attention Never Fades: Selective Progressive Attention ReCalibration for Detailed Image Captioning in Multimodal Large Language Models cites this paper.

Visual Attention Never Fades: Selective Progressive Attention ReCalibration for Detailed Image Captioning in Multimodal Large Language Models Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage

Reference 23

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Steer Where It Matters: Token-Level Visual-Sensitivity Steering for LVLMs Hallucination Mitigation cites this paper.

Steer Where It Matters: Token-Level Visual-Sensitivity Steering for LVLMs Hallucination Mitigation Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage

Reference 8

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Observation 1c122c86-07e9-45f2-81ff-a39571f7cca3 · inbound

CapRL++: Unified Reinforcement Learning with Verifiable Rewards for Dense Image and Video Captioning cites this paper.

CapRL++: Unified Reinforcement Learning with Verifiable Rewards for Dense Image and Video Captioning Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage

Reference 32

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CAPEval: A Decoupled Caption Evaluation across Understanding and Generation cites this paper.

CAPEval: A Decoupled Caption Evaluation across Understanding and Generation Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage

Reference 17

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