Paper Citation Record · LEDGER

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding

As of 17 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2508.16974.

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

pith.paper-citation-record.v1
2508.16974 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:12:14.964857Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

29 of 29 outbound references displayed

verified exact0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation be8cb9f3-ad98-430a-bf66-d46eb02392a8 · outbound

This paper cites A survey on large language model (LLM) security and privacy: The good, the bad, and the ugly,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding A survey on large language model (LLM) security and privacy: The good, the bad, and the ugly,

Reference 1

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Source-reported events for the cited work

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Observation a51ea89a-8c4f-441e-908b-1b5e83f29dc3 · outbound

This paper cites Visual in-context learning for large vision-language models,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Visual in-context learning for large vision-language models,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T17:12:14.830658Z

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Observation b619d075-625c-4cb0-8642-dc664a2714c8 · outbound

This paper cites Weak to strong generalization for large language models with multi-capabilities,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Weak to strong generalization for large language models with multi-capabilities,

Reference 3

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Observation 46db9d66-cade-4a98-8e46-00e1158efbf6 · outbound

This paper cites Multimodal event transformer for image-guided story ending generation,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Multimodal event transformer for image-guided story ending generation,

Reference 4

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Observation c1c2bb6f-087c-4301-beaf-cf420bbf57f9 · outbound

This paper cites A comprehensive survey of knowledge-based vision question answering systems: The lifecycle of knowledge in visual reasoning task,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding A comprehensive survey of knowledge-based vision question answering systems: The lifecycle of knowledge in visual reasoning task,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:12:15.431514Z

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Observation 14f131fd-694d-44db-a0b1-e00ca27cfbfa · outbound

This paper cites Culture and hallucinations: overview and future directions,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Culture and hallucinations: overview and future directions,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:12:15.412837Z

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Observation 44b49b13-3a2b-426c-ac1f-ad57371ada57 · outbound

This paper cites Improving Medical Large Vision-Language Models with Abnormal-Aware Feedback.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Improving Medical Large Vision-Language Models with Abnormal-Aware Feedback

Reference 7

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Observation aa513c0e-d795-4ef4-91ad-5bdc1bbde082 · outbound

This paper cites Thread of Thought Unraveling Chaotic Contexts.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Thread of Thought Unraveling Chaotic Contexts

Reference 8

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Observation 01715967-96e1-405d-a024-b5f9419b7606 · outbound

This paper cites Flamingo: a visual language model for few-shot learning,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Flamingo: a visual language model for few-shot learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:12:15.391633Z

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Observation 01ed2a53-977a-4bf1-a1de-374ea9fe16c9 · outbound

This paper cites BLIP-2: bootstrapping language-image pre-training with frozen image encoders and large language models,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding BLIP-2: bootstrapping language-image pre-training with frozen image encoders and large language models,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:12:15.372661Z

Source-reported events for the cited work

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Observation 497e9d34-de45-45ac-b634-cf2d438f6bbc · outbound

This paper cites Minigpt-4: Enhancing vision-language understanding with advanced large language models,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Minigpt-4: Enhancing vision-language understanding with advanced large language models,

Reference 11

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Observation fcb32ac4-8ab4-4e15-855c-ecf7a542b055 · outbound

This paper cites GQA: A new dataset for real- world visual reasoning and compositional question answering,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding GQA: A new dataset for real- world visual reasoning and compositional question answering,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:12:15.344129Z

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Observation 8a1de3c9-cb99-4917-b2a7-786b127b7691 · outbound

This paper cites A-OKVQA: A benchmark for visual question answering using world knowledge,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding A-OKVQA: A benchmark for visual question answering using world knowledge,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:12:15.327589Z

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Observation cfbb57bd-f5e4-4c7a-835a-4f0932060aed · outbound

This paper cites Revisiting referring expression comprehension evaluation in the era of large multimodal models,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Revisiting referring expression comprehension evaluation in the era of large multimodal models,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:12:15.309390Z

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Observation 6e0d7af7-b9de-41ac-abd6-06c3883f30b0 · outbound

This paper cites Debiasing vision-language models for vision tasks: a survey,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Debiasing vision-language models for vision tasks: a survey,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:12:15.290672Z

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Observation b49ffc55-3292-4b8b-a6be-24e1bb4de6a4 · outbound

This paper cites Instructblip: Towards general-purpose vision-language models with instruction tuning,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Instructblip: Towards general-purpose vision-language models with instruction tuning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:12:15.273132Z

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Observation a32ebee4-87de-4849-8d37-88a7dc31ef0e · outbound

This paper cites Towards multimodal in-context learning for vision and language models,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Towards multimodal in-context learning for vision and language models,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:12:15.255867Z

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Observation a79a8265-01f7-4aee-9753-a14e1fb32ded · outbound

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Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding VILA: on pre-training for visual language models,

Reference 18

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Observation 6b522645-74d5-4dcf-8a35-e2b4dfdee998 · outbound

This paper cites MAM: Modular Multi-Agent Framework for Multi-Modal Medical Diagnosis via Role-Specialized Collaboration.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding MAM: Modular Multi-Agent Framework for Multi-Modal Medical Diagnosis via Role-Specialized Collaboration

Reference 19

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Observation 3eb9e849-3925-4efc-9e9c-d4903767f67e · outbound

This paper cites Deciphering cross-modal alignment in large vision-language models with modality integration rate,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Deciphering cross-modal alignment in large vision-language models with modality integration rate,

Reference 20

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Observation c9b93399-892d-4236-8494-030d768cd419 · outbound

This paper cites Quantized prompt for efficient generalization of vision-language models,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Quantized prompt for efficient generalization of vision-language models,

Reference 21

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Observation 9dea9465-5870-4740-82a8-d4f9f4ac9a99 · outbound

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Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding A closer look at the few-shot adaptation of large vision-language models,

Reference 22

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Observation 602b964a-3c95-48ed-a345-2fe974be4eb6 · outbound

This paper cites Analyzing fine-grained alignment and enhancing vision understanding in multimodal language models,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Analyzing fine-grained alignment and enhancing vision understanding in multimodal language models,

Reference 23

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Observation 197454cb-838f-42f4-b2c4-f781031b7724 · outbound

This paper cites Hivg: Hierarchical multimodal fine-grained modulation for visual grounding,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Hivg: Hierarchical multimodal fine-grained modulation for visual grounding,

Reference 24

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Observation 11e6eae3-c70b-4387-9a59-b2b84f91eb5c · outbound

This paper cites Towards grounded visual spatial reasoning in multi-modal vision language models,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Towards grounded visual spatial reasoning in multi-modal vision language models,

Reference 25

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Observation 8e1c078d-fdab-44de-a51a-c01d2ce734c0 · outbound

This paper cites Analyzing and boosting the power of fine-grained visual recognition for multi-modal large language models,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Analyzing and boosting the power of fine-grained visual recognition for multi-modal large language models,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:12:15.118424Z

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Observation 23b79258-c320-4949-80b8-c5131073abe0 · outbound

This paper cites Insectmamba: State space model with adaptive composite features for insect recognition,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Insectmamba: State space model with adaptive composite features for insect recognition,

Reference 27

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This paper cites Towards visual grounding: A survey,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Towards visual grounding: A survey,

Reference 28

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This paper cites Hallucination of multimodal large language models: A survey,.

Hierarchical Contextual Grounding LVLM: Enhancing Fine-Grained Visual-Language Understanding with Robust Grounding Hallucination of multimodal large language models: A survey,

Reference 29

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Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.