Paper Citation Record · LEDGER

FoPru: Focal Pruning for Efficient Large Vision-Language Models

As of 15 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 2 inbound Pith citation observations for arXiv:2411.14164.

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

pith.paper-citation-record.v1
2411.14164 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:31:59.644467Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T13:18:01.973663Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T11:28:04.138065Z

Reference resolution

37 of 37 outbound references displayed

verified exact0
verified fuzzy6
unresolved30
parse uncertain1
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation db8227f8-147e-4253-b9ce-cb9b46f1f1a9 · outbound

This paper cites GPT-4 Technical Report.

FoPru: Focal Pruning for Efficient Large Vision-Language Models GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.476631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 872ca09e-972b-405c-b7ec-09fe25eba6e3 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.481892Z

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Observation 45aa0da5-97f5-4cc0-94c2-534a372bfda9 · outbound

This paper cites Qwen-vl: A versatile vision-language model for un- derstanding, localization, text reading, and beyond, 2023.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Qwen-vl: A versatile vision-language model for un- derstanding, localization, text reading, and beyond, 2023

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.487118Z

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Observation c4e0bd32-77d8-4629-8bd3-c51421c48563 · outbound

This paper cites Token Merging: Your ViT But Faster.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Token Merging: Your ViT But Faster

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.491831Z

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Observation 23a606ca-6404-4c92-a4dc-a4d1fca2a2f6 · outbound

This paper cites Vip- llava: Making large multimodal models understand arbitrary visual prompts.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Vip- llava: Making large multimodal models understand arbitrary visual prompts

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:32:00.302317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e0b08df6-00f3-4f40-8c41-b2feb04fa150 · outbound

This paper cites Honeybee: Locality-enhanced projector for multimodal llm.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Honeybee: Locality-enhanced projector for multimodal llm

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:32:00.288629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6eaca42b-0de6-47f9-a1f2-48dec4c38701 · outbound

This paper cites An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language Models.

FoPru: Focal Pruning for Efficient Large Vision-Language Models An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.505542Z

Source-reported events for the cited work

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Observation 2adbd800-f522-440c-bbca-5c1d812a1a88 · outbound

This paper cites MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices.

FoPru: Focal Pruning for Efficient Large Vision-Language Models MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.510689Z

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Observation 4d69ffdc-97d4-425d-b861-3cc5c7a8955b · outbound

This paper cites MobileVLM V2: Faster and Stronger Baseline for Vision Language Model.

FoPru: Focal Pruning for Efficient Large Vision-Language Models MobileVLM V2: Faster and Stronger Baseline for Vision Language Model

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.515164Z

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Observation 62308d71-e63b-4ee7-9331-b78ce6aa90fb · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

FoPru: Focal Pruning for Efficient Large Vision-Language Models An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.519727Z

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Observation c6fcfb3f-b9b0-4c66-958c-fbf697ffeddf · outbound

This paper cites Calibrating Undisciplined Over-Smoothing in Transformer for Weakly Supervised Semantic Segmentation.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Calibrating Undisciplined Over-Smoothing in Transformer for Weakly Supervised Semantic Segmentation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.524484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da4056be-e374-407b-b2b1-c86e417c5ad9 · outbound

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

FoPru: Focal Pruning for Efficient Large Vision-Language Models Gqa: A new dataset for real-world visual reasoning and compositional question answering

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.529257Z

Source-reported events for the cited work

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Observation 6a6798ac-b1bf-48af-8f15-da704e40ccb8 · outbound

This paper cites A diagram is worth a dozen images.

FoPru: Focal Pruning for Efficient Large Vision-Language Models A diagram is worth a dozen images

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.533871Z

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Observation 7b56f0b5-555a-4d44-a954-d69ac04895f4 · outbound

This paper cites Llava-next: Stronger llms supercharge multimodal capa- bilities in the wild, 2024.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Llava-next: Stronger llms supercharge multimodal capa- bilities in the wild, 2024

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:32:00.244395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation debfac4b-95a8-4a29-906f-987e399f8058 · outbound

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

FoPru: Focal Pruning for Efficient Large Vision-Language Models Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.547893Z

Source-reported events for the cited work

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Observation b9df33b0-369c-4531-afcb-3e94984d212a · outbound

This paper cites TokenPacker: Efficient Visual Projector for Multimodal LLM.

FoPru: Focal Pruning for Efficient Large Vision-Language Models TokenPacker: Efficient Visual Projector for Multimodal LLM

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.552458Z

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Observation 28d7c062-e1de-4a34-b6ea-f3b52dcdcca5 · outbound

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

FoPru: Focal Pruning for Efficient Large Vision-Language Models Evaluating Object Hallucination in Large Vision-Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.556790Z

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Observation 579c04ec-67c3-4821-a427-68dd004d9182 · outbound

This paper cites Improved baselines with visual instruction tuning, 2024.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Improved baselines with visual instruction tuning, 2024

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:32:00.221877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8b30e869-b499-425c-a72d-f627a50e1ed3 · outbound

This paper cites Llava-next: Im- proved reasoning, ocr, and world knowledge, 2024.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Llava-next: Im- proved reasoning, ocr, and world knowledge, 2024

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.565487Z

Source-reported events for the cited work

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Observation 08d7fe03-6b23-4d81-8b19-329bb8cef50d · outbound

This paper cites Visual instruction tuning.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Visual instruction tuning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.570078Z

Source-reported events for the cited work

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Observation fa296f04-2fe7-441e-88f7-f56d29bbfa5f · outbound

This paper cites OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models.

FoPru: Focal Pruning for Efficient Large Vision-Language Models OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.574233Z

Source-reported events for the cited work

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Observation 758ccf5c-db25-46e5-b383-f98da0ac6e4f · outbound

This paper cites Learn to explain: Multimodal reasoning via thought chains for science question answering.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Learn to explain: Multimodal reasoning via thought chains for science question answering

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.579416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b32fa945-9439-4ee8-a624-454f1b08a336 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.584282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f19cbb5-f716-4625-9575-a0d478a3977e · outbound

This paper cites Llava-prumerge: Adaptive token reduction for efficient large multimodal models.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Llava-prumerge: Adaptive token reduction for efficient large multimodal models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.588618Z

Source-reported events for the cited work

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Observation 9e6919cc-55a7-426c-90a5-83b0e81fa39e · outbound

This paper cites Towards vqa models that can read.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Towards vqa models that can read

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.592952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13f29409-05bd-4f6f-8156-48011eb7d8af · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Gemini: A Family of Highly Capable Multimodal Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.597350Z

Source-reported events for the cited work

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Observation 9ef5a90c-9652-4ce0-86fa-b511f526d811 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

FoPru: Focal Pruning for Efficient Large Vision-Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.601712Z

Source-reported events for the cited work

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Observation 5ff5cd4d-0220-46b9-8588-730cdad390dd · outbound

This paper cites CogVLM: Visual Expert for Pretrained Language Models.

FoPru: Focal Pruning for Efficient Large Vision-Language Models CogVLM: Visual Expert for Pretrained Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.606386Z

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Observation 4717be79-c53a-4b50-921b-984e1ec7af9e · outbound

This paper cites The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision).

FoPru: Focal Pruning for Efficient Large Vision-Language Models The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.611155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d43c3b93-998c-4912-a1da-37ab5b1d91dd · outbound

This paper cites Dense Connector for MLLMs.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Dense Connector for MLLMs

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.615606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35422bff-9241-458e-b612-0c18351d37c7 · outbound

This paper cites A Survey on Multimodal Large Language Models.

FoPru: Focal Pruning for Efficient Large Vision-Language Models A Survey on Multimodal Large Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.619881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f8fb637-e32f-4b4a-bd4a-03fbd19a2ea8 · outbound

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

FoPru: Focal Pruning for Efficient Large Vision-Language Models Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for ex- pert agi

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:32:00.171833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4cb094ab-17e0-442b-8e41-0cfaedb324df · outbound

This paper cites DocKylin: A Large Multimodal Model for Visual Document Understanding with Efficient Visual Slimming.

FoPru: Focal Pruning for Efficient Large Vision-Language Models DocKylin: A Large Multimodal Model for Visual Document Understanding with Efficient Visual Slimming

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.629310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e86d7296-89d5-4b09-8265-3e093fb1b967 · outbound

This paper cites LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models.

FoPru: Focal Pruning for Efficient Large Vision-Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.634230Z

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Observation 7868158f-73dd-4e55-8e48-45c883b69eb0 · outbound

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

FoPru: Focal Pruning for Efficient Large Vision-Language Models MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:59.639379Z

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Unavailable: canonical work link unavailable.

Observation 33ba7d4a-8565-4683-9490-c9f6db6125b6 · outbound

This paper cites The trend is smoother compared to rank pruning, where accuracy often rises more sharply at lower ratios (e.g., Ocrbench).

FoPru: Focal Pruning for Efficient Large Vision-Language Models The trend is smoother compared to rank pruning, where accuracy often rises more sharply at lower ratios (e.g., Ocrbench)

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:32:00.157804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation dc4be51d-ce40-4950-840d-90e17a451bd3 · outbound

This paper cites an unresolved cited work.

FoPru: Focal Pruning for Efficient Large Vision-Language Models Unresolved cited work

Reference 251

Resolution: parse uncertain; raw_fallback, observed 2026-08-12T15:32:00.258193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

Observation 41ffb6cd-4e62-4975-bb51-ac4ff2dec3bb · inbound

METEOR: Multi-Encoder Collaborative Token Pruning for Efficient Vision Language Models cites this paper.

METEOR: Multi-Encoder Collaborative Token Pruning for Efficient Vision Language Models FoPru: Focal Pruning for Efficient Large Vision-Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T13:18:01.973663Z

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Unavailable: canonical work link unavailable.

Observation b28d75ea-ad84-4120-a553-fbcde58dc1c0 · inbound

Reroute, Don't Remove: Recoverable Visual Token Routing for Vision-Language Models cites this paper.

Reroute, Don't Remove: Recoverable Visual Token Routing for Vision-Language Models FoPru: Focal Pruning for Efficient Large Vision-Language Models

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-07-03T11:28:04.139675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.