Paper Citation Record · LEDGER

Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2405.05803.

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

pith.paper-citation-record.v1
2405.05803 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:28:37.284569Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3b2d0748-67b0-40b2-8e29-7a8d8f00469a · inbound

FocusLLaVA: A Coarse-to-Fine Approach for Efficient and Effective Visual Token Compression cites this paper.

FocusLLaVA: A Coarse-to-Fine Approach for Efficient and Effective Visual Token Compression Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T15:28:37.284569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a26d361b-458d-46ad-8683-25451e33e88f · inbound

Accelerating Multimodal Large Language Models via Dynamic Visual-Token Exit and the Empirical Findings cites this paper.

Accelerating Multimodal Large Language Models via Dynamic Visual-Token Exit and the Empirical Findings Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T06:04:21.937545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0092223-0a8c-475a-9347-a225787ceb6a · inbound

Accelerating Multimodal Large Language Models by Searching Optimal Vision Token Reduction cites this paper.

Accelerating Multimodal Large Language Models by Searching Optimal Vision Token Reduction Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T05:21:10.859821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e31ec82e-f815-4370-bf47-b7610183a5ff · inbound

MBQ: Modality-Balanced Quantization for Large Vision-Language Models cites this paper.

MBQ: Modality-Balanced Quantization for Large Vision-Language Models Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T00:21:52.233673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1257f398-6e4f-412b-9219-cf04de81e5a9 · inbound

ST$^3$: Accelerating Multimodal Large Language Model by Spatial-Temporal Visual Token Trimming cites this paper.

ST$^3$: Accelerating Multimodal Large Language Model by Spatial-Temporal Visual Token Trimming Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T23:39:18.114263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67ef1458-76b2-41f6-87ca-0c0b71ef2bc8 · inbound

What Kind of Visual Tokens Do We Need? Training-free Visual Token Pruning for Multi-modal Large Language Models from the Perspective of Graph cites this paper.

What Kind of Visual Tokens Do We Need? Training-free Visual Token Pruning for Multi-modal Large Language Models from the Perspective of Graph Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T22:20:45.731407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 533e2edb-6634-435f-a09b-2c7f9bc28248 · inbound

HiMix: Reducing Computational Complexity in Large Vision-Language Models cites this paper.

HiMix: Reducing Computational Complexity in Large Vision-Language Models Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T19:18:49.288803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8904b5bd-f1e7-4be9-8402-952d135fd0e0 · inbound

RedundancyLens: Revealing and Exploiting Visual Token Processing Redundancy for Efficient Decoder-Only MLLMs cites this paper.

RedundancyLens: Revealing and Exploiting Visual Token Processing Redundancy for Efficient Decoder-Only MLLMs Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-09T21:39:21.727495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b00a0740-01fd-48c8-a130-bbcfc683fd6c · inbound

GreedyPrune: Retenting Critical Visual Token Set for Large Vision Language Models cites this paper.

GreedyPrune: Retenting Critical Visual Token Set for Large Vision Language Models Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:53.659544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8c4bba1-5541-4156-9d32-07021750a33a · inbound

LLaVA-Scissor: Token Compression with Semantic Connected Components for Video LLMs cites this paper.

LLaVA-Scissor: Token Compression with Semantic Connected Components for Video LLMs Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T22:24:28.571315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b21d098-658d-4f82-8300-bd55089c689f · inbound

Fast3D: Accelerating 3D Multi-modal Large Language Models for Efficient 3D Scene Understanding cites this paper.

Fast3D: Accelerating 3D Multi-modal Large Language Models for Efficient 3D Scene Understanding Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T18:03:01.514560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdc7355a-a878-48c0-a559-eb2e5a9c13c0 · inbound

Short-LVLM: Compressing and Accelerating Large Vision-Language Models by Pruning Redundant Layers cites this paper.

Short-LVLM: Compressing and Accelerating Large Vision-Language Models by Pruning Redundant Layers Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T10:55:18.205488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d4a8035-c364-4586-ba74-5874fe2d81fa · inbound

Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models cites this paper.

Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T05:51:15.965046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65e85f8d-6a2d-495b-ae7e-823283bcc887 · inbound

IKOD: Mitigating Visual Attention Degradation in Large Vision-Language Models cites this paper.

IKOD: Mitigating Visual Attention Degradation in Large Vision-Language Models Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T04:29:52.320117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be74d94d-1371-41f4-9704-d21c8c7b1298 · inbound

Late-Layer Fusion is Enough: Dual-Path Vision Token Routing for Multimodal Large Language Models under Visual Saturation cites this paper.

Late-Layer Fusion is Enough: Dual-Path Vision Token Routing for Multimodal Large Language Models under Visual Saturation Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-06-27T16:41:03.330850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d8e5c122-354f-4bf7-851f-23d6203502e0 · inbound

SlimVLM: Sensitivity-aware Dynamic Structured Pruning with Adaptive Visual Token Selection for Efficient Vision-Language Models cites this paper.

SlimVLM: Sensitivity-aware Dynamic Structured Pruning with Adaptive Visual Token Selection for Efficient Vision-Language Models Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-05T16:41:28.862652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.