Paper Citation Record · LEDGER

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models

As of 22 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 1 inbound Pith citation observation for arXiv:2507.09514.

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

pith.paper-citation-record.v1
2507.09514 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:59:33.134847Z

measured 69 of 69 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T17:53:38.503877Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:39:29.503341Z

Reference resolution

68 of 68 outbound references displayed

verified exact1
verified fuzzy32
unresolved35
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2aa73c59-da76-4018-a454-3e8dd3d14a3f · outbound

This paper cites Longformer: The Long-Document Transformer.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Longformer: The Long-Document Transformer

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6410f858-8541-4c76-a855-541b9795f512 · outbound

This paper cites and Hoffman, J.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models and Hoffman, J

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:41.196456Z

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 a88e0aa8-519b-4b98-bf40-e34aa64d1b45 · outbound

This paper cites Token Merging: Your ViT But Faster.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Token Merging: Your ViT But Faster

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:26.951484Z

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Observation 52d3b278-420f-4a34-9b57-2f3f801c7199 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Imagenet: A large-scale hierarchical image database

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:27.002807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2afab03-5f70-40e2-b02d-b3c27c761c0b · outbound

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

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:27.074610Z

Source-reported events for the cited work

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Observation 1a3fcd91-ee5e-4387-8f2f-dd76d743ae0a · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models An image is worth 16x16 words: Transformers for image recognition at scale

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:27.138967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5caf2e6c-e0f6-48af-85ba-1ae870cf4804 · outbound

This paper cites v., Williams, C., Winn, J., and Zisserman, A.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models v., Williams, C., Winn, J., and Zisserman, A

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:41.021664Z

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 38fb0b3f-b2e2-431e-b689-46977e2e3ed5 · outbound

This paper cites The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:27.249505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6b31128-d35d-4f4c-912c-daf149455075 · outbound

This paper cites F., Powell, J.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models F., Powell, J

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:27.325173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2766bee-dfda-4ec0-8e6e-814dea7b10cb · outbound

This paper cites Y., Dao, T., Saab, K.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Y., Dao, T., Saab, K

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:40.829544Z

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 50a8a855-03a3-4f48-b24c-a76701f550a0 · outbound

This paper cites Fast r-cnn.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Fast r-cnn

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:40.648414Z

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 c421c463-304e-452d-a508-f95b9844f63e · outbound

This paper cites Rich feature hierarchies for accurate object detection and semantic segmentation.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Rich feature hierarchies for accurate object detection and semantic segmentation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:27.537052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32f2baa7-d3c4-4c64-9bc8-17f608424f54 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:27.541474Z

Source-reported events for the cited work

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Observation 96f5b6d0-0c02-4c0d-9e8b-6c56acbcb6a5 · outbound

This paper cites Hippo: Recurrent memory with optimal polynomial projections.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Hippo: Recurrent memory with optimal polynomial projections

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:40.418981Z

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 7582af97-3f66-4133-92fa-56709ff270b5 · outbound

This paper cites Efficiently modeling long sequences with structured state spaces.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Efficiently modeling long sequences with structured state spaces

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:40.299987Z

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 ceae620d-560c-4eeb-8a5e-53615d343e10 · outbound

This paper cites Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:27.704718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7501206-bd9a-4cb8-9252-ed86fb8293c7 · outbound

This paper cites Deep residual learning for image recognition.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Deep residual learning for image recognition

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:27.823022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7428cfd1-1053-42bd-8429-d4bb882aec39 · outbound

This paper cites Channel pruning for accelerating very deep neural networks.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Channel pruning for accelerating very deep neural networks

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:40.168067Z

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 acd5db23-ac30-45a2-b364-543a7363590d · outbound

This paper cites Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:28.017036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a934d5d2-727c-4aae-afa1-832d5b7e03dc · outbound

This paper cites ZigMa: A DiT-style Zigzag Mamba Diffusion Model.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models ZigMa: A DiT-style Zigzag Mamba Diffusion Model

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:28.140778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00570895-fcdb-4959-b78a-c8aa6a5cbe24 · outbound

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QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Unresolved cited work

Reference 21

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

Observation 5d2a9e4f-76ec-44d3-b05a-808497e0ddb5 · outbound

This paper cites an unresolved cited work.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:59:39.717224Z

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 ac8fe3f0-ba52-40c6-91ef-433c42176d82 · outbound

This paper cites Crafting papers on machine learning.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Crafting papers on machine learning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:39.539437Z

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 60822566-733f-4ed1-a18d-e001d36f399d · outbound

This paper cites Optimal Brain Damage.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Optimal Brain Damage

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:39.348580Z

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 cc844d1a-1a2f-4e1b-be87-acc900edb4b3 · outbound

This paper cites Pruning Filters for Efficient ConvNets.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Pruning Filters for Efficient ConvNets

Reference 25

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Source-reported events for the cited work

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Observation 421ad7d2-17c9-475e-b20f-1894381d7cff · outbound

This paper cites VideoMamba: State Space Model for Efficient Video Understanding.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models VideoMamba: State Space Model for Efficient Video Understanding

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:28.795259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92f8753a-0555-4af1-b861-ad250c5eb7b0 · outbound

This paper cites Videomamba: State space model for efficient video understanding.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Videomamba: State space model for efficient video understanding

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:39.104894Z

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 7f828e15-3224-43f1-a56f-368b18786e9c · outbound

This paper cites Supervised masked knowledge distillation for few-shot transformers.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Supervised masked knowledge distillation for few-shot transformers

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:38.891164Z

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 31940c1b-6656-4199-bdc4-fe8bbfa7604d · outbound

This paper cites Hrank: Filter pruning using high-rank feature map.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Hrank: Filter pruning using high-rank feature map

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:38.677423Z

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 915de67a-f83b-483f-b78d-610083b4c6dd · outbound

This paper cites FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:29.255532Z

Source-reported events for the cited work

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Observation 9aaa47ca-014f-459d-aeeb-4df93450d29f · outbound

This paper cites Efficientvit: Memory efficient vision transformer with cascaded group attention.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Efficientvit: Memory efficient vision transformer with cascaded group attention

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:38.455301Z

Source-reported events for the cited work

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Observation 20de0ecf-ae59-4f6e-8714-f21244bb6669 · outbound

This paper cites VMamba: Visual State Space Model.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models VMamba: Visual State Space Model

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:29.412939Z

Source-reported events for the cited work

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Observation c46be122-0db1-451d-a448-03b77610843f · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Swin transformer: Hierarchical vision transformer using shifted windows

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:38.278509Z

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 f93b555c-0812-4d5f-9834-9850e9d013a7 · outbound

This paper cites Post-training quantization for vision transformer.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Post-training quantization for vision transformer

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:37.942952Z

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 510f641a-0baf-489d-93fd-96553665c81c · outbound

This paper cites Swin transformer v2: Scaling up capacity and resolution.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Swin transformer v2: Scaling up capacity and resolution

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:37.651505Z

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 1bc66269-5c2d-441a-bc71-2443ec0612e7 · outbound

This paper cites U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:29.982476Z

Source-reported events for the cited work

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Observation 473e7b50-e1b0-40f6-8034-e6c0112c05e7 · outbound

This paper cites S4nd: Modeling images and videos as multidimensional signals with state spaces.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models S4nd: Modeling images and videos as multidimensional signals with state spaces

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:37.409905Z

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 a2950387-485f-4054-be2f-61e641763b91 · outbound

This paper cites EfficientVMamba: Atrous Selective Scan for Light Weight Visual Mamba.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models EfficientVMamba: Atrous Selective Scan for Light Weight Visual Mamba

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:30.230457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44eb437b-d4d0-48d5-be09-a7fb2cb45344 · outbound

This paper cites K., et al.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models K., et al

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:37.211355Z

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 f48dd64e-d856-48d2-a132-90c248b4b618 · outbound

This paper cites Dynamicvit: Efficient vision transformers with dynamic token sparsification.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Dynamicvit: Efficient vision transformers with dynamic token sparsification

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:30.474574Z

Source-reported events for the cited work

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Observation 520eccca-66ab-402a-8fc2-c6bf79d813e1 · outbound

This paper cites Dynamic Spatial Sparsification for Efficient Vision Transformers and Convolutional Neural Networks.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Dynamic Spatial Sparsification for Efficient Vision Transformers and Convolutional Neural Networks

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:59:33.360101Z

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 d1ab60f6-4382-4b1e-96df-78ce439aa45a · outbound

This paper cites You only look once: Unified, real-time object detection.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models You only look once: Unified, real-time object detection

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:36.970522Z

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 35416c50-b71d-485e-b21b-c758605a4123 · outbound

This paper cites an unresolved cited work.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Unresolved cited work

Reference 43

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:59:36.818992Z

Source-reported events for the cited work

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Observation ee770119-5eb2-4921-8e8a-d29486685686 · outbound

This paper cites Faster Vision Mamba is Rebuilt in Minutes via Merged Token Re-training.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Faster Vision Mamba is Rebuilt in Minutes via Merged Token Re-training

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:30.946262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f777d99c-fcb4-404f-a003-8a2b80b77fbe · outbound

This paper cites and Zisserman, A.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models and Zisserman, A

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:36.660312Z

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 1b719dc9-3e26-41e0-9011-84f273779f17 · outbound

This paper cites T., Warrington, A., and Linderman, S.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models T., Warrington, A., and Linderman, S

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:36.408124Z

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 34478a53-a716-4ac1-aa0f-2ab2d0f515a3 · outbound

This paper cites Patch slimming for efficient vision transformers.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Patch slimming for efficient vision transformers

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:36.177084Z

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 972f78ea-74f6-40a4-9353-4342ae3fcced · outbound

This paper cites Vmrnn: Integrating vision mamba and lstm for efficient and accurate spatiotemporal forecasting.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Vmrnn: Integrating vision mamba and lstm for efficient and accurate spatiotemporal forecasting

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:35.889111Z

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 0219d8c5-b9ed-4e13-9623-316f062cdec8 · outbound

This paper cites DiM: Diffusion Mamba for Efficient High-Resolution Image Synthesis.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models DiM: Diffusion Mamba for Efficient High-Resolution Image Synthesis

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:31.491654Z

Source-reported events for the cited work

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Observation 54f006d9-7526-49de-aa5a-643720a4868b · outbound

This paper cites Training data-efficient image transformers & distillation through attention.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Training data-efficient image transformers & distillation through attention

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:35.712506Z

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 2c32fe0e-74b2-4939-bd58-1ab7510a6626 · outbound

This paper cites Linformer: Self-Attention with Linear Complexity.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Linformer: Self-Attention with Linear Complexity

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:31.618240Z

Source-reported events for the cited work

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Observation 80d0eb42-1e52-4ddf-9eb4-3c3e41c7e9fb · outbound

This paper cites Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:31.707399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a410d545-86d3-476c-9a16-631b8ef30530 · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:31.765024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7567e3a-c51c-4aca-94ff-18800bf341a7 · outbound

This paper cites ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 54

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f15e8afc-e611-45e5-8ccf-4abff36fb131 · outbound

This paper cites Unified perceptual parsing for scene understanding.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Unified perceptual parsing for scene understanding

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:35.441021Z

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 09a9fc2b-968d-46a6-a88a-7ccd7f594640 · outbound

This paper cites Segmamba: Long-range sequential modeling mamba for 3d medical image segmentation.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Segmamba: Long-range sequential modeling mamba for 3d medical image segmentation

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:35.225825Z

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 21cac31f-37f8-4ae2-865a-c501daf71bfe · outbound

This paper cites an unresolved cited work.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:59:34.910491Z

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 98659115-7d99-4dc9-bb4a-dd1042292961 · outbound

This paper cites Medmnist classification decathlon: A lightweight automl benchmark for medical image analysis.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Medmnist classification decathlon: A lightweight automl benchmark for medical image analysis

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:34.697095Z

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 6df773b8-afa3-4882-882e-121986279cce · outbound

This paper cites Medmnist v2-a large-scale lightweight benchmark for 2d and 3d biomedical image classification.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Medmnist v2-a large-scale lightweight benchmark for 2d and 3d biomedical image classification

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:34.321676Z

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 ab366496-5db8-4675-bec0-fd9bfd0b685b · outbound

This paper cites AdaViT: Adaptive Tokens for Efficient Vision Transformer.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models AdaViT: Adaptive Tokens for Efficient Vision Transformer

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:32.445461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08aeac04-2662-4e5a-8cf3-091326a8660b · outbound

This paper cites I., Han, X., Gao, M., Lin, C.-Y., and Davis, L.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models I., Han, X., Gao, M., Lin, C.-Y., and Davis, L

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:34.124830Z

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 4c3dad39-6b4a-4e6c-85d1-c4b5cb648176 · outbound

This paper cites MedMamba: Vision Mamba for Medical Image Classification.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models MedMamba: Vision Mamba for Medical Image Classification

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:32.688931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5792f12-1ed1-4810-9a0d-fd56e6c81e97 · outbound

This paper cites Exploring Token Pruning in Vision State Space Models.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Exploring Token Pruning in Vision State Space Models

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:32.755285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d0705c8-49a3-4dec-a889-bf80301af547 · outbound

This paper cites Scene parsing through ade20k dataset.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Scene parsing through ade20k dataset

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:33.956026Z

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 460c3563-e59a-4c01-95b1-19668d2111d8 · outbound

This paper cites Vision mamba: Efficient visual representation learning with bidirectional state space model.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Vision mamba: Efficient visual representation learning with bidirectional state space model

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:33.822025Z

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 89b80900-9961-43bc-bdf6-4d85d5cf9259 · outbound

This paper cites Vision Transformer Pruning.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Vision Transformer Pruning

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:32.981542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28ddd627-74d3-42be-b02c-1316a803741f · outbound

This paper cites Discrimination-aware channel pruning for deep neural networks.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models Discrimination-aware channel pruning for deep neural networks

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:59:33.644190Z

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 0ef91300-b866-4778-b562-d7c57d039093 · outbound

This paper cites write newline.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models write newline

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:33.134847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 11caece9-f833-4485-a219-df364e35db4c · inbound

Spatial-Aware Reduction Framework: Towards Efficient and Faithful Visual State Space Models cites this paper.

Spatial-Aware Reduction Framework: Towards Efficient and Faithful Visual State Space Models QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models

Reference 93

Resolution: verified exact; arxiv_id, observed 2026-07-04T03:39:29.505186Z

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.