Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations | Paper Citation Record

Observation ea32277f-f74c-4b96-8501-641d1f696574 · inbound

freePruner: A Training-free Approach for Large Multimodal Model Acceleration cites this paper.

freePruner: A Training-free Approach for Large Multimodal Model Acceleration Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-12T14:22:07.396842Z

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Observation f40f2a9e-832e-417a-b5ed-3c029dbbfce2 · inbound

Importance-Based Token Merging for Efficient Image and Video Generation cites this paper.

Importance-Based Token Merging for Efficient Image and Video Generation Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-12T14:24:43.505088Z

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Observation 57d6bcf7-97de-47df-af2e-fe5c3a0cbd10 · inbound

Training Noise Token Pruning cites this paper.

Training Noise Token Pruning Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T11:37:55.494689Z

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Observation 37753420-09e9-4d16-b5a4-4b970e057cb1 · inbound

A Stitch in Time Saves Nine: Small VLM is a Precise Guidance for Accelerating Large VLMs cites this paper.

A Stitch in Time Saves Nine: Small VLM is a Precise Guidance for Accelerating Large VLMs Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T22:35:24.251928Z

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Observation 506f0483-8b85-402b-8cbf-aa427a9dc19e · inbound

[CLS] Token Tells Everything Needed for Training-free Efficient MLLMs cites this paper.

[CLS] Token Tells Everything Needed for Training-free Efficient MLLMs Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T20:23:18.586120Z

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Observation d85d81fc-e697-42bd-84a4-8f63983b56d9 · 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 Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T22:20:45.721762Z

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Observation 91915679-b38e-4d0b-8eeb-1c4860918a1d · inbound

MoE$^2$: Optimizing Collaborative Inference for Edge Large Language Models cites this paper.

MoE$^2$: Optimizing Collaborative Inference for Edge Large Language Models Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T20:13:14.582960Z

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Observation 570304b3-610d-413f-90f6-ae1b3a19bfff · inbound

LVPruning: An Effective yet Simple Language-Guided Vision Token Pruning Approach for Multi-modal Large Language Models cites this paper.

LVPruning: An Effective yet Simple Language-Guided Vision Token Pruning Approach for Multi-modal Large Language Models Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T15:50:03.922240Z

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Observation e85b7bc2-e70f-4390-900b-f2e2245e06e0 · inbound

Fast Vision Mamba: Pooling Spatial Dimensions for Accelerated Processing cites this paper.

Fast Vision Mamba: Pooling Spatial Dimensions for Accelerated Processing Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-09T18:28:47.872619Z

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Observation 5e4cb527-517b-4265-9458-47b6e52d121e · inbound

Back to Fundamentals: Low-Level Visual Features Guided Progressive Token Pruning cites this paper.

Back to Fundamentals: Low-Level Visual Features Guided Progressive Token Pruning Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-16T10:37:07.124097Z

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Observation 65787873-357b-40aa-86f2-0de5a299b0ab · inbound

VCM: Vision Concept Modeling Based on Implicit Contrastive Learning with Vision-Language Instruction Fine-Tuning cites this paper.

VCM: Vision Concept Modeling Based on Implicit Contrastive Learning with Vision-Language Instruction Fine-Tuning Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-16T05:53:23.210832Z

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Observation 5ac41ef7-ed8b-4720-a9fe-96c7b757fedd · inbound

Vision Mamba in Remote Sensing: A Comprehensive Survey of Techniques, Applications and Outlook cites this paper.

Vision Mamba in Remote Sensing: A Comprehensive Survey of Techniques, Applications and Outlook Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-16T04:40:07.791930Z

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Observation fa1e6a57-f155-47d0-b020-47e66d4a603b · inbound

STAR: Stage-Wise Attention-Guided Token Reduction for Efficient Large Vision-Language Models Inference cites this paper.

STAR: Stage-Wise Attention-Guided Token Reduction for Efficient Large Vision-Language Models Inference Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:41.737294Z

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Observation 534f4d18-7d34-49ee-85ae-c58f6212dcc6 · inbound

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models cites this paper.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:08:08.089865Z

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Observation e8b292fc-de0a-451e-bd87-69d8a80c2088 · inbound

Sparsified State-Space Models are Efficient Highway Networks cites this paper.

Sparsified State-Space Models are Efficient Highway Networks Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T13:54:45.870665Z

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Observation c122fa6e-153e-4d26-a697-61bf9e76d380 · inbound

One Trajectory, One Token: Grounded Video Tokenization via Panoptic Sub-object Trajectory cites this paper.

One Trajectory, One Token: Grounded Video Tokenization via Panoptic Sub-object Trajectory Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 35

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T12:57:17.898197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fd4a96a3-e744-4317-88b6-1a3852736fd3 · inbound

Towards Storage-Efficient Visual Document Retrieval: An Empirical Study on Reducing Patch-Level Embeddings cites this paper.

Towards Storage-Efficient Visual Document Retrieval: An Empirical Study on Reducing Patch-Level Embeddings Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T10:34:48.952540Z

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Observation 4ea22053-9204-4db7-8171-e2f7f4ebb9c3 · inbound

Token Transforming: A Unified and Training-Free Token Compression Framework for Vision Transformer Acceleration cites this paper.

Token Transforming: A Unified and Training-Free Token Compression Framework for Vision Transformer Acceleration Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T10:29:06.229026Z

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Observation ee770358-a870-48f5-b5e5-9ec070135720 · 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 Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T22:24:28.245119Z

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Observation ba871690-ba73-4293-b9cb-ef2c964ae505 · 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 Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T18:03:01.459589Z

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Observation c5199860-0e89-4d3b-8de7-60e50dee72d5 · inbound

FTCFormer: Fuzzy Token Clustering Transformer for Image Classification cites this paper.

FTCFormer: Fuzzy Token Clustering Transformer for Image Classification Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T17:39:59.361077Z

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Observation 34bbf730-10a7-4fc6-9855-722f268c3662 · inbound

Block-based Symmetric Pruning and Fusion for Efficient Vision Transformers cites this paper.

Block-based Symmetric Pruning and Fusion for Efficient Vision Transformers Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T17:00:14.047818Z

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Observation fa967624-1162-48ec-92f1-0ca80caea4f8 · inbound

Local Representative Token Guided Merging for Text-to-Image Generation cites this paper.

Local Representative Token Guided Merging for Text-to-Image Generation Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T16:41:46.326936Z

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Observation 1f4dc3d8-4237-486d-a913-30bd5eb582de · inbound

Training-free Token Reduction for Vision Mamba cites this paper.

Training-free Token Reduction for Vision Mamba Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T16:16:49.316349Z

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Observation 87a9b2e3-3c2f-46d2-94f8-a85bd043f075 · inbound

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference cites this paper.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T15:19:58.923885Z

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Observation 9e74e16b-7f40-4407-bf36-e6fa0098a6fd · inbound

MixA-Q: Revisiting Activation Sparsity for Vision Transformers from a Mixed-Precision Quantization Perspective cites this paper.

MixA-Q: Revisiting Activation Sparsity for Vision Transformers from a Mixed-Precision Quantization Perspective Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T18:05:12.154637Z

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Observation eea70726-d90f-4818-a205-c5dd4d7668f2 · inbound

Toroidal area-preserving parameterizations of genus-one closed surfaces cites this paper.

Toroidal area-preserving parameterizations of genus-one closed surfaces Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-05T23:36:20.258033Z

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Observation dc572715-ba87-4965-8e26-67d65c612fae · inbound

Enhancing Fairness in Skin Lesion Classification for Medical Diagnosis Using Prune Learning cites this paper.

Enhancing Fairness in Skin Lesion Classification for Medical Diagnosis Using Prune Learning Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:13.602616Z

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Observation e6b405dd-1448-4dad-ab22-f1b0b2fd4fd9 · inbound

Accelerating Vision Transformers with Adaptive Patch Sizes cites this paper.

Accelerating Vision Transformers with Adaptive Patch Sizes Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T05:42:24.467790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9758eb87-7908-442e-a7b7-6fe739988f79 · inbound

CARES: Context-Aware Resolution Selector for VLMs cites this paper.

CARES: Context-Aware Resolution Selector for VLMs Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T08:44:41.395151Z

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Observation 752e0f15-f391-4fd6-9d5c-8d2fe1f74215 · inbound

A Comprehensive Study on Visual Token Redundancy for Discrete Diffusion-based Multimodal Large Language Models cites this paper.

A Comprehensive Study on Visual Token Redundancy for Discrete Diffusion-based Multimodal Large Language Models Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T21:31:34.339829Z

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Observation b91a355f-aa99-4406-8069-57d1bb8f047c · inbound

2K Retrofit: Entropy-Guided Efficient Sparse Refinement for High-Resolution 3D Geometry Prediction cites this paper.

2K Retrofit: Entropy-Guided Efficient Sparse Refinement for High-Resolution 3D Geometry Prediction Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 41

Resolution: unresolved; no resolver link, observed 2026-07-13T21:45:59.210064Z

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Observation 005f7602-7301-46f4-986e-e7d9c21751d8 · inbound

MaMe & MaRe: Matrix-Based Token Merging and Restoration for Efficient Visual Perception and Synthesis cites this paper.

MaMe & MaRe: Matrix-Based Token Merging and Restoration for Efficient Visual Perception and Synthesis Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-10T13:20:26.679364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 93d595dc-3d09-4168-9618-0b45a90d5af8 · inbound

Revisiting Token Compression for Accelerating ViT-based Sparse Multi-View 3D Object Detectors cites this paper.

Revisiting Token Compression for Accelerating ViT-based Sparse Multi-View 3D Object Detectors Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:35:18.948889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fd2aa10d-05d7-4a64-89c9-656b6d240758 · inbound

Why Training-Free Token Reduction Collapses: The Inherent Instability of Pairwise Scoring Signals cites this paper.

Why Training-Free Token Reduction Collapses: The Inherent Instability of Pairwise Scoring Signals Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:02:25.401712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2bec1d64-9656-42c4-98ab-5524bfae3f48 · inbound

Certainty Is Redundant: Token Sparsification for Efficient Camouflaged Object Detection with Vision Foundation Models cites this paper.

Certainty Is Redundant: Token Sparsification for Efficient Camouflaged Object Detection with Vision Foundation Models Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:56:47.595741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 367591f9-21dd-4963-a629-6e72dedd35ce · inbound

VideoRouter: Query-Adaptive Dual Routing for Efficient Long-Video Understanding cites this paper.

VideoRouter: Query-Adaptive Dual Routing for Efficient Long-Video Understanding Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:41:09.898505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b7ecdcd3-1f2e-4305-8bb9-f0cd1b555499 · inbound

VideoRouter: Query-Adaptive Dual Routing for Efficient Long-Video Understanding cites this paper.

VideoRouter: Query-Adaptive Dual Routing for Efficient Long-Video Understanding Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:05:56.508992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 574f26e7-24a0-4026-b00f-1a007c7ad922 · inbound

Provable Sparse Inversion and Token Relabel Enhanced One-shot Federated Learning with ViTs cites this paper.

Provable Sparse Inversion and Token Relabel Enhanced One-shot Federated Learning with ViTs Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 41

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T06:01:23.619747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 13046e92-a3ef-4e03-b096-242cb3ce3270 · inbound

SToRe3D: Sparse Token Relevance in ViTs for Efficient Multi-View 3D Object Detection cites this paper.

SToRe3D: Sparse Token Relevance in ViTs for Efficient Multi-View 3D Object Detection Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T05:19:46.754614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e59b3921-5bb4-44cd-8460-14ac6d3082fa · inbound

CoReDiT: Spatial Coherence-Guided Token Pruning and Reconstruction for Efficient Diffusion Transformers cites this paper.

CoReDiT: Spatial Coherence-Guided Token Pruning and Reconstruction for Efficient Diffusion Transformers Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-15T04:49:44.427609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1fb73584-cfc2-41b2-bafb-f3f7922dfc26 · inbound

Temporal Aware Pruning for Efficient Diffusion-based Video Generation cites this paper.

Temporal Aware Pruning for Efficient Diffusion-based Video Generation Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:13:16.420936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3adeaa16-3b1a-4b44-b845-bee5f3901850 · inbound

Temporal Aware Pruning for Efficient Diffusion-based Video Generation cites this paper.

Temporal Aware Pruning for Efficient Diffusion-based Video Generation Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-22T10:24:47.229230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ed70e5b1-9a6e-4d5d-aaf9-957de1035a65 · inbound

ASAP: Attention Sink Anchored Pruning cites this paper.

ASAP: Attention Sink Anchored Pruning Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-22T08:14:45.578068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c000258d-a7ff-47ae-9c8c-a15336907d71 · inbound

VisionPulse: Dynamic Visual Sparsity for Efficient Multimodal Reasoning cites this paper.

VisionPulse: Dynamic Visual Sparsity for Efficient Multimodal Reasoning Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:12:50.564283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4a7fdeb5-1f9e-4db2-9eab-4b86fdb1bba3 · inbound

See Less, Specify More: Visual Evidence Budgets for Generalizable VLAs cites this paper.

See Less, Specify More: Visual Evidence Budgets for Generalizable VLAs Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-07-01T23:36:23.993353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d4d0482d-06ca-4366-bf7e-ca34fda925f6 · inbound

When Attention Collapses: Stage-Aware Visual Token Pruning from Structure to Semantics cites this paper.

When Attention Collapses: Stage-Aware Visual Token Pruning from Structure to Semantics Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T02:36:26.553035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5ddded6f-8c6f-42f1-99b8-d36db6864dc4 · inbound

ViT-FREE: Efficient Face Recognition via Early Exiting and Synthetic Adaptation cites this paper.

ViT-FREE: Efficient Face Recognition via Early Exiting and Synthetic Adaptation Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-03T10:48:02.340927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3cd9c700-b2f0-4049-b0b9-ca0340c72906 · 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 Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-07-03T11:28:04.143302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6f086724-dd59-4066-8a9e-e557bed72864 · inbound

RegimeVGGT: Layer-Wise Spatially Preserving Redundancy Removal for Visual Geometry Grounded Transformer cites this paper.

RegimeVGGT: Layer-Wise Spatially Preserving Redundancy Removal for Visual Geometry Grounded Transformer Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-03T20:48:56.500170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4aaff8d7-9e24-4700-a912-00dfbf7d7742 · 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 Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-07-04T03:39:29.536795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2622c95b-65e3-487f-a0ba-adea836b4f23 · inbound

TOPS: First-Principles Visual Token Pruning via Constructing Token Optimal Preservation Sets for Efficient MLLM Inference cites this paper.

TOPS: First-Principles Visual Token Pruning via Constructing Token Optimal Preservation Sets for Efficient MLLM Inference Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-07-04T14:09:53.843556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 23c82d59-5379-412a-9c2b-7a4a6d5481b7 · inbound

MVPruner: Dynamic Token Pruning for Accelerating Multi-view Vision-Language Models in Autonomous Driving cites this paper.

MVPruner: Dynamic Token Pruning for Accelerating Multi-view Vision-Language Models in Autonomous Driving Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-06-29T18:23:51.162586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 25b0db98-b7a3-4dc8-879c-1858e7ebbd93 · inbound

MVPruner: Dynamic Token Pruning for Accelerating Multi-view Vision-Language Models in Autonomous Driving cites this paper.

MVPruner: Dynamic Token Pruning for Accelerating Multi-view Vision-Language Models in Autonomous Driving Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:37:24.196752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5d1ec76a-8544-408c-982c-ca6efdde66c4 · inbound

Less Tokens, Better Forecasts: Sparse Residual Routing for Efficient Weather Prediction cites this paper.

Less Tokens, Better Forecasts: Sparse Residual Routing for Efficient Weather Prediction Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-12T06:46:52.331932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4df548e4-465b-4e2d-ae53-08007170b7ce · inbound

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective cites this paper.

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-11T23:58:47.097757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4afd6eb-1b9d-403b-bffd-2efcf65fc499 · inbound

ELSA3D: Elastic Semantic Anchoring for Unified 3D Understanding and Generation cites this paper.

ELSA3D: Elastic Semantic Anchoring for Unified 3D Understanding and Generation Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 64

Resolution: verified exact; local_arxiv, observed 2026-07-08T01:44:26.266232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8a736969-6d7f-457e-936d-76c9fe19ab07 · inbound

Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2 cites this paper.

Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2 Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-01T11:43:15.551554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a02f626-1fca-44ae-bedd-8c23a35f2520 · inbound

DC-Leap: Training-Free Acceleration of dLLMs via Draft-Guided Contiguous Leaping Decoding cites this paper.

DC-Leap: Training-Free Acceleration of dLLMs via Draft-Guided Contiguous Leaping Decoding Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T13:42:25.353013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5070a4e-c3c1-4be8-9a28-ba259dfc7587 · inbound

CRAFT: Compression via Recursive Adaptive Fusion of Video Tokens for Vision-Language Models cites this paper.

CRAFT: Compression via Recursive Adaptive Fusion of Video Tokens for Vision-Language Models Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T23:46:51.538242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9a9699a-cb7b-4588-904f-74544af22fc9 · inbound

Spike-HTR: Spiking Neural Transformer for Handwritten Text Recognition cites this paper.

Spike-HTR: Spiking Neural Transformer for Handwritten Text Recognition Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-04T23:43:53.556103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 775cee6d-21f0-400f-b0e0-ce21db608cea · inbound

GSTEP: Global Spatio-Temporal Density-Driven Visual Token Pruning for Efficient Video Large Language Models cites this paper.

GSTEP: Global Spatio-Temporal Density-Driven Visual Token Pruning for Efficient Video Large Language Models Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:56.388709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63438658-5667-4035-b48c-a3ab1dcdf818 · inbound

CARVE: Cross-Slice Anisotropic Reallocation of Visual Evidence for Efficient 3D Medical Volume Understanding cites this paper.

CARVE: Cross-Slice Anisotropic Reallocation of Visual Evidence for Efficient 3D Medical Volume Understanding Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T14:41:24.493252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation daddbc57-a323-435e-9fb5-7d783b1be326 · inbound

Learning to Predict Middle-Layer Attention in MLLMs for Visual Token Prunin cites this paper.

Learning to Predict Middle-Layer Attention in MLLMs for Visual Token Prunin Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T04:30:14.241516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e144e591-fb6e-45a7-b2aa-11708ba23227 · inbound

Gated Spatial Redundancy Projection for Pathology Transformer Attentions cites this paper.

Gated Spatial Redundancy Projection for Pathology Transformer Attentions Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T00:11:16.239944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa5b4ddb-4ea0-4671-a9ef-2684849bd992 · inbound

Gated Spatial Redundancy Projection for Pathology Transformer Attentions cites this paper.

Gated Spatial Redundancy Projection for Pathology Transformer Attentions Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-14T04:42:11.045058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77136efc-db54-4adf-97ea-dea6e5571303 · inbound

PatchGen: Learning Soft Intra-Image Predictive Subsets for Visual Generalization cites this paper.

PatchGen: Learning Soft Intra-Image Predictive Subsets for Visual Generalization Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 236

Resolution: unresolved; no resolver link, observed 2026-08-15T23:50:02.411396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef6d8008-e34b-4ddc-adeb-5c6602ca7678 · inbound

MergeOver: Post-Training Token Merging for Recursive Vision Transformers cites this paper.

MergeOver: Post-Training Token Merging for Recursive Vision Transformers Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T15:54:53.713205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers