Token Cropr: Faster ViTs for Quite a Few Tasks | Paper Citation Record

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This paper cites Quantifying attention flow in transformers.

Token Cropr: Faster ViTs for Quite a Few Tasks Quantifying attention flow in transformers

Reference 1

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Observation ac2b0e88-8398-4bde-91df-2fb0341ccf84 · outbound

This paper cites Beit: Bert pre-training of image transformers.

Token Cropr: Faster ViTs for Quite a Few Tasks Beit: Bert pre-training of image transformers

Reference 2

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Observation 9b2d8924-7e23-4c0e-a081-6a7d6cfb7633 · outbound

This paper cites Iterative patch selection for high-resolution image recognition.

Token Cropr: Faster ViTs for Quite a Few Tasks Iterative patch selection for high-resolution image recognition

Reference 3

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Observation 8f9f6482-6475-4840-b493-90d50aca855f · outbound

This paper cites Flexivit: One model for all patch sizes.

Token Cropr: Faster ViTs for Quite a Few Tasks Flexivit: One model for all patch sizes

Reference 4

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Observation 6c1298c3-5c0c-410a-aadd-c9631bcdd4ec · outbound

This paper cites Soft-nms–improving object detection with one line of code.

Token Cropr: Faster ViTs for Quite a Few Tasks Soft-nms–improving object detection with one line of code

Reference 5

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Observation 1e552867-5617-4c86-b8c3-6586a8ad940f · outbound

This paper cites Token merging: Your vit but faster.

Token Cropr: Faster ViTs for Quite a Few Tasks Token merging: Your vit but faster

Reference 6

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Observation 483fe0dc-27f6-4439-8de4-e6aa87cea660 · outbound

This paper cites Learned thresholds token merging and pruning for vision transformers.

Token Cropr: Faster ViTs for Quite a Few Tasks Learned thresholds token merging and pruning for vision transformers

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:30.098400Z

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Observation d4cd2769-a231-4d4e-b6ad-c20f5b87c7b7 · outbound

This paper cites Cascade r-cnn: High quality object detection and instance segmentation.

Token Cropr: Faster ViTs for Quite a Few Tasks Cascade r-cnn: High quality object detection and instance segmentation

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:30.087796Z

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This paper cites an unresolved cited work.

Token Cropr: Faster ViTs for Quite a Few Tasks Unresolved cited work

Reference 9

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Observation 0133f840-af0b-45df-9a28-263e44ebf3ca · outbound

This paper cites Electra: Pre-training text encoders as discrimina- tors rather than generators.

Token Cropr: Faster ViTs for Quite a Few Tasks Electra: Pre-training text encoders as discrimina- tors rather than generators

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:30.065660Z

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Observation f28c4b64-fae6-4303-a9a7-0e09b25219fe · outbound

This paper cites Cubuk, Barret Zoph, Jonathon Shlens, and Quoc V.

Token Cropr: Faster ViTs for Quite a Few Tasks Cubuk, Barret Zoph, Jonathon Shlens, and Quoc V

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:30.054806Z

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Observation bb69a8b9-984d-4ccb-8a93-f1c150f5acb3 · outbound

This paper cites Flashattention: Fast and memory-efficient exact at- tention with io-awareness.

Token Cropr: Faster ViTs for Quite a Few Tasks Flashattention: Fast and memory-efficient exact at- tention with io-awareness

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:30.043794Z

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This paper cites an unresolved cited work.

Token Cropr: Faster ViTs for Quite a Few Tasks Unresolved cited work

Reference 13

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Observation 593a5395-998c-468c-9e37-deb3d399782d · outbound

This paper cites Scaling vision transformers to 22 billion pa- rameters.

Token Cropr: Faster ViTs for Quite a Few Tasks Scaling vision transformers to 22 billion pa- rameters

Reference 14

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This paper cites Davit: Dual attention vision transform- ers.

Token Cropr: Faster ViTs for Quite a Few Tasks Davit: Dual attention vision transform- ers

Reference 15

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Observation dbea7e9b-3868-43e7-92b9-bd9d9f5c1af2 · outbound

This paper cites Heatvit: Hardware-efficient adaptive token pruning for vision transformers.

Token Cropr: Faster ViTs for Quite a Few Tasks Heatvit: Hardware-efficient adaptive token pruning for vision transformers

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.995586Z

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Observation 289bffad-de76-44c5-af08-0100f154cfba · outbound

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

Token Cropr: Faster ViTs for Quite a Few Tasks An image is worth 16x16 words: Transformers for image recognition at scale

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.983537Z

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Observation 449070e8-6dfe-42c9-87e7-0ba2d58a7380 · outbound

This paper cites Study on den- sity peaks clustering based on k-nearest neighbors and prin- cipal component analysis.

Token Cropr: Faster ViTs for Quite a Few Tasks Study on den- sity peaks clustering based on k-nearest neighbors and prin- cipal component analysis

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.971104Z

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Observation 2075da71-6e2d-476a-af03-26c1066c6a6e · outbound

This paper cites Eva-02: A visual representation for neon genesis.

Token Cropr: Faster ViTs for Quite a Few Tasks Eva-02: A visual representation for neon genesis

Reference 19

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Observation fa341576-ddfd-40cf-bed9-5925bedfa70e · outbound

This paper cites Adaptive token sampling for efficient vision transformers.

Token Cropr: Faster ViTs for Quite a Few Tasks Adaptive token sampling for efficient vision transformers

Reference 20

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Observation 500b5959-4c0b-43be-bed6-24e80089f126 · outbound

This paper cites Simple copy-paste is a strong data augmentation method for instance segmentation.

Token Cropr: Faster ViTs for Quite a Few Tasks Simple copy-paste is a strong data augmentation method for instance segmentation

Reference 21

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Observation a4229bde-91ac-4429-8388-7021bd919a73 · outbound

This paper cites Multi-scale hybrid vision transformer and sinkhorn tokenizer for sewer defect classifi- cation.

Token Cropr: Faster ViTs for Quite a Few Tasks Multi-scale hybrid vision transformer and sinkhorn tokenizer for sewer defect classifi- cation

Reference 22

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Observation d3b3fd6a-5a0e-4b36-8917-3978dcf82ccf · outbound

This paper cites Tay- lor, and Thomas B.

Token Cropr: Faster ViTs for Quite a Few Tasks Tay- lor, and Thomas B

Reference 23

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Observation eaf44a83-cb4a-4a57-8a2b-2493dcc222d5 · outbound

This paper cites Mask r-cnn.

Token Cropr: Faster ViTs for Quite a Few Tasks Mask r-cnn

Reference 24

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Observation de21f02e-5050-4b6a-ac57-6b49cc191235 · outbound

This paper cites Masked autoencoders are scalable vision learners.

Token Cropr: Faster ViTs for Quite a Few Tasks Masked autoencoders are scalable vision learners

Reference 25

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Observation 36eca9f5-3ff8-4741-ae56-9b7c582b7197 · outbound

This paper cites Deep networks with stochastic depth.

Token Cropr: Faster ViTs for Quite a Few Tasks Deep networks with stochastic depth

Reference 26

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Observation c34f38c7-202b-4e82-8084-3bd44e265309 · outbound

This paper cites Mask scoring r-cnn.

Token Cropr: Faster ViTs for Quite a Few Tasks Mask scoring r-cnn

Reference 27

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Observation a26cc3aa-9bde-43f7-a88b-13be7bdd03ba · outbound

This paper cites Perceiver IO: A general architecture for structured inputs & outputs.

Token Cropr: Faster ViTs for Quite a Few Tasks Perceiver IO: A general architecture for structured inputs & outputs

Reference 28

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Observation 0c0ae718-bd0f-4a54-8029-25261ed4b1c3 · outbound

This paper cites Transformers in vision: A survey.ACM Comput.

Token Cropr: Faster ViTs for Quite a Few Tasks Transformers in vision: A survey.ACM Comput

Reference 29

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Observation 38b0889f-80d2-4aa3-98da-0b78269493c4 · outbound

This paper cites Token fusion: Bridging the gap between token pruning and token merging.

Token Cropr: Faster ViTs for Quite a Few Tasks Token fusion: Bridging the gap between token pruning and token merging

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.842162Z

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Observation 1a8732d2-6fdf-417b-9775-3b78ebb6348e · outbound

This paper cites Learned token pruning for transformers.

Token Cropr: Faster ViTs for Quite a Few Tasks Learned token pruning for transformers

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.830272Z

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Observation 7de89099-443d-40dc-8144-cac3b7e1b025 · outbound

This paper cites Spvit: Enabling faster vision transformers via latency-aware soft token pruning.

Token Cropr: Faster ViTs for Quite a Few Tasks Spvit: Enabling faster vision transformers via latency-aware soft token pruning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.819779Z

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Observation 442ce0cd-63da-4a35-8f62-bc667261f2b8 · outbound

This paper cites Fractalnet: Ultra-deep neural networks without residuals.

Token Cropr: Faster ViTs for Quite a Few Tasks Fractalnet: Ultra-deep neural networks without residuals

Reference 33

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Observation 21a8ede4-1fcd-43bf-a761-a55b2b65c425 · outbound

This paper cites SaiT: Sparse Vision Transformers through Adaptive Token Pruning.

Token Cropr: Faster ViTs for Quite a Few Tasks SaiT: Sparse Vision Transformers through Adaptive Token Pruning

Reference 34

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Observation 0f534f50-917d-4b8e-ba0b-01cdf5fe0b5e · outbound

This paper cites Not all patches are what you need: Expediting vision transformers via token reorganizations.

Token Cropr: Faster ViTs for Quite a Few Tasks Not all patches are what you need: Expediting vision transformers via token reorganizations

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.796291Z

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Observation c06f0a6b-7e84-40b1-86a6-9d4c55678de5 · outbound

This paper cites Microsoft coco: Common objects in context.

Token Cropr: Faster ViTs for Quite a Few Tasks Microsoft coco: Common objects in context

Reference 36

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Observation 223f8b28-57f8-4879-85a8-73346e6654b5 · outbound

This paper cites Revisiting token pruning for object detection and instance segmentation.

Token Cropr: Faster ViTs for Quite a Few Tasks Revisiting token pruning for object detection and instance segmentation

Reference 37

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Observation 116f8262-e35d-4c78-b487-54ddbcb0eaed · outbound

This paper cites Dynamic token-pass transformers for semantic segmentation.

Token Cropr: Faster ViTs for Quite a Few Tasks Dynamic token-pass transformers for semantic segmentation

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.764137Z

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Observation f1411864-ca45-4e86-96ef-7cb14526f544 · outbound

This paper cites Beyond attentive tokens: Incorporating to- ken importance and diversity for efficient vision transform- ers.

Token Cropr: Faster ViTs for Quite a Few Tasks Beyond attentive tokens: Incorporating to- ken importance and diversity for efficient vision transform- ers

Reference 39

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Observation 0128f5e8-e8b0-4e14-84f6-ac043a0728dd · outbound

This paper cites SGDR: Stochastic gradi- ent descent with warm restarts.

Token Cropr: Faster ViTs for Quite a Few Tasks SGDR: Stochastic gradi- ent descent with warm restarts

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.741886Z

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Observation 4c7bfa67-ddfb-4524-a0cf-bb8089c20b05 · outbound

This paper cites Decoupled weight decay regularization.

Token Cropr: Faster ViTs for Quite a Few Tasks Decoupled weight decay regularization

Reference 41

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Observation d9b7edd0-ef1c-4464-b7a4-f0d800cd1b25 · outbound

This paper cites Token pooling in vision transformers for image classification.

Token Cropr: Faster ViTs for Quite a Few Tasks Token pooling in vision transformers for image classification

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.719854Z

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Observation 13103a60-fcdb-45c1-b6fc-107b366f2477 · outbound

This paper cites Scaling open-vocabulary object detection.

Token Cropr: Faster ViTs for Quite a Few Tasks Scaling open-vocabulary object detection

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.708714Z

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Observation 0545293a-5c18-4cba-849d-ea6475cded7e · outbound

This paper cites Ia-redˆ2: Interpretability-aware redundancy reduction for vision trans- formers.

Token Cropr: Faster ViTs for Quite a Few Tasks Ia-redˆ2: Interpretability-aware redundancy reduction for vision trans- formers

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.697915Z

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Observation 4badef14-964f-4b54-be3a-ebd3ad85edc0 · outbound

This paper cites BEiT v2: Masked Image Modeling with Vector-Quantized Visual Tokenizers.

Token Cropr: Faster ViTs for Quite a Few Tasks BEiT v2: Masked Image Modeling with Vector-Quantized Visual Tokenizers

Reference 45

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This paper cites Acceleration of stochastic approximation by averaging.

Token Cropr: Faster ViTs for Quite a Few Tasks Acceleration of stochastic approximation by averaging

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.686562Z

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Observation 7873062c-f6c9-460b-a0e8-8170123ab49a · outbound

This paper cites Self-attention Does Not Need $O(n^2)$ Memory.

Token Cropr: Faster ViTs for Quite a Few Tasks Self-attention Does Not Need $O(n^2)$ Memory

Reference 47

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This paper cites Designing network design spaces.

Token Cropr: Faster ViTs for Quite a Few Tasks Designing network design spaces

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.674305Z

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Observation 6d6d1a44-5074-4bbd-8bc0-1a57c8b8825e · outbound

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

Token Cropr: Faster ViTs for Quite a Few Tasks Dynamicvit: Efficient vision transformers with dynamic token sparsification

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.663066Z

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Observation 3b089d5f-1ffe-4125-8d03-3b235bdca257 · outbound

This paper cites Learning to Merge Tokens in Vision Transformers.

Token Cropr: Faster ViTs for Quite a Few Tasks Learning to Merge Tokens in Vision Transformers

Reference 50

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Observation a25ef894-1329-4d47-a376-f4dbf59ddff8 · outbound

This paper cites Berg, and Li Fei-Fei.

Token Cropr: Faster ViTs for Quite a Few Tasks Berg, and Li Fei-Fei

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.651546Z

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Observation 1866e518-596b-42ba-bded-9324e09f77eb · outbound

This paper cites Objects365: A large-scale, high-quality dataset for object detection.

Token Cropr: Faster ViTs for Quite a Few Tasks Objects365: A large-scale, high-quality dataset for object detection

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.640856Z

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Observation f301c24f-6ba4-4f1c-8981-70af69c4fa84 · outbound

This paper cites Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps.

Token Cropr: Faster ViTs for Quite a Few Tasks Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-12T04:54:29.223121Z

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Observation 82625847-094b-4e9d-b2e9-4fe32c34c2ec · outbound

This paper cites Segmenter: Transformer for semantic segmenta- tion.

Token Cropr: Faster ViTs for Quite a Few Tasks Segmenter: Transformer for semantic segmenta- tion

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.629690Z

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Observation c34559cb-fafb-4818-9898-1afac5c573ca · outbound

This paper cites Rethinking the inception ar- chitecture for computer vision.

Token Cropr: Faster ViTs for Quite a Few Tasks Rethinking the inception ar- chitecture for computer vision

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-12T04:54:29.230300Z

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Observation f7a672d2-46a2-4732-a639-17b465cd8d90 · outbound

This paper cites Dynamic token pruning in plain vision transformers for semantic segmentation.

Token Cropr: Faster ViTs for Quite a Few Tasks Dynamic token pruning in plain vision transformers for semantic segmentation

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.611668Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dea3c2e5-f87d-435c-878a-6a0817d587e9 · outbound

This paper cites Patch slimming for ef- 10 ficient vision transformers.

Token Cropr: Faster ViTs for Quite a Few Tasks Patch slimming for ef- 10 ficient vision transformers

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.601183Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1d8997e4-2548-4505-a9a3-b80c91c33e1a · outbound

This paper cites Maxvit: Multi-axis vision transformer.

Token Cropr: Faster ViTs for Quite a Few Tasks Maxvit: Multi-axis vision transformer

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.590471Z

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Observation 6ef01aa5-43eb-4c33-ae67-811b3df07a20 · outbound

This paper cites Learning a parametric embedding by preserving local structure.

Token Cropr: Faster ViTs for Quite a Few Tasks Learning a parametric embedding by preserving local structure

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.579928Z

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Observation 840f9d95-95cc-4bf0-84de-3f3dc50eecf6 · outbound

This paper cites Visualizing data using t-SNE.

Token Cropr: Faster ViTs for Quite a Few Tasks Visualizing data using t-SNE

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.570024Z

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Observation 5362f8dc-dc70-4d09-8145-20e0e3cba399 · outbound

This paper cites Attention is all you need.

Token Cropr: Faster ViTs for Quite a Few Tasks Attention is all you need

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.560209Z

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Observation 3693d487-00b4-4db3-82a2-4b58070642dc · outbound

This paper cites Image as a foreign language: Beit pretraining for vision and vision- language tasks.

Token Cropr: Faster ViTs for Quite a Few Tasks Image as a foreign language: Beit pretraining for vision and vision- language tasks

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.550538Z

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Observation f3cd62c0-8e6f-48a9-ba96-df5e0b743daf · outbound

This paper cites Solo: A simple framework for instance segmen- tation.

Token Cropr: Faster ViTs for Quite a Few Tasks Solo: A simple framework for instance segmen- tation

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.540592Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7cf2e679-f831-4ecc-a3a7-ca644c4d2a11 · outbound

This paper cites Joint token pruning and squeezing towards more ag- gressive compression of vision transformers.

Token Cropr: Faster ViTs for Quite a Few Tasks Joint token pruning and squeezing towards more ag- gressive compression of vision transformers

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.530940Z

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Observation b5215c38-3ab4-43cc-bebe-1a74c0b3a7e7 · outbound

This paper cites Con- vnext v2: Co-designing and scaling convnets with masked autoencoders.

Token Cropr: Faster ViTs for Quite a Few Tasks Con- vnext v2: Co-designing and scaling convnets with masked autoencoders

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.520687Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4be6e88e-c2ea-485e-a06c-28015dfa2272 · outbound

This paper cites PPT: Token Pruning and Pooling for Efficient Vision Transformers.

Token Cropr: Faster ViTs for Quite a Few Tasks PPT: Token Pruning and Pooling for Efficient Vision Transformers

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-12T04:54:29.268860Z

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Observation 8e313385-cd21-480a-a724-901d537b725b · outbound

This paper cites an unresolved cited work.

Token Cropr: Faster ViTs for Quite a Few Tasks Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-12T04:54:29.510634Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 894ad820-6be3-4036-96c3-1e5e1ef0661c · outbound

This paper cites Evo-vit: Slow-fast token evolution for dynamic vision transformer.

Token Cropr: Faster ViTs for Quite a Few Tasks Evo-vit: Slow-fast token evolution for dynamic vision transformer

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.500259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7dcfe7d5-4fc1-4759-ab4f-d861af19727d · outbound

This paper cites A-vit: Adaptive tokens for efficient vision transformer.

Token Cropr: Faster ViTs for Quite a Few Tasks A-vit: Adaptive tokens for efficient vision transformer

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.488989Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e0d70c20-cea8-458b-a52c-2f9c4dbda1b3 · outbound

This paper cites Metaformer baselines for vision.

Token Cropr: Faster ViTs for Quite a Few Tasks Metaformer baselines for vision

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.478623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 90526648-382d-4f66-9cd8-fe5bfbbacffc · outbound

This paper cites Cutmix: Regu- larization strategy to train strong classifiers with localizable features.

Token Cropr: Faster ViTs for Quite a Few Tasks Cutmix: Regu- larization strategy to train strong classifiers with localizable features

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.468275Z

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Observation 623b71ae-27f8-416e-b994-0817326bf328 · outbound

This paper cites Visualizing and understanding convolutional net- works.

Token Cropr: Faster ViTs for Quite a Few Tasks Visualizing and understanding convolutional net- works

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.457244Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5684ad75-416c-4fb6-8bf3-8dfa8c474fa9 · outbound

This paper cites Not all tokens are equal: Human-centric visual analysis via token clustering transformer.

Token Cropr: Faster ViTs for Quite a Few Tasks Not all tokens are equal: Human-centric visual analysis via token clustering transformer

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.445487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8c110580-b31e-4ce0-81e4-a7a71b5efb2e · outbound

This paper cites Scaling vision transformers.

Token Cropr: Faster ViTs for Quite a Few Tasks Scaling vision transformers

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.433971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 33befdaf-3a5d-46ae-b120-3cf5502b7d5f · outbound

This paper cites Dauphin, and David Lopez-Paz.

Token Cropr: Faster ViTs for Quite a Few Tasks Dauphin, and David Lopez-Paz

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.423466Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dd8e9d57-0b2e-4c6d-9cbc-1590fe3de5f8 · outbound

This paper cites Scene parsing through ade20k dataset.

Token Cropr: Faster ViTs for Quite a Few Tasks Scene parsing through ade20k dataset

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.412782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ee3e7098-d0d7-4d99-821b-431feb978997 · outbound

This paper cites Self-slimmed vision trans- former.

Token Cropr: Faster ViTs for Quite a Few Tasks Self-slimmed vision trans- former

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:54:29.400948Z

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