Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation | Paper Citation Record

Observation 1e509b39-0717-4dce-a7b4-5ced0adbec71 · outbound

This paper cites Zerowaste dataset: To- wards deformable object segmentation in cluttered scenes.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Zerowaste dataset: To- wards deformable object segmentation in cluttered scenes

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.746199Z

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Observation 28594f12-b209-49ab-a85a-cfe51ce3f4f5 · outbound

This paper cites Token Merging: Your ViT But Faster.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Token Merging: Your ViT But Faster

Reference 2

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Observation c86c28c2-8ee7-40b4-9a06-65874c14c5fd · outbound

This paper cites The eccentricity effect: Target eccentricity af- fects performance on conjunction searches.Perception & psychophysics, 57:1241–1261, 1995.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation The eccentricity effect: Target eccentricity af- fects performance on conjunction searches.Perception & psychophysics, 57:1241–1261, 1995

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.694667Z

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Observation e2183c98-8fcb-4a6c-bb8d-b4cd06db1fb2 · outbound

This paper cites Pelk: Parameter-efficient large kernel con- vnets with peripheral convolution.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Pelk: Parameter-efficient large kernel con- vnets with peripheral convolution

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.642470Z

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Observation 55063883-09bd-41a8-89dd-fafbd792858a · outbound

This paper cites Diffrate: Differentiable compression rate for efficient vision transformers.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Diffrate: Differentiable compression rate for efficient vision transformers

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.627947Z

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Observation 9b378b04-b665-45ab-af7e-f1ae93f46f5b · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation The cityscapes dataset for semantic urban scene understanding

Reference 6

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Observation 8327ace9-0161-4fb0-914d-af88c483025c · outbound

This paper cites Rescaling egocentric vision: Collection, pipeline and chal- lenges for epic-kitchens-100.International Journal of Com- puter Vision, pages 1–23, 2022.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Rescaling egocentric vision: Collection, pipeline and chal- lenges for epic-kitchens-100.International Journal of Com- puter Vision, pages 1–23, 2022

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.607128Z

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Observation 55363477-3f56-4009-bd58-67cd24293673 · outbound

This paper cites Vision Transformers Need Registers.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Vision Transformers Need Registers

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.719371Z

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Observation eaf99e91-6ff2-42c3-a664-fb632d5f4745 · outbound

This paper cites Epic-kitchens visor benchmark: Video segmenta- tions and object relations.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Epic-kitchens visor benchmark: Video segmenta- tions and object relations

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.593588Z

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Observation 0f531688-f6f3-4537-9755-c3accd759b1f · outbound

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

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Imagenet: A large-scale hierarchical image database

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.580040Z

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Observation 5bd0c6c2-48f7-406f-8e90-cb51c855634a · outbound

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

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.728704Z

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Observation 72ea821b-b086-4d6d-b65a-2f06aad9f9ab · outbound

This paper cites Project Aria: A New Tool for Egocentric Multi-Modal AI Research.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Project Aria: A New Tool for Egocentric Multi-Modal AI Research

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.732463Z

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Observation 2b6c4ab8-f20c-40e8-8e11-08ac62ec1bf0 · outbound

This paper cites Adaptive token sampling for efficient vision transformers.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Adaptive token sampling for efficient vision transformers

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.554245Z

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Observation 21c265b8-1918-4a76-8f95-917f683ff375 · outbound

This paper cites Instance segmen- tation for autonomous log grasping in forestry operations.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Instance segmen- tation for autonomous log grasping in forestry operations

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.515908Z

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Observation 99a98a1c-017e-41cd-a25a-d4f760767f8c · outbound

This paper cites Deep residual learning for image recognition.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Deep residual learning for image recognition

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.463612Z

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Observation 18b36cfc-202c-4303-b830-5c8676a3cd26 · outbound

This paper cites Masked autoencoders are scalable vision learners.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Masked autoencoders are scalable vision learners

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.445343Z

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Observation 73d796ab-7a26-4cb7-a8bc-8af8e40e5868 · outbound

This paper cites Bytes Are All You Need: Transformers Operating Directly On File Bytes.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Bytes Are All You Need: Transformers Operating Directly On File Bytes

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.747349Z

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Observation 40a1255e-c691-4dd0-81b2-330d8e2c0bec · outbound

This paper cites FoveaTer: Foveated Transformer for Image Classification.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation FoveaTer: Foveated Transformer for Image Classification

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.751062Z

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Observation 0fa90366-b06b-4c18-999a-852cc05fc66c · outbound

This paper cites Scaling Laws for Neural Language Models.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Scaling Laws for Neural Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.754450Z

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Observation 8e62f6ee-dc64-4cb4-96a4-a8b2d340878b · outbound

This paper cites Segment any- thing.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Segment any- thing

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.433749Z

Source-reported events for the cited work

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Observation c7db607a-ee3c-4385-8c74-e1c25ba8a50b · outbound

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

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Spvit: Enabling faster vision transformers via latency-aware soft token pruning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.422770Z

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Observation 9ca957d8-7dc4-43bd-9854-dd88108d4785 · outbound

This paper cites GazeGPT: Augmenting Human Capabilities using Gaze-contingent Contextual AI for Smart Eyewear.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation GazeGPT: Augmenting Human Capabilities using Gaze-contingent Contextual AI for Smart Eyewear

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.764359Z

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Observation 590a6293-dc25-4f1d-9958-f665e0569fb0 · outbound

This paper cites Imagenet classification with deep convolutional neural net- works.NeurIPS, 25, 2012.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Imagenet classification with deep convolutional neural net- works.NeurIPS, 25, 2012

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.411540Z

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Observation 63c6b7bf-c21b-49ac-a983-781244081ff1 · outbound

This paper cites Microsoft coco: Common objects in context.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Microsoft coco: Common objects in context

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.771069Z

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Observation 36157df9-59b5-4627-a570-b74ea1f749c3 · outbound

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

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Efficientvit: Memory efficient vision transformer with cascaded group attention

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.390481Z

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Observation 084b4e53-0296-46e9-af71-b67bc7baa978 · outbound

This paper cites Nymeria: A Massive Collection of Multimodal Egocentric Daily Motion in the Wild.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Nymeria: A Massive Collection of Multimodal Egocentric Daily Motion in the Wild

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.777693Z

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Observation 788a1717-40dd-4ee4-8aa0-f37e6cdbb4a8 · outbound

This paper cites Token Pooling in Vision Transformers.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Token Pooling in Vision Transformers

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.781218Z

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Observation a7e9de63-7a8c-483d-a0e1-f877df98dc81 · outbound

This paper cites Adavit: Adaptive vision transformers for efficient image recognition.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Adavit: Adaptive vision transformers for efficient image recognition

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.377985Z

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Observation 4c17ce08-a961-4e2a-b3ca-24f2b5bde1e1 · outbound

This paper cites Peripheral vision transformer.NeurIPS, 35:32097–32111,.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Peripheral vision transformer.NeurIPS, 35:32097–32111,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.365746Z

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Observation f56ad5c0-676c-4893-aac9-98ab94bf32b6 · outbound

This paper cites Finely-grained annotated datasets for image-based plant phenotyping.Pattern recognition letters, 81:80–89, 2016.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Finely-grained annotated datasets for image-based plant phenotyping.Pattern recognition letters, 81:80–89, 2016

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.354346Z

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Observation 1235dc9c-c215-4930-968f-9f7b0e3a0247 · outbound

This paper cites Rgb no more: Minimally- decoded jpeg vision transformers.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Rgb no more: Minimally- decoded jpeg vision transformers

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.341396Z

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Observation cbf95ed2-4d45-4c90-a0bd-b8014a99c4cd · outbound

This paper cites Dynamicvit: Efficient vision transformers with dynamic token sparsification.NeurIPS, 34:13937–13949, 2021.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Dynamicvit: Efficient vision transformers with dynamic token sparsification.NeurIPS, 34:13937–13949, 2021

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.329601Z

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Observation 69d40b15-99d7-4f63-8ae8-d2561eba0191 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation SAM 2: Segment Anything in Images and Videos

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.800874Z

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Observation c65e594d-c154-445b-a67a-def22ddd5241 · outbound

This paper cites Learning to Merge Tokens in Vision Transformers.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Learning to Merge Tokens in Vision Transformers

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.804525Z

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Observation 7ccae9cd-45a8-41a1-a6a8-b6cb26b7a985 · outbound

This paper cites CP-ViT: Cascade Vision Transformer Pruning via Progressive Sparsity Prediction.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation CP-ViT: Cascade Vision Transformer Pruning via Progressive Sparsity Prediction

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.807850Z

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Observation e8f10b38-f447-44eb-968a-3d3eaf864169 · outbound

This paper cites On Efficient Variants of Segment Anything Model: A Survey.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation On Efficient Variants of Segment Anything Model: A Survey

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.811323Z

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Observation d23f2a49-6e4d-41b8-84f9-aba653abed04 · outbound

This paper cites NDD20: A large-scale few-shot dolphin dataset for coarse and fine-grained categorisation.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation NDD20: A large-scale few-shot dolphin dataset for coarse and fine-grained categorisation

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.814417Z

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Observation 43bd1eec-cba5-4ced-a584-1a7f911a7b8d · outbound

This paper cites Neural discrete representation learning.NeurIPS, 30, 2017.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Neural discrete representation learning.NeurIPS, 30, 2017

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.818098Z

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Observation b4ca801e-802b-431c-a17c-b8c84bc54fda · outbound

This paper cites SqueezeSAM: User friendly mobile interactive segmentation.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation SqueezeSAM: User friendly mobile interactive segmentation

Reference 39

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Observation 39280563-a8b6-411a-928b-0b8736568912 · outbound

This paper cites Efficientsam: Leveraged masked image pretraining for efficient segment anything.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Efficientsam: Leveraged masked image pretraining for efficient segment anything

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.309971Z

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Observation 4fb11bf9-fcfe-488a-bb6c-46e94179d6f8 · outbound

This paper cites ElasticTok: Adaptive Tokenization for Image and Video.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation ElasticTok: Adaptive Tokenization for Image and Video

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.828275Z

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Observation d5c30b82-a863-4e20-8dfa-befadddf50fa · outbound

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

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation A-vit: Adaptive tokens for efficient vision transformer

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.299277Z

Source-reported events for the cited work

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Observation 0e845d06-82ed-4ee2-8822-c956a82a55ec · outbound

This paper cites Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.288980Z

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Observation 51258c3e-8c81-49a3-8ae8-791671ac755e · outbound

This paper cites Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.837602Z

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Observation 1406d1ef-0d27-4c18-a42b-e0873baf7cbf · outbound

This paper cites An Image is Worth 32 Tokens for Reconstruction and Generation.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation An Image is Worth 32 Tokens for Reconstruction and Generation

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.840987Z

Source-reported events for the cited work

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Observation c971f6c8-29c5-4407-8401-1fe63677d38d · outbound

This paper cites Faster Segment Anything: Towards Lightweight SAM for Mobile Applications.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Faster Segment Anything: Towards Lightweight SAM for Mobile Applications

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.844273Z

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Observation 09b06f40-1aee-42b8-9c5a-6f73400cc95c · outbound

This paper cites Fine-grained egocentric hand-object segmentation: Dataset, model, and applications.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Fine-grained egocentric hand-object segmentation: Dataset, model, and applications

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.278276Z

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Observation 13e08c05-b92e-4eb8-a142-e51cfd207e2d · outbound

This paper cites Efficientvit-sam: Accelerated segment anything model without performance loss.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Efficientvit-sam: Accelerated segment anything model without performance loss

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.267838Z

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 e57b58ee-d1ee-4a3b-bb66-c6f4e81d541b · outbound

This paper cites Fast Segment Anything.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Fast Segment Anything

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.853152Z

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Observation 7ce1e0d3-1524-42d2-bd27-260cfd55224e · outbound

This paper cites Semantic under- standing of scenes through the ade20k dataset.IJCV, 127: 302–321, 2019.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Semantic under- standing of scenes through the ade20k dataset.IJCV, 127: 302–321, 2019

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.256436Z

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Observation 4f101be8-ea3f-41fc-980f-1c44a8ac2330 · outbound

This paper cites EdgeSAM: Prompt-In-the-Loop Distillation for SAM.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation EdgeSAM: Prompt-In-the-Loop Distillation for SAM

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:23.859111Z

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Observation 9a6763cf-b739-4160-aff5-205b06f3fbe4 · outbound

This paper cites MAE Pre-training We pre-trained our foveated image encoders using MAE pre-training for 500K iterations.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation MAE Pre-training We pre-trained our foveated image encoders using MAE pre-training for 500K iterations

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.246207Z

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Observation ed16bc5d-091d-4f38-bd2f-fd6573629003 · outbound

This paper cites Here we give a more formal definition of the parameterization of such a pattern.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Here we give a more formal definition of the parameterization of such a pattern

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.235663Z

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 47069a74-dd08-4d4f-8a35-60ad7cff6bd0 · outbound

This paper cites We plot the training loss curves in Figure 12.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation We plot the training loss curves in Figure 12

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.223472Z

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 e45f3356-3b77-40e8-bd38-290c2a6498fd · outbound

This paper cites Our foveation patterns exists in a high-dimensional design space, and each new pattern requires its own MAE pre-training.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Our foveation patterns exists in a high-dimensional design space, and each new pattern requires its own MAE pre-training

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.211826Z

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 813448ba-c64e-4019-a5c7-c23e2205b705 · outbound

This paper cites an unresolved cited work.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:24.200458Z

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 399a220f-faf9-4e66-be1f-94a640639ef8 · outbound

This paper cites an unresolved cited work.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:24.190238Z

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 51feced0-379a-438d-ba46-36a366146a89 · outbound

This paper cites in computing FLOP counts for transformer architectures (c.f.

Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation in computing FLOP counts for transformer architectures (c.f

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:24.179128Z

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.

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Reference resolution

Outbound references

Pith citing papers