Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:52:49.988237Z
Paper Citation Record · LEDGER
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost
As of 16 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2506.01304.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
61 of 61 outbound references displayed
- verified exact1
- verified fuzzy33
- unresolved26
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 11a488a3-9d79-45bd-84bf-3beb1059ecc5 · outbound
This paper cites Xmem++: Production-level video segmenta- tion from few annotated frames.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Xmem++: Production-level video segmenta- tion from few annotated frames
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.738085Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 366b346b-2fb1-42a3-9b20-82c3210325bf · outbound
This paper cites One- shot video object segmentation.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost One- shot video object segmentation
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.726052Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 11561c84-e797-4fbf-950d-36de8a62d960 · outbound
This paper cites Rsprompter: Learning to prompt for remote sensing instance segmenta- tion based on visual foundation model.IEEE Transactions on Geoscience and Remote Sensing, 2024.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Rsprompter: Learning to prompt for remote sensing instance segmenta- tion based on visual foundation model.IEEE Transactions on Geoscience and Remote Sensing, 2024
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.714060Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ba02cf08-f5f4-4072-95c3-ddd96b478355 · outbound
This paper cites Adaptformer: Adapting vision transformers for scalable visual recognition.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Adaptformer: Adapting vision transformers for scalable visual recognition
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.703563Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4a334688-76cb-41b5-8674-3a3d106dde9e · outbound
This paper cites SAM2-Adapter: Evaluating & Adapting Segment Anything 2 in Downstream Tasks: Camouflage, Shadow, Medical Image Segmentation, and More.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost SAM2-Adapter: Evaluating & Adapting Segment Anything 2 in Downstream Tasks: Camouflage, Shadow, Medical Image Segmentation, and More
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:38.439660Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation db998cdb-5490-40f5-97fe-37adf7115483 · outbound
This paper cites 0.1% data makes segment anything slim.NeurIPS,.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost 0.1% data makes segment anything slim.NeurIPS,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.692814Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4c34bce8-2e12-47db-abee-d3958b50182d · outbound
This paper cites Xmem: Long- term video object segmentation with an atkinson-shiffrin memory model.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Xmem: Long- term video object segmentation with an atkinson-shiffrin memory model
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.682205Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4e577a05-e56e-4644-8cdd-8399b2e354d6 · outbound
This paper cites Modular interactive video object segmentation: Interaction-to-mask, propagation and difference-aware fusion.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Modular interactive video object segmentation: Interaction-to-mask, propagation and difference-aware fusion
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.669131Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7e4ddc88-dcfd-4521-8ca4-3f5f80beee02 · outbound
This paper cites Rethink- ing space-time networks with improved memory coverage for efficient video object segmentation.NeurIPS, 2021.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Rethink- ing space-time networks with improved memory coverage for efficient video object segmentation.NeurIPS, 2021
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.656205Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f07074bf-67a3-4cd5-8cd0-9247113ec8ae · outbound
This paper cites Tracking anything with de- coupled video segmentation.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Tracking anything with de- coupled video segmentation
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:38.821648Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 68e2cdb2-f115-42c5-b0f3-2c108187e7a2 · outbound
This paper cites Putting the object back into video object segmentation.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Putting the object back into video object segmentation
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.636635Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9b1cc4fd-526c-497a-b21e-a3484ac88c49 · outbound
This paper cites Segment and Track Anything.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Segment and Track Anything
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:38.984260Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a33b334d-66b1-4181-a184-740ff8cbc34e · outbound
This paper cites ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:39.082937Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 409ef4a8-5aeb-4347-a106-dceda66c567b · outbound
This paper cites Learning the what and how of annotation in video object segmentation.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Learning the what and how of annotation in video object segmentation
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.625812Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 35c29cac-6a12-481e-84a0-ac4ac2ca8add · outbound
This paper cites Segment anything model 2: an application to 2D and 3D medical images.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Segment anything model 2: an application to 2D and 3D medical images
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:39.281260Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 642f041d-7bee-48c2-94c4-6b3bac3f550a · outbound
This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:39.420425Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8c099b13-52de-4c6f-820c-5c523858aadf · outbound
This paper cites Interactive video object segmentation using global and local transfer modules.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Interactive video object segmentation using global and local transfer modules
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.615372Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 58d1537e-41f7-47b0-a316-1aeda0409a70 · outbound
This paper cites A Neuromorphic Dataset for Object Segmentation in Indoor Cluttered Environment.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost A Neuromorphic Dataset for Object Segmentation in Indoor Cluttered Environment
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T11:52:50.520855Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d6944856-87ef-495f-a04c-90eb2ac2d4c0 · outbound
This paper cites Prompting visual-language models for efficient video understanding.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Prompting visual-language models for efficient video understanding
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.604426Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3c3594b6-e9d5-4f84-86ef-35f0455f93e5 · outbound
This paper cites Segment anything in high qual- ity.NeurIPS, 2023.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Segment anything in high qual- ity.NeurIPS, 2023
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.593770Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 50853442-a2d1-4ad6-8d6a-4f62cb46ffe0 · outbound
This paper cites Segment any- thing.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Segment any- thing
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.584383Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 06580f31-8f5e-41a2-a50f-92f1890d0de8 · outbound
This paper cites Frozen clip models are efficient video learners.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Frozen clip models are efficient video learners
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.574762Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3d97282a-0322-42fa-a8d3-8595e413b810 · outbound
This paper cites Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:44.860444Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a27319da-c951-430b-95ce-aa2214fc1cdd · outbound
This paper cites Decoupled Weight Decay Regularization.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Decoupled Weight Decay Regularization
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:45.975938Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 46538667-b3ba-4a45-9504-1aea96602a29 · outbound
This paper cites Segment anything in medical images.Nature Communications, 2024.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Segment anything in medical images.Nature Communications, 2024
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.562809Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 296753c5-d4e9-4a3e-9d0c-e1f19ce65fb1 · outbound
This paper cites Video object segmentation without temporal information.IEEE TPAMI, 2018.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Video object segmentation without temporal information.IEEE TPAMI, 2018
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.545539Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 97ffd79f-007d-4c78-84ff-5e994a6b19fc · outbound
This paper cites Segment anything model for medical image analysis: an experimental study.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Segment anything model for medical image analysis: an experimental study
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.517771Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation cf47f950-2c8b-4f84-9960-b8b403de068f · outbound
This paper cites Fast video object segmentation by reference- guided mask propagation.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Fast video object segmentation by reference- guided mask propagation
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.363558Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ade024f6-0491-46a6-86ce-d70d8e35fd4f · outbound
This paper cites St-adapter: Parameter-efficient image-to-video transfer learning.NeurIPS, 2022.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost St-adapter: Parameter-efficient image-to-video transfer learning.NeurIPS, 2022
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.187973Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation fce007a0-bd8a-485a-9603-4ae670e231c8 · outbound
This paper cites Dual- path adaptation from image to video transformers.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Dual- path adaptation from image to video transformers
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:53.020964Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1c66845a-b417-4fe3-be90-b52433a7d20f · outbound
This paper cites Pytorch: An imperative style, high-performance deep learning library.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Pytorch: An imperative style, high-performance deep learning library
Reference 31
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 54246d1f-937a-4143-8f44-ca248c0a50a6 · outbound
This paper cites The 2017 DAVIS Challenge on Video Object Segmentation.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost The 2017 DAVIS Challenge on Video Object Segmentation
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:47.338977Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ba348c6-d502-4d91-869a-c166418a4c9c · outbound
This paper cites Disentangling spatial and temporal learning for efficient image-to-video transfer learning.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Disentangling spatial and temporal learning for efficient image-to-video transfer learning
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:52.962159Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4cdc9513-ab3e-4027-a34e-7f0167211ff8 · outbound
This paper cites Learn- ing transferable visual models from natural language super- vision.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Learn- ing transferable visual models from natural language super- vision
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:47.507661Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 54567cfc-c79c-4116-b667-2137cf7a270a · outbound
This paper cites Segment Anything Meets Point Tracking.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Segment Anything Meets Point Tracking
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:47.613125Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 32d05b03-b271-4e21-ad9f-ba434b00d35e · outbound
This paper cites SAM 2: Segment Anything in Images and Videos.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost SAM 2: Segment Anything in Images and Videos
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:47.689544Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b46505a9-ab4f-4412-a50f-b4457b8763be · outbound
This paper cites Seg- ment anything, from space? InWACV, 2024.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Seg- ment anything, from space? InWACV, 2024
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:52.634283Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d2d55a5b-8207-4979-97ea-d2284c541ef0 · outbound
This paper cites Learning fast and robust target models for video object segmentation.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Learning fast and robust target models for video object segmentation
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:52.441859Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6367c98a-127d-4bb1-8f02-dc5c67f8f2ba · outbound
This paper cites Interactive 3D Medical Image Segmentation with SAM 2.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Interactive 3D Medical Image Segmentation with SAM 2
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:48.066282Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0af786a1-4ab5-4cc8-94af-fd5a658cad6c · outbound
This paper cites TinySAM: Pushing the Envelope for Efficient Segment Anything Model.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost TinySAM: Pushing the Envelope for Efficient Segment Anything Model
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:48.139202Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 145770c0-a7d4-449f-ad6e-75da32188b50 · outbound
This paper cites Towards open-vocabulary video instance segmentation.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Towards open-vocabulary video instance segmentation
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:52.416992Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a28ac603-12cc-45d1-b433-35d72d35297e · outbound
This paper cites F3net: Fu- sion, feedback and focus for salient object detection.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost F3net: Fu- sion, feedback and focus for salient object detection
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:52.133490Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8fa47d21-827d-415a-8d7b-019097e79d86 · outbound
This paper cites Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:48.476606Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f66ab37f-aead-4a37-b22e-914904281cd9 · outbound
This paper cites Scalable video object segmentation with simplified frame- work.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Scalable video object segmentation with simplified frame- work
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:51.963083Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3cf8432a-bead-4b98-9543-340adc1bda27 · outbound
This paper cites Cat-sam: Con- ditional tuning for few-shot adaptation of segment anything model.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Cat-sam: Con- ditional tuning for few-shot adaptation of segment anything model
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:51.886849Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2d21e214-7128-4169-94a9-69c759c75ee2 · outbound
This paper cites Sam2-unet: Segment anything 2 makes strong encoder for natural and medical image segmentation.arXiv:2408.08870,.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Sam2-unet: Segment anything 2 makes strong encoder for natural and medical image segmentation.arXiv:2408.08870,
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:48.758340Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f6ec5bef-6694-4bca-b495-7d1b0097f919 · outbound
This paper cites Efficientsam: Leveraged masked image pretraining for efficient segment anything.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Efficientsam: Leveraged masked image pretraining for efficient segment anything
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:51.871711Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 66dd7019-f941-415a-b79a-1d07b6480998 · outbound
This paper cites Youtube-vos: Sequence-to-sequence video object segmentation.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Youtube-vos: Sequence-to-sequence video object segmentation
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:51.629829Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9ac3aeba-a833-4a41-8e9e-70ccdfed6daa · outbound
This paper cites Track Anything: Segment Anything Meets Videos.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Track Anything: Segment Anything Meets Videos
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:49.056362Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 960e79a4-35db-4e07-83ec-aca882a801dc · outbound
This paper cites Efficient video object segmen- tation via network modulation.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Efficient video object segmen- tation via network modulation
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:51.325468Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 71beb037-fafc-43c3-8e60-8a94f15c8c43 · outbound
This paper cites AIM: Adapting image models for efficient video action recognition.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost AIM: Adapting image models for efficient video action recognition
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:51.156717Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 907785b0-b6af-41a1-98b3-a28ef3db9675 · outbound
This paper cites Collaborative video object segmentation by foreground-background inte- gration.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Collaborative video object segmentation by foreground-background inte- gration
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:51.066669Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5404a6f2-5757-4575-aca4-3a46ccf51623 · outbound
This paper cites Faster Segment Anything: Towards Lightweight SAM for Mobile Applications.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Faster Segment Anything: Towards Lightweight SAM for Mobile Applications
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:49.455141Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b14219f4-0ea2-41f4-8266-4983cc0e55d0 · outbound
This paper cites MobileSAMv2: Faster Segment Anything to Everything.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost MobileSAMv2: Faster Segment Anything to Everything
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:49.547609Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2ee8bb8f-c9f7-4a37-b36b-eaaa7dc82e06 · outbound
This paper cites Joint Modeling of Feature, Correspondence, and a Compressed Memory for Video Object Segmentation.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Joint Modeling of Feature, Correspondence, and a Compressed Memory for Video Object Segmentation
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:49.642417Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a027915a-2f96-4f65-8176-e2d4128ae780 · outbound
This paper cites Fast Segment Anything.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Fast Segment Anything
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:49.758396Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 19b37adb-16b0-4d3f-ad7a-f5ceaa97255e · outbound
This paper cites EdgeSAM: Prompt-In-the-Loop Distillation for SAM.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost EdgeSAM: Prompt-In-the-Loop Distillation for SAM
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:49.890149Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6722ea7-d27d-4d4b-a968-83bc9046d004 · outbound
This paper cites Medical SAM 2: Segment medical images as video via Segment Anything Model 2.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Medical SAM 2: Segment medical images as video via Segment Anything Model 2
Reference 58
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:49.909797Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e62b112e-18b2-4ce8-8a43-a0b8f4e6efd4 · outbound
This paper cites -” indicates directly combining existing pre-trained models for inference. “Cost.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost -” indicates directly combining existing pre-trained models for inference. “Cost
Reference 61
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-07T11:52:50.813473Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 56a8c35a-5af4-4fc7-8199-6c8eecbe5760 · outbound
This paper cites an unresolved cited work.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Unresolved cited work
Reference 2023
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:52:52.280421Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4a59372e-94cc-41ba-9a79-00605792d2b9 · outbound
This paper cites an unresolved cited work.
SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Unresolved cited work
Reference 2024
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:52:52.837961Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
No inbound Pith citation observations are available.