Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2312.00863.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T11:19:23.161236Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T13:48:19.715498Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 4931a258-6a2c-4fa7-93df-a87005a97de3 · inbound
Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks cites this paper.
Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
Reference 63
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T06:20:15.828200Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation b1807004-4610-4e87-9e7d-d8620f8f41f1 · inbound
Looking Locally: Object-Centric Vision Transformers as Foundation Models for Efficient Segmentation cites this paper.
Looking Locally: Object-Centric Vision Transformers as Foundation Models for Efficient Segmentation EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T11:19:23.161236Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a8540285-5f7d-4a9d-aa91-17cdcaba8555 · inbound
IRS: Incremental Relationship-guided Segmentation for Digital Pathology cites this paper.
IRS: Incremental Relationship-guided Segmentation for Digital Pathology EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:04:30.647045Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ee6d4960-afe5-4b1c-9271-2392a7a93bad · inbound
Inter2Former: Dynamic Hybrid Attention for Efficient High-Precision Interactive cites this paper.
Inter2Former: Dynamic Hybrid Attention for Efficient High-Precision Interactive EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:59:44.221558Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9ea5bad5-b353-4a73-967f-3c010aaaeb95 · inbound
Zero-Shot Polygon Matching with Pre-trained Models for Pose Estimation and Polygon Cloud from Challenging Stereo cites this paper.
Zero-Shot Polygon Matching with Pre-trained Models for Pose Estimation and Polygon Cloud from Challenging Stereo EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T23:28:25.846478Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1f74f94b-0330-4494-aed6-53645f5827ec · inbound
Towards Any-Quality Image Segmentation via Generative and Adaptive Latent Space Enhancement cites this paper.
Towards Any-Quality Image Segmentation via Generative and Adaptive Latent Space Enhancement EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
Reference 85
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-16T18:13:13.166338Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6ffa774f-7082-4caf-acd5-028420dab5d5 · inbound
Lightweight Distillation of SAM 3 and DINOv3 for Edge-Deployable Individual-Level Livestock Monitoring and Longitudinal Visual Analytics cites this paper.
Lightweight Distillation of SAM 3 and DINOv3 for Edge-Deployable Individual-Level Livestock Monitoring and Longitudinal Visual Analytics EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T09:56:26.726950Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 233c3beb-d218-461b-9177-1fa9834854cc · inbound
SparseSAM: Structured Sparsification of Activations in Segment Anything Models cites this paper.
SparseSAM: Structured Sparsification of Activations in Segment Anything Models EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T13:48:19.717709Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6cb6212c-e438-4fb6-8517-2d3c7a4349a7 · inbound
GeoSAM-Lite: A Lightweight Foundation Model for Onboard Remote Sensing Segmentation cites this paper.
GeoSAM-Lite: A Lightweight Foundation Model for Onboard Remote Sensing Segmentation EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T00:08:46.276767Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.