Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:56:39.687700Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2507.14613.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:56:39.687700Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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
14 of 14 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 5deed596-dac0-4f54-9367-442e74444093 · outbound
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 The results are presented in Table 1
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 44cf5867-ced4-4a77-9dc7-02b7aff617b2 · outbound
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 Its architecture comprises three main components: an image encoder, a prompt encoder, and a mask decoder
Reference 2
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 507f8c77-0451-4988-a830-54b3be5ee801 · outbound
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 The architecture is composed of four key components: the image encoder, streaming memory, prompt encoder, and mask decoder
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4e873f02-67ab-4f6f-91c0-3c5116435f3e · outbound
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 Unresolved cited work
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 49c5dd50-3c53-479a-b575-89382f6dabe2 · outbound
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 Unresolved cited work
Reference 5
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3330d967-2867-4aee-bd27-b0fe0754ec16 · outbound
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 Unresolved cited work
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e98db074-677c-42cc-b852-c7e987d9c7e0 · outbound
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 Medical SAM 2: Segment medical images as video via Segment Anything Model 2
Reference 7
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 29129471-3484-4662-861f-bf6420c041c5 · outbound
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 The corresponding performance metrics are summarized in Table 2
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation bc56d8cc-114c-4903-974b-0c2f517b93ee · outbound
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 The first -frame prompt was a bounding box, while the middle -frame prompt varied across three types: mask, bounding box, and 10 positive points
Reference 10
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ab6548b2-b5ed-4855-a989-7ec505f77f36 · outbound
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 Unresolved cited work
Reference 11
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e99df406-dc20-4eb0-872c-97fb33648973 · outbound
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 The results, presented in Table 10, indicate that both models maintain competitive performance across all four evaluation metrics , even with as few as one or two training cases
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 74d45e81-3666-40f4-97c6-dc70bd448c02 · outbound
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 Unresolved cited work
Reference 13
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2ba5a18b-8da0-457c-a3c3-774f9d1a1308 · outbound
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 The results are summarized in Table 11
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 49e7e743-ea47-4fbf-95e7-ef7e79c9cd59 · outbound
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2 In these visualizations, the ground truth annotations are shown in red, whereas the model predictions are depicted in green
Reference 15
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
No inbound Pith citation observations are available.