Paper Citation Record · LEDGER

Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2408.07931.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2408.07931 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:07:34.900507Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T13:39:50.407907Z

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 1304567c-7feb-42e1-8e5a-b0e2c7e4aea9 · inbound

SASVi -- Segment Any Surgical Video cites this paper.

SASVi -- Segment Any Surgical Video Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T11:07:34.900507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d97282a-0322-42fa-a8d3-8595e413b810 · inbound

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost cites this paper.

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 7975da19-cd78-4200-b52d-6eb0741a478e · inbound

SurgVLM: A Large Vision-Language Model and Systematic Evaluation Benchmark for Surgical Intelligence cites this paper.

SurgVLM: A Large Vision-Language Model and Systematic Evaluation Benchmark for Surgical Intelligence Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T11:26:38.845546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a22fdc4b-c2a9-4fbb-86f2-ac1058f66381 · inbound

Challenging Vision-Language Models with Surgical Data: A New Dataset and Broad Benchmarking Study cites this paper.

Challenging Vision-Language Models with Surgical Data: A New Dataset and Broad Benchmarking Study Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T06:01:40.821259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb935502-4c04-4525-868d-28418d07b2e4 · inbound

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation cites this paper.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T17:58:45.474699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6609d21-15fc-4281-af7b-6e0e2930faf6 · inbound

HRVVS: A High-resolution Video Vasculature Segmentation Network via Hierarchical Autoregressive Residual Priors cites this paper.

HRVVS: A High-resolution Video Vasculature Segmentation Network via Hierarchical Autoregressive Residual Priors Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T11:38:36.105922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9dace3aa-b40e-4400-b2e3-c49b25429d65 · inbound

PanoSAM2: Lightweight Distortion- and Memory-aware Adaptions of SAM2 for 360 Video Object Segmentation cites this paper.

PanoSAM2: Lightweight Distortion- and Memory-aware Adaptions of SAM2 for 360 Video Object Segmentation Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:30:55.274014Z

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 21f8ae61-2403-4e9d-80a4-3fcd01c147c3 · inbound

EndoGSim: Physics-Aware 4D Dynamic Endoscopic Scene Simulations via MLLM-Guided Gaussian Splatting cites this paper.

EndoGSim: Physics-Aware 4D Dynamic Endoscopic Scene Simulations via MLLM-Guided Gaussian Splatting Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-20T19:53:42.128425Z

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 d70917f2-f263-4058-b461-a5e41341f87a · inbound

Training LLMs with Reinforcement Learning over Digital Twin Representations for Reasoning-Intensive Surgical VideoQA cites this paper.

Training LLMs with Reinforcement Learning over Digital Twin Representations for Reasoning-Intensive Surgical VideoQA Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-03T17:48:46.286113Z

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 ee8169a5-7a5e-4943-9c1e-a9e8abff41d7 · inbound

Temporally Consistent Label Interpolation for Robust Surgical Multi-Task Learning under Challenging Conditions cites this paper.

Temporally Consistent Label Interpolation for Robust Surgical Multi-Task Learning under Challenging Conditions Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning

Reference 34

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T13:39:50.409522Z

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.