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Paper Citation Record · LEDGER

Semantic-SAM: Segment and Recognize Anything at Any Granularity

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2307.04767.

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

pith.paper-citation-record.v1
2307.04767 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 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 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:14:30.282057Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

51
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a6ab64ba-50ae-4198-89e4-5a9ee91ca4a5 · inbound

Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V cites this paper.

Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-12T14:01:50.005621Z

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.

source=pdf_text observed=2026-05-12T14:01:49.854238Z digest=sha256:71698cc2f37a9ac86f8edb9696a1d6d529750df4361cf982df5e98c4ab7a8d70

Observation e35b4bf4-0d2d-47c4-a8f9-0742a98a8291 · inbound

Self-Correcting Text-to-Video Generation with Misalignment Detection and Localized Refinement cites this paper.

Self-Correcting Text-to-Video Generation with Misalignment Detection and Localized Refinement Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-23T08:25:29.385429Z

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.

source=pdf_text observed=2026-05-23T08:25:01.468957Z digest=sha256:1b3aaa8bbf2205e26b3d10a7a023ca89d4b4222a28f616bb20ab761b1608e3d8

Observation ed41c6af-0ce5-4b2f-9d35-510a57609777 · inbound

Personalization Toolkit: Training Free Personalization of Large Vision Language Models cites this paper.

Personalization Toolkit: Training Free Personalization of Large Vision Language Models Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-23T03:35:21.119306Z

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.

source=pdf_text observed=2026-05-23T03:33:13.549114Z digest=sha256:5ab3b78b49675e12aa3971d7680fc0a6ede353f67276d7ae3897ce021f30112c

Observation ea2279a4-5fa7-4c78-8ea0-4586935ca215 · inbound

FusionForce: End-to-end Differentiable Neural-Symbolic Layer for Trajectory Prediction cites this paper.

FusionForce: End-to-end Differentiable Neural-Symbolic Layer for Trajectory Prediction Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T19:14:30.282057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T19:14:30.282057Z digest=sha256:b9c50fb7edb9cbf1de9a2fc9e429988b8085e3e307caf8eaad0a034b9090aeeb

Observation c563c1f1-84d0-439a-8963-fdd760c74134 · inbound

Synthetic Visual Genome cites this paper.

Synthetic Visual Genome Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T05:34:56.285746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:34:56.285746Z digest=sha256:1334e9a139600aa4ab28e175b20c15ef22c5a99963ad1e5642c79e0f98dba37b

Observation 77f17ac7-04f3-4f9f-8413-ae5154ee2bd6 · inbound

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution cites this paper.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T15:18:55.509775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:55.509775Z digest=sha256:fff16a7d0c777025f7ae2d518b77921d606e017cfd493a55649fc85c3721b29d

Observation d663012e-ae00-487d-9dbc-c13c2da3159f · inbound

Training-free Geometric Image Editing on Diffusion Models cites this paper.

Training-free Geometric Image Editing on Diffusion Models Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-06T10:57:35.968703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:57:35.968703Z digest=sha256:5fa637391b36ee23dc0901cce638a7bd18237805593328b6b586c2ccef839f34

Observation 84e518fe-f37e-4d8e-bd68-20e905e663dc · inbound

PASG: A Closed-Loop Framework for Automated Geometric Primitive Extraction and Semantic Anchoring in Robotic Manipulation cites this paper.

PASG: A Closed-Loop Framework for Automated Geometric Primitive Extraction and Semantic Anchoring in Robotic Manipulation Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-05T23:07:31.129332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T23:07:31.129332Z digest=sha256:e66c1c42b033b9212bdfd11158c4243cd1e48bf1c12940db3a128cd8397a4a94

Observation 0efebf3f-cb5a-47e3-8a60-eeafacf487cd · inbound

Integrating SAM Supervision for 3D Weakly Supervised Point Cloud Segmentation cites this paper.

Integrating SAM Supervision for 3D Weakly Supervised Point Cloud Segmentation Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-05T15:27:12.760761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:27:12.760761Z digest=sha256:f1db02e19facd852927d114392c33a65a9b9add8257264e51b859da339098ac1

Observation 1b92b556-a5ae-4362-a098-6b6e9160f9c2 · inbound

SAM-MI: A Mask-Injected Framework for Enhancing Open-Vocabulary Semantic Segmentation with SAM cites this paper.

SAM-MI: A Mask-Injected Framework for Enhancing Open-Vocabulary Semantic Segmentation with SAM Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-03T20:27:24.734169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T20:27:24.734169Z digest=sha256:b3b4d6fcfb3ca66114ac78a0da721c2b3a933b793b807a91e9646fcb17194325

Observation 74710137-ffa6-4159-bbcd-aef34cfc712b · inbound

MV3DIS: Multi-View Mask Matching via 3D Guides for Zero-Shot 3D Instance Segmentation cites this paper.

MV3DIS: Multi-View Mask Matching via 3D Guides for Zero-Shot 3D Instance Segmentation Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:15:57.908725Z

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.

source=pdf_text observed=2026-05-10T17:44:01.158027Z digest=sha256:ee711e136c689363c819a56d505be224a9032543fa6fc2b2e066ac0bcd037f43

Observation 63b67edc-2284-490b-a413-75df26c30122 · inbound

Amodal SAM: A Unified Amodal Segmentation Framework with Generalization cites this paper.

Amodal SAM: A Unified Amodal Segmentation Framework with Generalization Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-10T01:10:08.914737Z

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.

source=pdf_text observed=2026-05-10T01:07:03.433259Z digest=sha256:174ffd936b851720417b3dd8c3c5bb45dd53c79ec8de58f4f986bf9804187455

Observation 3289eff1-2204-46f4-bcf3-b93c20ac3344 · inbound

UnAC: Adaptive Visual Prompting with Abstraction and Stepwise Checking for Complex Multimodal Reasoning cites this paper.

UnAC: Adaptive Visual Prompting with Abstraction and Stepwise Checking for Complex Multimodal Reasoning Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 16

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T23:16:37.565480Z

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.

source=arxiv_source observed=2026-05-07T17:35:28.050906Z digest=sha256:6895a3d3cc71d4feab2cdba9e601bce60986777ae9cb6d3e29cb49d4967be23f

Observation ab373b61-2f06-406b-81a6-4f4fb58ea751 · inbound

Vision Harnessing Agent for Open Ad-hoc Segmentation cites this paper.

Vision Harnessing Agent for Open Ad-hoc Segmentation Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-05-20T05:53:04.494769Z

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.

source=pdf_text observed=2026-05-20T05:52:40.429412Z digest=sha256:3d8a4f879a77befe687866d2e910f9b5d188029104f6a730f4f28fe5f7f04241

Observation 42021030-6bc4-4a13-8b34-219ce405f24f · inbound

COCOTree: A Dataset and Benchmark for Open Tree-Structured Visual Decomposition cites this paper.

COCOTree: A Dataset and Benchmark for Open Tree-Structured Visual Decomposition Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-22T08:01:16.126830Z

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.

source=pdf_text observed=2026-05-22T07:56:21.445602Z digest=sha256:d89eec393ed4c3d827262806f568aad24ba7cc2e05697deb72a9da588d6eb4c4

Observation b7049ca8-b8f1-42df-ba63-64a7fd63085b · inbound

Ultralytics YOLO26: Unified Real-Time End-to-End Vision Models cites this paper.

Ultralytics YOLO26: Unified Real-Time End-to-End Vision Models Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:26:26.534722Z

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.

source=pdf_text observed=2026-06-28T10:57:09.699207Z digest=sha256:795fdc5ef7b471d72bfd135a6bd0ad4caf479495f7b5546835898303e257a0c2

Observation d21b7517-aca7-4822-9285-7ccf5d577df0 · inbound

EPS3D: End-to-End Feed-Forward 3D Panoptic Segmentation cites this paper.

EPS3D: End-to-End Feed-Forward 3D Panoptic Segmentation Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-03T00:27:29.333214Z

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.

source=pdf_text observed=2026-06-27T17:14:57.964494Z digest=sha256:c4cfc0a9af3493ddbc49f8e157c0145cbbeb86bfd375410b4f21b835f00a7b18

Observation be855366-f952-4dd2-95c6-e5f40a1542df · inbound

In-context Region-based Drag: Drag Any Region to Any Shape cites this paper.

In-context Region-based Drag: Drag Any Region to Any Shape Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 91

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T20:10:08.828752Z

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.

source=arxiv_source observed=2026-06-25T20:32:44.771500Z digest=sha256:fc57699909f7b9bda3fbe4fa59949aa609f0dde27487d07508a0cf201eada9a3

Observation 5f8defb1-5b75-4237-8d1c-43c81f2000b1 · inbound

G$^2$TAM: Geometry Grounded Track Anything Model cites this paper.

G$^2$TAM: Geometry Grounded Track Anything Model Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-11T23:56:52.009530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T23:56:52.009530Z digest=sha256:a973337efa991ef7b44afa9c597f30cdbb17abc3255251b8e7276cb45a68e92e