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Paper Citation Record · LEDGER

SegGPT: Segmenting Everything In Context

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2304.03284.

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

pith.paper-citation-record.v1
2304.03284 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:34:02.883035Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T22:17:26.317749Z

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 23ce99aa-f8c4-4d88-8d31-ffcb1600b1fb · inbound

LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention cites this paper.

LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention SegGPT: Segmenting Everything In Context

Reference 289

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T23:07:42.904075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-14T23:07:42.245641Z digest=sha256:18990010ab0ed81745db56b7b5573e5ca03b0442527ecfbe1277d94d1f265967

Observation 85cb4df5-4ad4-45a3-be1f-22cc82bd2f69 · inbound

Comparison Study: Glacier Calving Front Delineation in Synthetic Aperture Radar Images With Deep Learning cites this paper.

Comparison Study: Glacier Calving Front Delineation in Synthetic Aperture Radar Images With Deep Learning SegGPT: Segmenting Everything In Context

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-23T05:55:27.520531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-23T05:54:29.408764Z digest=sha256:505ad15d27b21c9ec29cd124889ce14374f25763427d47ff0a989c3f40a0fbfc

Observation c62d018a-9cf4-4368-b7d8-bffd7e730ec2 · inbound

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine cites this paper.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine SegGPT: Segmenting Everything In Context

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-07T11:34:02.883035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:34:02.883035Z digest=sha256:440af0d4bad1cbac2c1b94efffee967a2eaba4a29b811c8d637750032f4ab580

Observation 1038fe8b-c7cd-44f3-8436-a5b918634933 · inbound

ConText: Driving In-context Learning for Text Removal and Segmentation cites this paper.

ConText: Driving In-context Learning for Text Removal and Segmentation SegGPT: Segmenting Everything In Context

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-07T11:01:12.851868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:01:12.851868Z digest=sha256:1d79695332281e0f7e6e602c3f44f1b9e1d7cd099e2827bbee5624a4b4a35870

Observation 8e077271-0c8a-4686-a488-f855ee7cfb74 · inbound

Is Visual in-Context Learning for Compositional Medical Tasks within Reach? cites this paper.

Is Visual in-Context Learning for Compositional Medical Tasks within Reach? SegGPT: Segmenting Everything In Context

Reference 89

Resolution
unresolved
no resolver link, observed 2026-08-06T21:12:06.111268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:12:06.111268Z digest=sha256:7bdf1dc93b7564e20478ad57f5d4c9909c0d01dcd7a92cf71d1f79ab8eae15bd

Observation 7d9ab87b-5fac-4a46-8f21-5f277d3c7140 · inbound

Generate Aligned Anomaly: Region-Guided Few-Shot Anomaly Image-Mask Pair Synthesis for Industrial Inspection cites this paper.

Generate Aligned Anomaly: Region-Guided Few-Shot Anomaly Image-Mask Pair Synthesis for Industrial Inspection SegGPT: Segmenting Everything In Context

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-06T17:57:53.709870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:57:53.709870Z digest=sha256:c1f1e5feb0fa7f73a6cb900c01269755202e1dfffa668c512a66a3cfbdbe173b

Observation 62873a9b-c56b-4f7f-98bf-49240d3e6394 · inbound

Decouple before Align: Visual Disentanglement Enhances Prompt Tuning cites this paper.

Decouple before Align: Visual Disentanglement Enhances Prompt Tuning SegGPT: Segmenting Everything In Context

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T10:17:04.461068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:17:04.461068Z digest=sha256:c580808ef11ea860214843336e2ef3afa19b49f2f5bf4a9512133f3ccac64882

Observation 01044a92-b29a-4e56-aecb-5b0abe3a94db · inbound

DOMR: Establishing Cross-View Segmentation via Dense Object Matching cites this paper.

DOMR: Establishing Cross-View Segmentation via Dense Object Matching SegGPT: Segmenting Everything In Context

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T01:01:24.498380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T01:01:24.498380Z digest=sha256:439e6eef79be2ccf0c7c41771880713f57046e620683f024e9bf8138e1cddb93

Observation d6743e03-b4d1-4a9f-ad12-21eb31c0a679 · inbound

Stable Diffusion Models are Secretly Good at Visual In-Context Learning cites this paper.

Stable Diffusion Models are Secretly Good at Visual In-Context Learning SegGPT: Segmenting Everything In Context

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-05T20:45:10.267368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:45:10.267368Z digest=sha256:fc2170369cafdd0629279d3f17c67e62847b59ec0388421077e251c75612d101

Observation 0fb81cf2-0628-439d-b988-dc5bcdda3cca · inbound

GenCellAgent: Generalizable, Training-Free Cellular Image Segmentation via Large Language Model Agents cites this paper.

GenCellAgent: Generalizable, Training-Free Cellular Image Segmentation via Large Language Model Agents SegGPT: Segmenting Everything In Context

Reference 27

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T07:26:03.473914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T07:22:58.072356Z digest=sha256:903f397c96caac6be38f964f9cfeeb0f422cfd4a0137ec7aa3587be419da5b16

Observation 91522a8d-c611-4dae-837e-c4b9a38de124 · inbound

Fully Spiking Neural Networks with Target Awareness for Energy-Efficient UAV Tracking cites this paper.

Fully Spiking Neural Networks with Target Awareness for Energy-Efficient UAV Tracking SegGPT: Segmenting Everything In Context

Reference 42

Resolution
unresolved
no resolver link, observed 2026-07-13T16:55:20.099628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T16:55:20.099628Z digest=sha256:8146e548a48a4b0b89627232af4b00261f91546327bb963d0f46d7efd72bd26f

Observation 09aded28-89ab-4ba2-ac50-68f027d204d3 · inbound

Learning to Focus and Precise Cropping: A Reinforcement Learning Framework with Information Gaps and Grounding Loss for MLLMs cites this paper.

Learning to Focus and Precise Cropping: A Reinforcement Learning Framework with Information Gaps and Grounding Loss for MLLMs SegGPT: Segmenting Everything In Context

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-14T21:38:01.034863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-14T21:35:12.859669Z digest=sha256:b99ca244c199d38ee0badb7906cffab10b97af0f919fa0c4a8820764015ca16c

Observation bc20fc3c-34a9-4ada-8fcf-1855260cff7d · inbound

Probing Intrinsic Medical Task Relationships: A Contrastive Learning Perspective cites this paper.

Probing Intrinsic Medical Task Relationships: A Contrastive Learning Perspective SegGPT: Segmenting Everything In Context

Reference 70

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:25:50.207998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T19:54:48.926387Z digest=sha256:143b82fb5e412c38d497b9d6461a31cbf455d5f51fcc8c4b12334a33f9a8467e

Observation d1eeb079-78e6-458a-87a6-77bff994661c · 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 SegGPT: Segmenting Everything In Context

Reference 21

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T23:16:37.390425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-07T17:35:28.050906Z digest=sha256:70b9102d8157eac2fc15c019f810da9ce3509cf933b4ad41a305a08dd8b9ebf4

Observation 60210681-032c-44b2-9b13-5daf31b29e26 · inbound

Functionalization via Structure Completion and Motion Rectification cites this paper.

Functionalization via Structure Completion and Motion Rectification SegGPT: Segmenting Everything In Context

Reference 166

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T12:28:17.038715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-20T12:25:07.157086Z digest=sha256:7517a8d0a6780c7d03175ce2facdb189653409dc93fb610a5fdbf8271d5aae7b

Observation 1a098565-88fb-4bff-ae60-a2e2d5d55715 · inbound

CheXanatomy: Anatomy-Aware Vision-Language Modeling for Chest Radiographs cites this paper.

CheXanatomy: Anatomy-Aware Vision-Language Modeling for Chest Radiographs SegGPT: Segmenting Everything In Context

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-07-02T22:17:26.319426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T19:01:14.023587Z digest=sha256:551ad6d3124828b78506812b9ffeae1159f454e02d26174ffce2b0019024eb28