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Paper Citation Record · LEDGER

Segment Everything Everywhere All at Once

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2304.06718.

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

pith.paper-citation-record.v1
2304.06718 v4

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 2026-08-07T06:34:17.273281+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:23:56.532387Z

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
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

152
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 9978467e-fe73-445f-ad36-107fed6fde64 · 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 Segment Everything Everywhere All at Once

Reference 299

Resolution
verified exact
arxiv_id, observed 2026-05-14T23:07:42.969180Z

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=sha256:15fc5d249caab79ab67d2e146d5b903b05401c02970e06d1bb9210dfbc363899

Observation 2643566a-fe84-4a14-a8b4-a44edef62890 · inbound

Evaluating Object Hallucination in Large Vision-Language Models cites this paper.

Evaluating Object Hallucination in Large Vision-Language Models Segment Everything Everywhere All at Once

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-11T13:44:09.728006Z

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=2026-05-11T13:44:09.626361Z digest=sha256:9f7b095bae0aaeda643f7af420b11c89530bd2df21c13abc2e6066bbf16ffbd2

Observation e1790811-4204-4ca4-9a5a-74e6d6e1a2e4 · inbound

The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) cites this paper.

The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) Segment Everything Everywhere All at Once

Reference 160

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T23:26:06.571484Z

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=2026-05-15T23:26:06.183574Z digest=sha256:e835968e4d5468b392a140544975ce04f6006f787c743a285edd27188fa3815a

Observation 8b2cf28e-a79f-422d-9fc3-f31abffb0f22 · 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 Segment Everything Everywhere All at Once

Reference 65

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T14:01:49.971425Z

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=2026-05-12T14:01:49.854238Z digest=sha256:0e823f529152a38ae78da971fce05405d38d76bfc581a07e32d3dd71a9aab79f

Observation abf5aaca-21bb-4d6a-a111-80dc9d3d8b09 · inbound

Deformable Attentive Visual Enhancement for Referring Segmentation Using Vision-Language Model cites this paper.

Deformable Attentive Visual Enhancement for Referring Segmentation Using Vision-Language Model Segment Everything Everywhere All at Once

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T14:23:56.532387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:23:56.532387Z digest=sha256:4766de2542b0b5bc16da6603f3554f565fe914493f1c2a44c9c446355d6a2f12

Observation 2c663d35-f275-4fdf-89a6-cb6c53056acc · inbound

From Vision To Language through Graph of Events in Space and Time: An Explainable Self-supervised Approach cites this paper.

From Vision To Language through Graph of Events in Space and Time: An Explainable Self-supervised Approach Segment Everything Everywhere All at Once

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T19:43:43.308601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:43:43.308601Z digest=sha256:6bbe5de57d6984838f66c287815e0a035e068a72fd6faf6269b91133081b42db

Observation 8e008236-00e6-4e64-8d6f-cc78ffb88613 · inbound

Prompt Engineering in Segment Anything Model: Methodologies, Applications, and Emerging Challenges cites this paper.

Prompt Engineering in Segment Anything Model: Methodologies, Applications, and Emerging Challenges Segment Everything Everywhere All at Once

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-06T17:56:03.866876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:56:03.866876Z digest=sha256:2ab4ca279c8ffbd891d54b9d4e8ffd5a70461d6b901e736b631fbfed1b40621b

Observation 04472d0b-2cf9-4923-ba9c-f146fb714665 · inbound

Discovering and using Spelke segments cites this paper.

Discovering and using Spelke segments Segment Everything Everywhere All at Once

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T15:25:13.523578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:25:13.523578Z digest=sha256:ff948ba56859255ac0d88df5afb7330a470ce3c206d0218312fdbfaccfdd3ac2

Observation 014c5b24-eefd-4e5b-88c6-b05da2a6081b · inbound

DrivingGaussian++: Towards Realistic Reconstruction and Editable Simulation for Surrounding Dynamic Driving Scenes cites this paper.

DrivingGaussian++: Towards Realistic Reconstruction and Editable Simulation for Surrounding Dynamic Driving Scenes Segment Everything Everywhere All at Once

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-05T14:47:12.824391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:47:12.824391Z digest=sha256:d230ae21fa2f7b3d0b937a6bac66adcd9c43c82938ad66e5479f413199b781b9

Observation c303e814-4ce6-4193-8f03-493afad9fc66 · inbound

Functionalization via Structure Completion and Motion Rectification cites this paper.

Functionalization via Structure Completion and Motion Rectification Segment Everything Everywhere All at Once

Reference 169

Resolution
verified exact
arxiv_id, observed 2026-05-20T12:28:17.082194Z

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=sha256:60c248fb397f6b6d5472b252003e6e5ad13da633b4f1fc5cb69cdae8828dfa7f