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Paper Citation Record · LEDGER

Domain Adaptation and Multi-view Attention for Learnable Landmark Tracking with Sparse Data

As of 13 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 0 inbound Pith citation observations for arXiv:2507.09420.

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

pith.paper-citation-record.v1
2507.09420 v1

Coverage vector

measured 10 of 10 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:59:26.225386Z

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

10 of 10 outbound references displayed

  • verified exact1
  • verified fuzzy7
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3dc4174d-73f8-40f6-9e56-b1f76a5cabeb · outbound

This paper cites an unresolved cited work.

Domain Adaptation and Multi-view Attention for Learnable Landmark Tracking with Sparse Data Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:59:27.496976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T17:59:25.650633Z digest=sha256:8696252917006b6fa78d18f77d101e4ba6ef3b816d4429059da41fa98dc275e3

Observation 21b5f2ca-5612-4a54-b6c9-57e4bf057869 · outbound

This paper cites Mars: Multi-view attention regularizations for patch-based feature recognition of space terrain.

Domain Adaptation and Multi-view Attention for Learnable Landmark Tracking with Sparse Data Mars: Multi-view attention regularizations for patch-based feature recognition of space terrain

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:59:27.353989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T17:59:25.711944Z digest=sha256:31ca4cff37b9c5e674d38cf66ffba21e1cae80e87d17c7083979140fbca999d9

Observation 4557e1c8-d36a-4b1f-a068-e8eceda596e4 · outbound

This paper cites Profiling vision-based deep learning architectures on nasa spacecube platforms.

Domain Adaptation and Multi-view Attention for Learnable Landmark Tracking with Sparse Data Profiling vision-based deep learning architectures on nasa spacecube platforms

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T17:59:25.819012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:59:25.819012Z digest=sha256:8517328b8e79e0d41e782e28779104973f3e24d80385543bab369d26fce9b7f7

Observation 0feed838-3d85-463e-ad2e-97fbfe751bc6 · outbound

This paper cites You Only Crash Once v2: Perceptually Consistent Strong Features for One-Stage Domain Adaptive Detection of Space Terrain.

Domain Adaptation and Multi-view Attention for Learnable Landmark Tracking with Sparse Data You Only Crash Once v2: Perceptually Consistent Strong Features for One-Stage Domain Adaptive Detection of Space Terrain

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:59:26.408619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T17:59:25.883202Z digest=sha256:44d2d84b29520f42615a16dbd99c04c66f5b392207cb7faf3032f8a6c3e25b81

Observation 3ec65b83-6f3f-4cb0-a359-30b0f4603b02 · outbound

This paper cites Challenges of slam in extremely unstructured environments: The dlr planetary stereo, solid-state lidar, inertial dataset.

Domain Adaptation and Multi-view Attention for Learnable Landmark Tracking with Sparse Data Challenges of slam in extremely unstructured environments: The dlr planetary stereo, solid-state lidar, inertial dataset

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:59:27.224277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T17:59:25.941884Z digest=sha256:df464954a3a07cb0986b6ed78352b60e196496de9a6add67662c89c7b7ecc418

Observation da1d316a-ee4e-44cf-a63b-49d953364007 · outbound

This paper cites Nasa SpaceCube Edge TPU SmallSat Card for Autonomous Operations and Onboard Science-Data Analysis.

Domain Adaptation and Multi-view Attention for Learnable Landmark Tracking with Sparse Data Nasa SpaceCube Edge TPU SmallSat Card for Autonomous Operations and Onboard Science-Data Analysis

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:59:27.112653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T17:59:26.020856Z digest=sha256:3e77cdfde802c51a53870e02b4abe00fbb1cc8647c79362442f81913f86723c3

Observation f3e19bf7-7862-4edf-8b3c-751b0f3a4a21 · outbound

This paper cites Mars 2020 lander vision system flight performance.

Domain Adaptation and Multi-view Attention for Learnable Landmark Tracking with Sparse Data Mars 2020 lander vision system flight performance

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:59:26.976534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T17:59:26.071634Z digest=sha256:5c2215f9dc84f7d6d3562053aa3315d46c3df8ea5d5a54edb5266b11b49fb695

Observation 3e635b6b-2a0c-45d5-99cc-84d880745974 · outbound

This paper cites Autonomous navigation performance using natural feature tracking during the osiris-rex touch-and-go sample collection event.

Domain Adaptation and Multi-view Attention for Learnable Landmark Tracking with Sparse Data Autonomous navigation performance using natural feature tracking during the osiris-rex touch-and-go sample collection event

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:59:26.853409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T17:59:26.124806Z digest=sha256:5de8ad3b22f0445275010c6d37b6cf67ebc560353ed24a3aacb1d285f0cf879f

Observation 3dad846e-70bd-4b6f-959d-cc4a5f87e16b · outbound

This paper cites Seeking similarities over differences: Similarity-based domain alignment for adaptive object detection.

Domain Adaptation and Multi-view Attention for Learnable Landmark Tracking with Sparse Data Seeking similarities over differences: Similarity-based domain alignment for adaptive object detection

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:59:26.710058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T17:59:26.177073Z digest=sha256:5a0f85d3ac228962582bfdbe992ad05a08ba13c9aa2a09237dd1b6543bc1259c

Observation 02307750-dc68-436c-bb54-0e393b2ce9d9 · outbound

This paper cites Relative terrain imaging navigation (retina) tool for the asteroid redirect robotic mission (arrm).

Domain Adaptation and Multi-view Attention for Learnable Landmark Tracking with Sparse Data Relative terrain imaging navigation (retina) tool for the asteroid redirect robotic mission (arrm)

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:59:26.605547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T17:59:26.225386Z digest=sha256:3da855265636a8fef120c50ae3b0f9433530d4d34e82849124b8c1c45a8e9f89

Pith citing papers

No inbound Pith citation observations are available.