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Paper Citation Record · LEDGER

XLRS-Bench: Could Your Multimodal LLMs Understand Extremely Large Ultra-High-Resolution Remote Sensing Imagery?

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2503.23771.

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

pith.paper-citation-record.v1
2503.23771 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T02:47:25.515864Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T09:47:59.465812Z

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 43f5b33d-fb80-43de-9d4d-209176a8bfe2 · inbound

RSRCC: A Remote Sensing Regional Change Comprehension Benchmark Constructed via Retrieval-Augmented Best-of-N Ranking cites this paper.

RSRCC: A Remote Sensing Regional Change Comprehension Benchmark Constructed via Retrieval-Augmented Best-of-N Ranking XLRS-Bench: Could Your Multimodal LLMs Understand Extremely Large Ultra-High-Resolution Remote Sensing Imagery?

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:24:47.520906Z

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=pdf_text observed=2026-05-10T00:05:26.906011Z digest=sha256:7a85f46e8c89e049a3ea9dae207de79517fa5c1baa77f9021b1e83edd66b26f0

Observation 124b307f-5770-4447-8603-695d158deabc · inbound

UniReason-Med: A Shared Grounded Reasoning Interface for 2D-to-3D Transfer in Medical VQA cites this paper.

UniReason-Med: A Shared Grounded Reasoning Interface for 2D-to-3D Transfer in Medical VQA XLRS-Bench: Could Your Multimodal LLMs Understand Extremely Large Ultra-High-Resolution Remote Sensing Imagery?

Reference 73

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T09:47:59.467156Z

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=2026-06-27T10:21:12.782864Z digest=sha256:f4a561405d4a2bb86d5df0dfb7f8e8b349cdb202187410ccb5c9a6d60641005f

Observation 52b5e044-50a9-4d0c-b289-e25af79c9551 · inbound

Beyond Zooming: Learning Multi-Tool Visual Reasoning for Ultra-High-Resolution Remote Sensing cites this paper.

Beyond Zooming: Learning Multi-Tool Visual Reasoning for Ultra-High-Resolution Remote Sensing XLRS-Bench: Could Your Multimodal LLMs Understand Extremely Large Ultra-High-Resolution Remote Sensing Imagery?

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-01T00:59:16.958440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:59:16.958440Z digest=sha256:dfec5ef060014101d76e46314b1e4c772c4bdf4b2bd7ee25f0836f14783e8838

Observation 121c2f26-fe75-467d-96aa-348bd73e7c38 · inbound

Obshazard-bench: Benchmarking Multimodal Foundation Models for Real-Time Disaster Intelligence from Raw Earth Observation Streams cites this paper.

Obshazard-bench: Benchmarking Multimodal Foundation Models for Real-Time Disaster Intelligence from Raw Earth Observation Streams XLRS-Bench: Could Your Multimodal LLMs Understand Extremely Large Ultra-High-Resolution Remote Sensing Imagery?

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-04T02:47:25.515864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T02:47:25.515864Z digest=sha256:41e5087a4f45a5bb77281ed92aa89c197d2caa2472c4f3b87424579bfdf91e90