Pith. sign in

Paper Citation Record · LEDGER

RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2412.05679.

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

pith.paper-citation-record.v1
2412.05679 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 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 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:39:41.756940Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T09:47:59.375569Z

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 34c328bb-c4b8-44cc-a63f-6325c4738d5e · inbound

Domain Specific Benchmarks for Evaluating Multimodal Large Language Models cites this paper.

Domain Specific Benchmarks for Evaluating Multimodal Large Language Models RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T00:39:41.756940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:39:41.756940Z digest=sha256:21a5ba27ffc2c4d768a2ed3658234df13e29b4b92b5f2215a91c0d086e4d36e8

Observation f83e90f2-a829-40bc-b0ea-8b0f4cb61f5f · inbound

Remote Sensing Large Vision-Language Model: Semantic-augmented Multi-level Alignment and Semantic-aware Expert Modeling cites this paper.

Remote Sensing Large Vision-Language Model: Semantic-augmented Multi-level Alignment and Semantic-aware Expert Modeling RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T22:22:38.461173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:22:38.461173Z digest=sha256:b0f2af68a8ef3e927aae496e3a107622254d0bc6e6009c4c3d5259fdbf309cff

Observation 42d09d2c-62a4-44e8-b52a-39fc11d4074b · inbound

RemoteAgent: Bridging Vague Human Intents and Earth Observation with RL-based Agentic MLLMs cites this paper.

RemoteAgent: Bridging Vague Human Intents and Earth Observation with RL-based Agentic MLLMs RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:40:59.522225Z

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=2026-05-10T18:00:20.216268Z digest=sha256:13103fbbe7b6cdf297a37b8c2da0d60435b5d5255abf3745ea8b91af3d129e6c

Observation 4ed4e817-79c0-40ea-99e1-b327f90eb442 · inbound

Semantic-Geometric Dual Compression: Training-Free Visual Token Reduction for Ultra-High-Resolution Remote Sensing Understanding cites this paper.

Semantic-Geometric Dual Compression: Training-Free Visual Token Reduction for Ultra-High-Resolution Remote Sensing Understanding RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts

Reference 23

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T10:26:01.278915Z

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=2026-05-10T15:29:49.681399Z digest=sha256:9aee9dfda58e763a1a45ce93c26f3f6ed6d418a2804c15414fe5c5e65bf3da5b

Observation 04b6bb58-7ee1-4b85-a3fe-ac50188356c4 · inbound

Decoding the Delta: Unifying Remote Sensing Change Detection and Understanding with Multimodal Large Language Models cites this paper.

Decoding the Delta: Unifying Remote Sensing Change Detection and Understanding with Multimodal Large Language Models RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-10T13:05:25.171115Z

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=2026-05-10T13:01:26.436025Z digest=sha256:71ba1ff996f8eccd974a25ddba4fe07fc8fcc9365ca444f21fd35093242e1c67

Observation 462146e8-e3f8-485c-9d06-b80724d2c503 · inbound

RemoteShield: Enable Robust Multimodal Large Language Models for Earth Observation cites this paper.

RemoteShield: Enable Robust Multimodal Large Language Models for Earth Observation RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-10T06:51:46.266824Z

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=2026-05-10T06:48:11.250689Z digest=sha256:a7e44fb443c545c8538a84b1f54c24b37a56fb852c4a5be86bb6b43d81b4aef2

Observation dc617437-60b5-448a-ae98-2a534bb51f87 · inbound

RemoteZero: Geospatial Reasoning with Zero Human Annotations cites this paper.

RemoteZero: Geospatial Reasoning with Zero Human Annotations RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:30:40.292327Z

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=2026-05-08T18:24:46.030608Z digest=sha256:4243168736aaf3a99cc4b83da32f5b2a051f86a738ae4300bc5d20920addcd25

Observation 686951a9-b252-46b0-b1be-44321a1cfb69 · inbound

SenseBench: A Benchmark for Remote Sensing Low-Level Visual Perception and Description in Large Vision-Language Models cites this paper.

SenseBench: A Benchmark for Remote Sensing Low-Level Visual Perception and Description in Large Vision-Language Models RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:46:35.039793Z

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=2026-05-12T04:00:50.940530Z digest=sha256:4c8af8f98d02c262710e1c05b7767184a5befbd75c63a0bbab90eec22a76ec0c

Observation c013c1a1-21a4-405a-b5ed-fa0325b832db · 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 RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts

Reference 87

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T09:47:59.377021Z

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=2026-06-27T10:21:12.782864Z digest=sha256:2ee15aeeea3e0300f456fd774729d48ce66591b1ee885234c37a958a42293e39

Observation a4009fd8-4c32-408a-933c-a8c1654a3083 · inbound

WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding cites this paper.

WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts

Reference 31

Resolution
unresolved
no resolver link, observed 2026-07-14T14:09:30.395518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T14:09:30.395518Z digest=sha256:98f17a811a90a9bba010cd4824681df5605d7c2d5466a6ff82ced2cc0f673918

Observation bf66e690-c950-4d14-b84c-12030a074936 · inbound

SkyVLaM: Multimodal Large Language Model for UAV Video Understanding in Remote Sensing cites this paper.

SkyVLaM: Multimodal Large Language Model for UAV Video Understanding in Remote Sensing RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-01T18:11:02.265647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:11:02.265647Z digest=sha256:045690604e202320554cac2b79d1ab60077ec92246617387fc54c14020ae1f48