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Paper Citation Record · LEDGER

RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2406.07089.

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

pith.paper-citation-record.v1
2406.07089 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:23:08.399859Z

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

2
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 f5c15524-3534-4cea-84b1-de1a06cd517e · inbound

Augmented Vision-Language Models: A Systematic Review cites this paper.

Augmented Vision-Language Models: A Systematic Review RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 120

Resolution
unresolved
no resolver link, observed 2026-08-06T14:33:43.369772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:33:43.369772Z digest=sha256:04b20944d4f815274ea6556b8886dd3dcb073145c15f6d4ddf77654df657459a

Observation 0ab927cc-e6b3-4cde-ae35-7bd82d5094f5 · inbound

CangLing-KnowFlow: A Unified Knowledge-and-Flow-fused Agent for Comprehensive Remote Sensing Applications cites this paper.

CangLing-KnowFlow: A Unified Knowledge-and-Flow-fused Agent for Comprehensive Remote Sensing Applications RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-03T15:55:28.151602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:55:28.151602Z digest=sha256:869d7877abfd4c2b50755f73123ba30d23bafe044fbda9a9ff609c9823ad6ca5

Observation 18298235-368d-4992-a7b2-1be2dd75e29a · inbound

Agentic AI in Remote Sensing: Foundations, Taxonomy, and Emerging Systems cites this paper.

Agentic AI in Remote Sensing: Foundations, Taxonomy, and Emerging Systems RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 142

Resolution
verified exact
arxiv_id, observed 2026-07-08T02:18:05.035311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-16T18:28:33.277442Z digest=sha256:bebb5616811a9813b73295d6516ff46a105b5fe9d2666581c4ec03743d3be7fb

Observation 6c312ba4-2c37-4d91-8d7b-64e5b69540bc · inbound

Forest-Chat: Adapting Vision-Language Agents for Interactive Forest Change Analysis cites this paper.

Forest-Chat: Adapting Vision-Language Agents for Interactive Forest Change Analysis RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-03T09:13:39.180706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T09:13:39.180706Z digest=sha256:93b8fa8dbde0d821e6ad53796a34f88e4f58b9cf457a8502798b8820d778fad4

Observation 0dc04eb6-7ff1-441b-9b98-62e3490a0f16 · inbound

OpenEarthAgent: A Unified Framework for Tool-Augmented Geospatial Agents cites this paper.

OpenEarthAgent: A Unified Framework for Tool-Augmented Geospatial Agents RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-02T22:10:53.599802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T22:10:53.599802Z digest=sha256:ac25716b78566fa3afc64c66de16ff77a35505a5a6022d95524ed6a5d2b38687

Observation 3298f736-ee7c-4417-822c-bb2c0ce5df17 · 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 RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 67

Resolution
verified exact
arxiv_id, observed 2026-07-08T02:18:05.035311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T18:00:20.216268Z digest=sha256:940d2c48c9b555a8e37e6f5f23e38e421266883e170b94763755647552175b17

Observation 13e99e6c-625b-425b-9660-12757f10a9a4 · inbound

MONETA: Multimodal Industry Classification through Geographic Information with Multi Agent Systems cites this paper.

MONETA: Multimodal Industry Classification through Geographic Information with Multi Agent Systems RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-07-08T02:18:05.035311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-10T18:30:00.400451Z digest=sha256:a95079e97ef81e6530bbf4df8a88e8f38813d5ccd0deca030a711693a7df9cba

Observation 483a138e-02df-48c3-a2d6-8313f549a54a · inbound

Agentic AI for Remote Sensing: Technical Challenges and Research Directions cites this paper.

Agentic AI for Remote Sensing: Technical Challenges and Research Directions RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 130

Resolution
verified exact
arxiv_id, observed 2026-07-08T02:18:05.035311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-08T04:29:22.477531Z digest=sha256:6ce2730de8e9ce821403bc0fca5dcdbaa2f2e7188a89c6ed0ac714500eb3f871

Observation 723fe82f-009f-4970-bb82-74edd1563006 · inbound

Agentic AI for Remote Sensing: Technical Challenges and Research Directions cites this paper.

Agentic AI for Remote Sensing: Technical Challenges and Research Directions RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 130

Resolution
verified exact
arxiv_id, observed 2026-07-08T02:18:05.035311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-14T20:55:38.841743Z digest=sha256:a810a9e180fa4ff5cea236c4842cb7b60c734af7688ac444181500dda6c4402d

Observation 62a99541-b2f8-46fc-8ee2-60208cb7a4df · inbound

Bridging Perception and Action: A Lightweight Multimodal Meta-Planner Framework for Robust Earth Observation Agents cites this paper.

Bridging Perception and Action: A Lightweight Multimodal Meta-Planner Framework for Robust Earth Observation Agents RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 85

Resolution
metadata mismatch
arxiv_id, observed 2026-07-08T02:18:05.035311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-08T15:45:27.700503Z digest=sha256:c011b7b5e7d3342d2306504b8c11187194071ad4ba9c72f397128cca18d89184

Observation 9e4987e6-6318-4dd7-a431-413ec26a7cdb · inbound

Can LLM Agents Respond to Disasters? Benchmarking Heterogeneous Geospatial Reasoning in Emergency Operations cites this paper.

Can LLM Agents Respond to Disasters? Benchmarking Heterogeneous Geospatial Reasoning in Emergency Operations RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-07-08T02:18:05.035311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-13T01:25:42.059685Z digest=sha256:8185e125695b61b452dc80a31fb7ac4a832465744000404b3f3be6ef1c8e54a6

Observation 990366fb-ec53-4853-af6c-c9a49913fa1e · inbound

RS-Claw: Progressive Active Tool Exploration via Hierarchical Skill Trees for Remote Sensing Agents cites this paper.

RS-Claw: Progressive Active Tool Exploration via Hierarchical Skill Trees for Remote Sensing Agents RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-07-08T02:18:05.035311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-14T19:33:48.787673Z digest=sha256:ec018b5a9aa9b4b043a6be0dd7e046249afb8355d38a2a1d857b57d2399a835e

Observation 734f3f55-fa06-4cf9-bf13-6700bd9d2e77 · inbound

Bidirectional Semantic Complementary Tool Retrieval for Remote Sensing Agents cites this paper.

Bidirectional Semantic Complementary Tool Retrieval for Remote Sensing Agents RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-07-08T02:18:05.035311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-01T08:40:29.728679Z digest=sha256:411a8e39fbefc8b92ae04d77801a96bc53d5fc844df2fcb50aa692417dbb0a94

Observation ac4f5fbb-b342-4de9-9393-5610db0792cb · inbound

GeoDisaster: Benchmarking Orchestrated Agents for Operational Disaster Geo-Intelligence cites this paper.

GeoDisaster: Benchmarking Orchestrated Agents for Operational Disaster Geo-Intelligence RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-07-08T02:18:05.035311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-27T03:49:42.112919Z digest=sha256:7631c7cb9900e94fe0321f3fbe2095e0a1c54b685b91f4c45b3ddf22def06cfa

Observation 398e9758-a33c-48be-a634-6cada187c4ec · inbound

A Task-Driven and Quality-Assured Agent Framework for SAR Data Generation cites this paper.

A Task-Driven and Quality-Assured Agent Framework for SAR Data Generation RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-08T02:18:05.035311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T08:39:12.222916Z digest=sha256:ccdd6660e5e15497819f5854ceb98f9b7e26e7e5758a8703cd0ea3299a4db026

Observation e8dcb154-998c-48ea-b4c6-1699762af818 · inbound

JL1-CC&QA: Extending the JL1-CD Benchmark with Change Captioning and Question Answering cites this paper.

JL1-CC&QA: Extending the JL1-CD Benchmark with Change Captioning and Question Answering RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 136

Resolution
verified exact
arxiv_id, observed 2026-07-08T02:18:05.035311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-01T05:25:10.409645Z digest=sha256:618e2918a48f56c2ef94e5691c16937661f0e5f45e54311c5dc52b2b652efc25

Observation ff5c14ec-5c39-4d18-a323-49baa60be98f · inbound

Multimodal Large Language Models for Remote Sensing Image Understanding: Domain-Specific or General-Purpose? cites this paper.

Multimodal Large Language Models for Remote Sensing Image Understanding: Domain-Specific or General-Purpose? RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-01T10:20:55.171751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T10:20:55.171751Z digest=sha256:b1c833a42d6d87b4b1b3dad441b0b63bed476f39162f024591f0683d0ae0762f

Observation 2502ba9d-f7c6-4f86-9f67-e6c78d2b8961 · inbound

GeoForge: Non-Parametric Self-Evolving Agents for Earth-Observation Reasoning cites this paper.

GeoForge: Non-Parametric Self-Evolving Agents for Earth-Observation Reasoning RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-15T14:23:08.399859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T14:23:08.399859Z digest=sha256:1fa3c31677e6f4ad2a6f0e43653901eab1007393e1113a0d82fd19c6d96c1663