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Paper Citation Record · LEDGER

RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 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 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:33:43.369772Z

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=sha256:2cb8d18cff29c152581db9a32b3903de9df948079985a706ee056f549472b3f1

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-16T18:28:33.277442Z digest=sha256:0417dea9c40d2f8faec2f1ab26986246479e1100a34cd82a8501241717af4852

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=sha256:488c4001f3039f809f211cd4d8c2f550f745434fe1903559492f0a990a6f2c9c

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T18:00:20.216268Z digest=sha256:1bc655d1b611f0b9ca81c6536caee496a9c20cf84b0d31f844988258ae868ef5

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-10T18:30:00.400451Z digest=sha256:2ffead3cdf6da7c4c57a79e1d1a8e36948c8af12b816360d6d19175c2934c3f0

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-08T04:29:22.477531Z digest=sha256:567123aead44a267b11a2cc23377e0865776ca5ce82ca1030347a7c2231aef2d

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-14T20:55:38.841743Z digest=sha256:b9c840095de7ca359a2154718211cc4e9230c3c6b6caed486c0c1c08d5737286

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-08T15:45:27.700503Z digest=sha256:b9f4e6fb78156aacf9b2ee41956159d4a0fc07f9178616e2a3b159178cf162b5

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-13T01:25:42.059685Z digest=sha256:9f2c6ca1c500b448835715dfc271d81ea43ae336f828671a3fe560efddde24c5

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-14T19:33:48.787673Z digest=sha256:6a8dfa485937817e56f6ed9cd9107012fba1392989152560a8614ef55d44360e

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-01T08:40:29.728679Z digest=sha256:2e11d371205f4ca3bf587c382f51fcca673dac99b8d005dea3bdfaf5ec0539ae

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-27T03:49:42.112919Z digest=sha256:e5b7104aeb4898f587a3942fc8c126fd976188d9ab31199e07d9392abb2ef737

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-30T08:39:12.222916Z digest=sha256:0f450765afe04e8dbbd67868788f542b730bec420a16ee79474847ad89b3504c

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-01T05:25:10.409645Z digest=sha256:135f2d4a8c769e9cb736fd0dde7aba4451b72d0da45d31a9cfb8532e5066ffc5

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