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Paper Citation Record · LEDGER

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning

As of 17 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 7 inbound Pith citation observations for arXiv:2505.07236.

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

pith.paper-citation-record.v1
2505.07236 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:24:51.010403Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:14:00.925442Z

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

22 of 22 outbound references displayed

  • verified exact0
  • verified fuzzy8
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 64a2a88e-ba39-4db7-9d25-85b227a03675 · outbound

This paper cites AI meets UA Vs: A survey on AI empowered UA V perception systems for precision agriculture,.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning AI meets UA Vs: A survey on AI empowered UA V perception systems for precision agriculture,

Reference 1

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source=pdf_text observed=2026-08-15T22:24:50.887446Z digest=sha256:9827a40bbde406718c89080eb8fa6db775c620f560a62c4c8cbb29e5b55d5ff8

Observation d1bb80fd-9ffc-4e89-a0c5-c587ed8db32f · outbound

This paper cites Unmanned aerial vehicles for search and rescue: A survey,.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning Unmanned aerial vehicles for search and rescue: A survey,

Reference 2

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source=pdf_text observed=2026-08-15T22:24:50.892928Z digest=sha256:d6cdea51f2c32d05a3aede7cbe1c9e4269b3ae2b7296be600a8c35b71cbc1276

Observation f29459af-709c-4090-9431-31789f98bb7d · outbound

This paper cites FlightAR: AR flight assistance interface with multiple video streams and object detection aimed at immersive drone control,.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning FlightAR: AR flight assistance interface with multiple video streams and object detection aimed at immersive drone control,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:50.897874Z digest=sha256:40ef2dfabcab1de4b2387c87055d2de40bc7f932904457e24b9d44aa788d7d2b

Observation 268e5e01-9b7a-49d8-8f6d-031e17dd97d9 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 4

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source=pdf_text observed=2026-08-15T22:24:50.902583Z digest=sha256:e453a7a044bbd338ed6b66275bc736f597031a831e5f16f14c4714dc18701a7d

Observation d90bc7b3-f9fb-4006-b97e-c7118e9b6df2 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion,.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning Learning transferable visual models from natural language supervi- sion,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:50.911756Z digest=sha256:89dc9c08329c1aff3305e5f892a1394684d5a73e81de3348695deb6e7f3eba5e

Observation ccc5ffe8-daa1-47e4-b72a-8262b99a4653 · outbound

This paper cites GPT-4 Technical Report.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning GPT-4 Technical Report

Reference 6

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source=pdf_text observed=2026-08-15T22:24:50.917566Z digest=sha256:bbc49f56889302fb14d6f7dbd57f7595173f7fc15e75538e8a059a216a1e5c18

Observation 8922b4e7-ea0e-474d-bfac-a2705f831682 · outbound

This paper cites AerialVLN: Vision-and-language navigation for UA Vs,.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning AerialVLN: Vision-and-language navigation for UA Vs,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:50.922974Z digest=sha256:ff531cd702e9aa7f4788d86536ed05ab375782d954219d3f9640cfd541654c16

Observation 368c3553-4e65-4200-96e6-9797f8b02a3f · outbound

This paper cites Aerial vision-and-dialog navigation,.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning Aerial vision-and-dialog navigation,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:50.928301Z digest=sha256:9fb93e70596f7abe4543b0eb82d274b12f09310ba8e09af65bcf4eb47a868086

Observation de7718d3-9591-4e7b-9802-4f695ecf6d05 · outbound

This paper cites Towards Realistic UAV Vision-Language Navigation: Platform, Benchmark, and Methodology.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning Towards Realistic UAV Vision-Language Navigation: Platform, Benchmark, and Methodology

Reference 9

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source=pdf_text observed=2026-08-15T22:24:50.936775Z digest=sha256:b2f80b6a4e452df48b13035a4c24d5d42224fe384013a43ed4010c0c9337fe43

Observation 4d79d272-afaf-44b7-991b-c5bc255eb7ef · outbound

This paper cites Exploring Spatial Representation to Enhance LLM Reasoning in Aerial Vision-Language Navigation.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning Exploring Spatial Representation to Enhance LLM Reasoning in Aerial Vision-Language Navigation

Reference 10

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source=pdf_text observed=2026-08-15T22:24:50.942826Z digest=sha256:b39e3916fa9514f643ea762e63dfe2110c15e58e25bb935d4d10f40324bac01a

Observation 19eb2e92-91e3-497e-bf53-b31c0ec703a9 · outbound

This paper cites EmbodiedCity: Embodied aerial agent for city-level visual language navigation using large language model,.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning EmbodiedCity: Embodied aerial agent for city-level visual language navigation using large language model,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:50.949566Z digest=sha256:6873004dab9f859b87f321e6dfb81412b99e76158d72708e67b73cf4c14f9415

Observation 19d21cac-a0d5-4ba6-a9fd-44cfe87f4f20 · outbound

This paper cites MorphoNavi: Aerial-Ground Robot Navigation with Object Oriented Mapping in Digital Twin.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning MorphoNavi: Aerial-Ground Robot Navigation with Object Oriented Mapping in Digital Twin

Reference 12

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source=pdf_text observed=2026-08-15T22:24:50.956127Z digest=sha256:cf3bf33618340e053a519b6e6d5df1967c35111c62ed919c913987c1ab69563d

Observation 3443681f-cabf-4196-b396-894c3729b83c · outbound

This paper cites CognitiveDrone: A VLA Model and Evaluation Benchmark for Real-Time Cognitive Task Solving and Reasoning in UAVs.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning CognitiveDrone: A VLA Model and Evaluation Benchmark for Real-Time Cognitive Task Solving and Reasoning in UAVs

Reference 13

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source=pdf_text observed=2026-08-15T22:24:50.963339Z digest=sha256:7831a31af3706630a2df2bed18168bd959ab50a2627ddf93d7a8244013bb72e7

Observation 761c545d-d228-4077-a990-2cd1adbb7c13 · outbound

This paper cites UA V-VLA: Vision-language-action system for large scale aerial mission generation,.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning UA V-VLA: Vision-language-action system for large scale aerial mission generation,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:50.968129Z digest=sha256:6ca092e56180775c9bd0e476f6d25642cf06c34892cc8bf003a16b7ee5df1a63

Observation 58152ffd-8df5-4107-a935-34bbe873c1a8 · outbound

This paper cites UAV-VLPA*: A Vision-Language-Path-Action System for Optimal Route Generation on a Large Scales.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning UAV-VLPA*: A Vision-Language-Path-Action System for Optimal Route Generation on a Large Scales

Reference 15

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source=pdf_text observed=2026-08-15T22:24:50.973253Z digest=sha256:2a11c6b44af6b29a62277a42c06ef6b44a41d808dfdd6be7fbe9fa16f1192b2e

Observation 478cf7c9-a502-4a1e-aba9-76dd15d80e2f · outbound

This paper cites UAV-VLRR: Vision-Language Informed NMPC for Rapid Response in UAV Search and Rescue.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning UAV-VLRR: Vision-Language Informed NMPC for Rapid Response in UAV Search and Rescue

Reference 16

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source=pdf_text observed=2026-08-15T22:24:50.978097Z digest=sha256:ada86c6806dd0d839884be17975feba80f26856cc6105d612d076779afe6f3b4

Observation 51712254-2bd4-40b3-86d9-f10f470342ff · outbound

This paper cites RaceVLA: VLA-based Racing Drone Navigation with Human-like Behaviour.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning RaceVLA: VLA-based Racing Drone Navigation with Human-like Behaviour

Reference 17

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source=pdf_text observed=2026-08-15T22:24:50.984662Z digest=sha256:b6fd4927a7830c239e491f45ba3a139f3af9a7004c6495a4120b1d6177a9b9e5

Observation 9d85ffba-1bc7-47f1-bef7-6fdfc4ea0f3c · outbound

This paper cites OpenVLA: An Open-Source Vision-Language-Action Model.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning OpenVLA: An Open-Source Vision-Language-Action Model

Reference 18

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source=pdf_text observed=2026-08-15T22:24:50.989131Z digest=sha256:23cbba327b71f7c7050df5791e4ab5018b241e618f581861658d7a070a380e7d

Observation 25fbafcf-8321-449d-8333-2bd89ba24630 · outbound

This paper cites MiniVLA: A better VLA with a smaller footprint,.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning MiniVLA: A better VLA with a smaller footprint,

Reference 19

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:50.993473Z digest=sha256:d2b5f1be5d36c782b984c0e53095ecabbdd223b40bf7745e9eb6219f48ac2cf2

Observation 3d3221cd-a7f8-41f4-af64-a55ae24d57cb · outbound

This paper cites Swarm-GPT: Combining Large Language Models with Safe Motion Planning for Robot Choreography Design.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning Swarm-GPT: Combining Large Language Models with Safe Motion Planning for Robot Choreography Design

Reference 20

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source=pdf_text observed=2026-08-15T22:24:50.999118Z digest=sha256:6857a1f4e66eb3827b504696d1b49252e55a779fbd2636a8a384823feb2123a0

Observation 1a481531-c5dd-4f41-8384-1ff230af0373 · outbound

This paper cites FlockGPT: Guiding UA V flocking with linguistic orchestration,.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning FlockGPT: Guiding UA V flocking with linguistic orchestration,

Reference 21

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:51.005874Z digest=sha256:3d1e0530fcdaeb82718e9cdbb29683adf0fe2ab3e5833e9cef2db495ed88ccd5

Observation 01dfad5d-239e-42ab-8bf8-3a027cd756ac · outbound

This paper cites WildfireGPT: Tailored Large Language Model for Wildfire Analysis.

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning WildfireGPT: Tailored Large Language Model for Wildfire Analysis

Reference 22

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source=pdf_text observed=2026-08-15T22:24:51.010403Z digest=sha256:1df86c83ce12f8855f10902c585d9dd135236cf504d1e7fbba4255755598d9f7

Pith citing papers

Observation e701cfc2-9ea8-4976-a052-179060a917c9 · inbound

From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications cites this paper.

From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning

Reference 185

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source=pdf_text observed=2026-08-07T13:14:00.925442Z digest=sha256:eb26eaad8e34aca8112ff08da42b13cef8cdbdb3b65c2d5d8c6c26b9b45f83d6

Observation e727097f-45a2-4f04-87f8-2d9b519b891c · inbound

UAVs Meet Agentic AI: A Multidomain Survey of Autonomous Aerial Intelligence and Agentic UAVs cites this paper.

UAVs Meet Agentic AI: A Multidomain Survey of Autonomous Aerial Intelligence and Agentic UAVs UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning

Reference 14

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source=pdf_text observed=2026-08-07T05:47:56.900062Z digest=sha256:c63674dcc42d29169ebd52119ac2b50f96eb4d0340f690510c2a5df9d20bf1c6

Observation 6ed34466-d0c6-4b1a-973b-121b6b1e99e3 · inbound

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

Agentic AI in Remote Sensing: Foundations, Taxonomy, and Emerging Systems UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning

Reference 108

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arxiv_id, observed 2026-05-16T18:31:10.833701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-16T18:28:33.277442Z digest=sha256:ef46790c08ec4376e5d5fcd7780915ba81441c4e871cd3d69143bc74240624b5

Observation 0bbcda29-aa6b-4f0a-8960-e729a406474b · inbound

QuadAgent: A Responsive Agent System for Vision-Language Guided Quadrotor Agile Flight cites this paper.

QuadAgent: A Responsive Agent System for Vision-Language Guided Quadrotor Agile Flight UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning

Reference 7

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arxiv_id, observed 2026-05-13T20:18:13.172615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-13T20:16:36.843013Z digest=sha256:5f67b999e29a452e3b3cabce0f269ecbcda8cab7c731b94c2344518c426032cd

Observation a9efad98-8ff5-440e-a6fb-fc07c61ff70b · inbound

Vision-Language Navigation for Aerial Robots: Towards the Era of Large Language Models cites this paper.

Vision-Language Navigation for Aerial Robots: Towards the Era of Large Language Models UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning

Reference 35

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arxiv_id, observed 2026-05-11T00:45:49.958062Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T18:20:12.463846Z digest=sha256:d0d011f7e188a100b5b9a6a2e2b22ed061e95e780b2d08cc0d8e7854fc02ada1

Observation 8e9cae50-796c-4c7c-921e-0c981a762219 · inbound

PEACE: A Planner-Executor Agent with Constraint Enforcement for UAVs cites this paper.

PEACE: A Planner-Executor Agent with Constraint Enforcement for UAVs UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning

Reference 17

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arxiv_id, observed 2026-06-29T16:53:40.404017Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-29T16:53:17.504094Z digest=sha256:1ac7508d6d6452fe52456296d0cdd4211d86f77bc39e7e7e772484ea8da136ce

Observation a9f1fdd1-4a61-491e-879c-f6dd7dbe4190 · inbound

MultiUAV-Plat: An LLM-Oriented Platform, Benchmark and Framework for Multi-UAV Collaborative Task Planning cites this paper.

MultiUAV-Plat: An LLM-Oriented Platform, Benchmark and Framework for Multi-UAV Collaborative Task Planning UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning

Reference 22

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arxiv_id, observed 2026-07-01T06:15:26.643913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-07-01T06:09:22.431356Z digest=sha256:833965379cf25bd0ecd58628434060f0b115c60e8634316ff009cffb013e5946