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Paper Citation Record · LEDGER

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents

As of 20 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2607.22014.

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

pith.paper-citation-record.v1
2607.22014 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T06:06:27.053550Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

33 of 33 outbound references displayed

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Outbound references

Observation ec3cfbd5-58ee-42ba-944d-d30c22f1dadc · outbound

This paper cites Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

Reference 1

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source=arxiv_source observed=2026-08-01T06:06:22.205940Z digest=sha256:f8fd67181f0927f0d62782461ba9ca9844afcc5805812396927dbcfa43b23664

Observation dd4230a2-8678-4e8b-aeb3-9715c914ba81 · outbound

This paper cites Vision-and-language navigation: Interpreting visually-grounded navigation instructions in real environments.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Vision-and-language navigation: Interpreting visually-grounded navigation instructions in real environments

Reference 2

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source=arxiv_source observed=2026-08-01T06:06:22.322113Z digest=sha256:19c9a3a6f0eaaf1dbc5cd8d1dc21d7676491f3f9654f3d58ef1175ac7ab1abaa

Observation 55877264-052d-4d56-9c15-4298c5c30555 · outbound

This paper cites ObjectNav Revisited: On Evaluation of Embodied Agents Navigating to Objects.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents ObjectNav Revisited: On Evaluation of Embodied Agents Navigating to Objects

Reference 3

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source=arxiv_source observed=2026-08-01T06:06:22.509088Z digest=sha256:ff3a6c40538f72736e03a717269f215f8d0232c6c8d04a9f18e42e32a994a7fe

Observation 341f4d76-c855-42a0-9518-a5f3b5ef1247 · outbound

This paper cites Neusis: A compositional neuro-symbolic framework for autonomous perception, reasoning, and planning in complex uav search missions.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Neusis: A compositional neuro-symbolic framework for autonomous perception, reasoning, and planning in complex uav search missions

Reference 4

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source=arxiv_source observed=2026-08-01T06:06:22.619852Z digest=sha256:d76a93fa5cac99117e85b188d204dfee4e94fb76051ea093912527a2f69b417a

Observation 2ed5fccc-e570-4c51-93a3-696004f56dfa · outbound

This paper cites TypeFly: Flying Drones with Large Language Model.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents TypeFly: Flying Drones with Large Language Model

Reference 5

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source=arxiv_source observed=2026-08-01T06:06:22.727891Z digest=sha256:5628c7235978a58ad606dc7d65e3687bcb737fc9dd27d84c8b7b20baa453194d

Observation 79160368-0112-47d0-b764-c75123e98fe3 · outbound

This paper cites NaVILA: Legged Robot Vision-Language-Action Model for Navigation.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents NaVILA: Legged Robot Vision-Language-Action Model for Navigation

Reference 6

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source=arxiv_source observed=2026-08-01T06:06:22.870692Z digest=sha256:c0bfaca452d2ea8019daea0db9761243adfc2518859f6486379920ad8c54e2d1

Observation 0388e1fc-4596-40cf-8314-14968ac96602 · outbound

This paper cites Spatialrgpt: Grounded spatial reasoning in vision-language models.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Spatialrgpt: Grounded spatial reasoning in vision-language models

Reference 7

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source=arxiv_source observed=2026-08-01T06:06:22.985428Z digest=sha256:141ac8d66084f56751e0e3d4db7da4ce3a6fe6a3bb9f566579a61427fcf6c2bc

Observation 41aac132-8697-40a7-a404-378f641a0870 · outbound

This paper cites PaLM-E: An Embodied Multimodal Language Model.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents PaLM-E: An Embodied Multimodal Language Model

Reference 8

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source=arxiv_source observed=2026-08-01T06:06:23.128305Z digest=sha256:cec91f760703afb2260a20326197d98ee49fa61857bcb5cae9430e707460b5c2

Observation fa6551c9-4ffc-4983-9dfd-87b21718a2f8 · outbound

This paper cites Unreal engine, 2019.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Unreal engine, 2019

Reference 9

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source=arxiv_source observed=2026-08-01T06:06:23.243971Z digest=sha256:b8f77ae97a95d1a897f4a6f9db51a0aa0d48359f20d2a33b8de935d487f0b175

Observation 58f257f1-a520-42af-ba85-2c237643191f · outbound

This paper cites Aerial vision-and-dialog navigation.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Aerial vision-and-dialog navigation

Reference 10

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source=arxiv_source observed=2026-08-01T06:06:23.341555Z digest=sha256:9aed7f5e069e1a36dee146fb64422ed9e6fa1c83ab2e53fd132a2fe5c681f0e0

Observation cac186aa-430b-4d77-8fcb-aca6c0da8293 · outbound

This paper cites Openfly: A comprehensive platform for aerial vision-language navigation.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Openfly: A comprehensive platform for aerial vision-language navigation

Reference 11

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source=arxiv_source observed=2026-08-01T06:06:23.519409Z digest=sha256:d621e9d989df294395110df9e4bf48dffcd448078132c6363cb9a4d2b65600e9

Observation a7591919-e997-4f45-9756-87227c45556a · outbound

This paper cites Bedi: A comprehensive benchmark for evaluating embodied agents on uavs.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Bedi: A comprehensive benchmark for evaluating embodied agents on uavs

Reference 12

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source=arxiv_source observed=2026-08-01T06:06:23.671626Z digest=sha256:2aa09a8bfea647ec4ec6d9a02ca86330f0332a5b92d9c6d34c26024ac83883dc

Observation 1ed93ec9-34f6-4db4-a6a8-9be470d5fc34 · outbound

This paper cites See, point, fly: A learning-free vlm framework for universal unmanned aerial navigation.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents See, point, fly: A learning-free vlm framework for universal unmanned aerial navigation

Reference 13

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source=arxiv_source observed=2026-08-01T06:06:23.823269Z digest=sha256:d6e38baca387db2a11e8277753d436ab658f8b8181de3c860b836019de1beca7

Observation a6053d50-668a-412c-ada4-3a4e7ab9432a · outbound

This paper cites Cosys-airsim: a real-time simulation framework expanded for complex industrial applications.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Cosys-airsim: a real-time simulation framework expanded for complex industrial applications

Reference 14

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source=arxiv_source observed=2026-08-01T06:06:24.040848Z digest=sha256:78ca045f37f5461a9ec0d06131df7161e31b8e0e780579ecf6c98ca4088cced9

Observation 3042a8fa-1ab6-4309-b836-960f98916f4f · outbound

This paper cites Citynav: A large-scale dataset for real-world aerial navigation.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Citynav: A large-scale dataset for real-world aerial navigation

Reference 15

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source=arxiv_source observed=2026-08-01T06:06:24.167344Z digest=sha256:587471b4e46559352e923e28d70491d0dacc55b621697e75f82c205e0c158022

Observation db3ba871-0065-467d-817a-1fce14300f3e · outbound

This paper cites Aerialvln: Vision-and-language navigation for uavs.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Aerialvln: Vision-and-language navigation for uavs

Reference 16

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source=arxiv_source observed=2026-08-01T06:06:24.344583Z digest=sha256:83b486a83ae36ee39394b8d34b79eee2401c8f6497311de6d91f6b415955f116

Observation 1d9a592b-4f78-470f-942b-46595d1d0917 · outbound

This paper cites Unmanned aerial vehicles (uavs): Practical aspects, applications, open challenges, security issues, and future trends.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Unmanned aerial vehicles (uavs): Practical aspects, applications, open challenges, security issues, and future trends

Reference 17

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source=arxiv_source observed=2026-08-01T06:06:24.527579Z digest=sha256:fc6ca93e265d88cc0da691cc39427b04b1a1d5cb8416d95b99624fde7b62f5c6

Observation 5bfd415c-c03d-4bc1-af1f-c1307428d40e · outbound

This paper cites Flysearch: Exploring how vision-language models explore.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Flysearch: Exploring how vision-language models explore

Reference 18

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source=arxiv_source observed=2026-08-01T06:06:24.709694Z digest=sha256:c2a5a95146d7211c5404c9aa2e175b63a7b072a591a6799793d111b256e00411

Observation 65f50460-9375-4870-923e-b787ec04db13 · outbound

This paper cites Unrealcv: Virtual worlds for computer vision.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Unrealcv: Virtual worlds for computer vision

Reference 19

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source=arxiv_source observed=2026-08-01T06:06:24.825591Z digest=sha256:5f8f3780918be970900d170287d281e9d1e80f251a93d51e3c197ee44e6a0e74

Observation 67979c39-150b-4e7a-8a17-e4836295b2f8 · outbound

This paper cites Airsim: High-fidelity visual and physical simulation for autonomous vehicles.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Airsim: High-fidelity visual and physical simulation for autonomous vehicles

Reference 20

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source=arxiv_source observed=2026-08-01T06:06:25.002520Z digest=sha256:3469de53e4a0e05dd70d863f028ad3eee1d7d5171be37675a76ae73e6f03935a

Observation dbf39903-e55b-408f-bb48-57a0b77cf14a · outbound

This paper cites Unmanned aerial vehicles (uavs): A survey on civil applications and key research challenges.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Unmanned aerial vehicles (uavs): A survey on civil applications and key research challenges

Reference 21

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source=arxiv_source observed=2026-08-01T06:06:25.128108Z digest=sha256:4d6bdb8aad7a6027850b3c9da8c0151b72908561f15fcd314d16dbba949798bc

Observation a7a5c4a5-db10-4761-8417-62f3f3a5439a · outbound

This paper cites Alfred: A benchmark for interpreting grounded instructions for everyday tasks.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Alfred: A benchmark for interpreting grounded instructions for everyday tasks

Reference 22

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source=arxiv_source observed=2026-08-01T06:06:25.278237Z digest=sha256:68617e5b8db648b0e39ae59c061994a8d9c2df95fc4b6ea1bf1a1fddd532e6d4

Observation 04f9071a-34e7-4df7-80e4-be0ed12d917a · outbound

This paper cites UAVs meet LLMs : Overviews and perspectives toward agentic low-altitude mobility, 2025.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents UAVs meet LLMs : Overviews and perspectives toward agentic low-altitude mobility, 2025

Reference 23

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source=arxiv_source observed=2026-08-01T06:06:25.426013Z digest=sha256:97a11463a8d80a96c64d358cf677ab59f6a8bfe3e138378799c28949c5acce4f

Observation f67ef22f-c96e-496b-9fed-e703bb4050c4 · outbound

This paper cites Cambrian-1: A fully open, vision-centric exploration of multimodal llms.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Cambrian-1: A fully open, vision-centric exploration of multimodal llms

Reference 24

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source=arxiv_source observed=2026-08-01T06:06:25.547686Z digest=sha256:433bed57074635a5d7bacc79cab8bcfebe890f3e12c4820f56b59f6e1d926cad

Observation 974fd98a-3256-4475-81d7-60bc26bff0d8 · outbound

This paper cites Towards realistic uav vision-language navigation: Platform, benchmark, and methodology.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Towards realistic uav vision-language navigation: Platform, benchmark, and methodology

Reference 25

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source=arxiv_source observed=2026-08-01T06:06:25.666211Z digest=sha256:80b5ddb6522f4dbbb043bc5738aeecf455456594a974bb03a80baf8e5f1cbd93

Observation 5fd02f4f-3bd6-4d32-afbe-ea66ab9d1f71 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Chain-of-thought prompting elicits reasoning in large language models

Reference 26

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source=arxiv_source observed=2026-08-01T06:06:25.860668Z digest=sha256:28001546149986ee305bc85ce368dc0310e515d606ebe4a1f73ccf1a83fd7b7e

Observation 5a64412e-eeb4-4797-b757-92ac34df7be0 · outbound

This paper cites Uav-on: A benchmark for open-world object goal navigation with aerial agents.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Uav-on: A benchmark for open-world object goal navigation with aerial agents

Reference 27

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source=arxiv_source observed=2026-08-01T06:06:26.055345Z digest=sha256:4bfe225baeea67e10621ee78ebfe23fb5b34098de25cd59a1744c2981d353bd8

Observation 7d98032a-5083-4a3e-bf17-822cd8fe2055 · outbound

This paper cites Aeroverse: Uav-agent benchmark suite for simulating, pre-training, finetuning, and evaluating aerospace embodied world models.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Aeroverse: Uav-agent benchmark suite for simulating, pre-training, finetuning, and evaluating aerospace embodied world models

Reference 28

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source=arxiv_source observed=2026-08-01T06:06:26.183336Z digest=sha256:6b2e551f47208880a53cd88c52cab94a331df15a2a7b5d36d92f0f5e863a69e3

Observation 523e0590-29fe-44c9-b6c2-695bdb17d436 · outbound

This paper cites ESARBench: A Benchmark for Agentic UAV Embodied Search and Rescue.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents ESARBench: A Benchmark for Agentic UAV Embodied Search and Rescue

Reference 29

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source=arxiv_source observed=2026-08-01T06:06:26.379840Z digest=sha256:c9601b90eeb13515f11b1d0647c65ee9e4d78515298daf13113304135e1d4bc2

Observation bfaa9010-c4e0-4e65-9d65-3ddcf053f311 · outbound

This paper cites NaVid: Video-based VLM Plans the Next Step for Vision-and-Language Navigation.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents NaVid: Video-based VLM Plans the Next Step for Vision-and-Language Navigation

Reference 30

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source=arxiv_source observed=2026-08-01T06:06:26.559465Z digest=sha256:50872363b44e5d0c87e48a508f9d1b8207a2d9bff8968878c849ca374cdf0b5b

Observation 3e1e7f5a-c240-4266-a3ac-94ed28ff8bd1 · outbound

This paper cites Is your vlm sky-ready? a comprehensive spatial intelligence benchmark for uav navigation.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Is your vlm sky-ready? a comprehensive spatial intelligence benchmark for uav navigation

Reference 31

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source=arxiv_source observed=2026-08-01T06:06:26.720238Z digest=sha256:ccea14b457f7df08fb8a5320a7543e70d7fe480aa7f8ef484b0abe026bf50d9f

Observation cab63ab8-972c-40ff-b6d4-ff9bb840a4ff · outbound

This paper cites Towards learning a generalist model for embodied navigation.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Towards learning a generalist model for embodied navigation

Reference 32

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source=arxiv_source observed=2026-08-01T06:06:26.882286Z digest=sha256:efb9cc99aae73e79a6b54d5f4a64a421dad3d92def6c31f62669193fcfe396bd

Observation c9dd02ac-605d-438f-97c7-8314f87ef883 · outbound

This paper cites Navgpt-2: Unleashing navigational reasoning capability for large vision-language models.

Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents Navgpt-2: Unleashing navigational reasoning capability for large vision-language models

Reference 33

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source=arxiv_source observed=2026-08-01T06:06:27.053550Z digest=sha256:9bca132e20e741f7610cd9212e5599d2ff81a9bfa70910fe633fbc4c5945697c

Pith citing papers

No inbound Pith citation observations are available.