Paper Citation Record · LEDGER

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities

As of 22 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 2 inbound Pith citation observations for arXiv:2505.09477.

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

pith.paper-citation-record.v1
2505.09477 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:34:49.618516Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T17:18:38.294448Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T17:20:10.478658Z

Reference resolution

40 of 40 outbound references displayed

verified exact1
verified fuzzy20
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1b5a3cb1-1139-4a0d-a6eb-b0343e31eaf2 · outbound

This paper cites Sayplan: Grounding large language models using 3d scene graphs for scalable task planning,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Sayplan: Grounding large language models using 3d scene graphs for scalable task planning,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:50.013786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cc8c68da-4b87-4f3c-bfb1-b735beb3933c · outbound

This paper cites Driving everywhere with large language model policy adaptation,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Driving everywhere with large language model policy adaptation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:50.003574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5b3fd3c8-676d-4ef2-9d55-16425c14b39f · outbound

This paper cites Deploying and evaluating llms to program service mobile robots,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Deploying and evaluating llms to program service mobile robots,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.994064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f208a42d-6ff6-4adc-8b09-15188c008a23 · outbound

This paper cites SPINE: Online Semantic Planning for Missions with Incomplete Natural Language Specifications in Unstructured Environments.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities SPINE: Online Semantic Planning for Missions with Incomplete Natural Language Specifications in Unstructured Environments

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.488678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d61549a3-7df5-48e9-99e1-f50bfbdb6134 · outbound

This paper cites Code as Policies: Language Model Programs for Embodied Control.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Code as Policies: Language Model Programs for Embodied Control

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.492773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c68ea41-1aae-4908-a609-810ff8d6ec8b · outbound

This paper cites Grounding Complex Natural Language Commands for Temporal Tasks in Unseen Environments.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Grounding Complex Natural Language Commands for Temporal Tasks in Unseen Environments

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.496792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5bde3ac-8475-4198-a63b-e25eddb89384 · outbound

This paper cites Language-Grounded Dynamic Scene Graphs for Interactive Object Search with Mobile Manipulation.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Language-Grounded Dynamic Scene Graphs for Interactive Object Search with Mobile Manipulation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.500903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec75d00f-ecb6-4550-b1b1-3867a0dddf46 · outbound

This paper cites Rea- soning about the unseen for efficient outdoor object navigation,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Rea- soning about the unseen for efficient outdoor object navigation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.984412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f8658388-57f4-42e7-b3b2-2550200c5a12 · outbound

This paper cites Robohop: Segment-based topological map representation for open-world visual navigation,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Robohop: Segment-based topological map representation for open-world visual navigation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.974268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0fe28834-c530-4f06-8210-8e5255bc4acd · outbound

This paper cites Navigation with large language models: Semantic guesswork as a heuristic for planning,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Navigation with large language models: Semantic guesswork as a heuristic for planning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.963581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 26592f45-b3a3-4004-8da7-1f8132846da8 · outbound

This paper cites Lm-nav: Robotic navigation with large pre-trained models of language, vision, and action,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Lm-nav: Robotic navigation with large pre-trained models of language, vision, and action,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.944603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c117a5e0-4d44-4891-a34e-3843bb1516fb · outbound

This paper cites Inner Monologue: Embodied Reasoning through Planning with Language Models.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Inner Monologue: Embodied Reasoning through Planning with Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.521533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15d1fd50-81f7-49e2-b6bd-1dc3c4cbca35 · outbound

This paper cites ViKiNG: Vision-Based Kilometer-Scale Nav- igation with Geographic Hints,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities ViKiNG: Vision-Based Kilometer-Scale Nav- igation with Geographic Hints,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.934943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f5f5a1bc-6726-4ab0-a039-8e9d0fe463ca · outbound

This paper cites NEUSIS: A Compositional Neuro-Symbolic Framework for Autonomous Perception, Reasoning, and Planning in Complex UAV Search Missions.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities NEUSIS: A Compositional Neuro-Symbolic Framework for Autonomous Perception, Reasoning, and Planning in Complex UAV Search Missions

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.528793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1ce408c-1f08-4a2d-84b9-4066e83c8803 · outbound

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

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Aerialvln: Vision-and-language navigation for uavs,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.924352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 54540640-499a-4f8b-971a-e86eb1c9b6bc · outbound

This paper cites Landmark-rxr: Solving vision-and-language navigation with fine- grained alignment supervision,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Landmark-rxr: Solving vision-and-language navigation with fine- grained alignment supervision,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.535748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 877af2c5-fa10-48dc-9ba0-1dadaa24a435 · outbound

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

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Exploring Spatial Representation to Enhance LLM Reasoning in Aerial Vision-Language Navigation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.538830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a74605b8-715f-4981-98d6-cd0c14786403 · outbound

This paper cites Air-ground col- laboration for language-specified missions in unknown environments,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Air-ground col- laboration for language-specified missions in unknown environments,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.908630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 83c874b7-053d-46e6-b424-ac8a283f2988 · outbound

This paper cites Faster- lio: Lightweight tightly coupled lidar-inertial odometry using parallel sparse incremental voxels,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Faster- lio: Lightweight tightly coupled lidar-inertial odometry using parallel sparse incremental voxels,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.545409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e617236c-b624-41de-8a59-2ab36339cc36 · outbound

This paper cites Groundgrid: Lidar point cloud ground segmentation and terrain estimation,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Groundgrid: Lidar point cloud ground segmentation and terrain estimation,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.548824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1dea912-9793-47b7-a55a-d6f033fd75b8 · outbound

This paper cites EvMAPPER: High Altitude Orthomapping with Event Cameras.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities EvMAPPER: High Altitude Orthomapping with Event Cameras

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-15T21:34:49.724658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 23b60954-ca1d-47f9-9aee-f07c3232282f · outbound

This paper cites Enabling Large-scale Heterogeneous Collaboration with Opportunistic Communications,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Enabling Large-scale Heterogeneous Collaboration with Opportunistic Communications,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.887077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d09a2425-90c3-4db4-a554-94d7907d54ff · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities LoRA: Low-Rank Adaptation of Large Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.559278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb11f12a-2391-4028-b70f-ecb2de356243 · outbound

This paper cites Stronger together: Air-ground robotic collaboration using semantics,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Stronger together: Air-ground robotic collaboration using semantics,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.876534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2df526f0-bb73-4348-9498-319753673ff8 · outbound

This paper cites Grounded sam: Assembling open-world models for diverse visual tasks,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Grounded sam: Assembling open-world models for diverse visual tasks,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.573329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6842b35-3641-41d8-870e-0ad757a6a43e · outbound

This paper cites Opportunistic commu- nication in robot teams,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Opportunistic commu- nication in robot teams,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.860224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9bf217e1-6d5e-4ccc-b9ca-5d2a1728d484 · outbound

This paper cites Evaluating Real-World Robot Manipulation Policies in Simulation.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Evaluating Real-World Robot Manipulation Policies in Simulation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.580259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e37daab-0c45-4088-a034-04618608981e · outbound

This paper cites Open X-Embodiment: Robotic Learning Datasets and RT-X Models.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Open X-Embodiment: Robotic Learning Datasets and RT-X Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.583920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 696f0234-dd4f-4f68-a47f-b040555aa804 · outbound

This paper cites SANPO: A Scene Understanding, Accessibility and Human Navigation Dataset.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities SANPO: A Scene Understanding, Accessibility and Human Navigation Dataset

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.586932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8b547d9-e343-47f7-a50d-9d560f9d3bae · outbound

This paper cites Gibson env: Real-world perception for embodied agents,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Gibson env: Real-world perception for embodied agents,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.850987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 540b8887-1248-4106-a7a4-d9e7ef391aab · outbound

This paper cites Hm3d- ovon: A dataset and benchmark for open-vocabulary object goal navigation,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Hm3d- ovon: A dataset and benchmark for open-vocabulary object goal navigation,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.841285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 90954da1-c263-4240-ba2c-5b8e8c0fc839 · outbound

This paper cites Matterport3D: Learning from RGB-D Data in Indoor Environments.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Matterport3D: Learning from RGB-D Data in Indoor Environments

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.597013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2186306f-e4f6-45fb-a042-625291f845ff · outbound

This paper cites Robothor: An open simulation-to-real embodied ai platform,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Robothor: An open simulation-to-real embodied ai platform,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.830611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f2a55530-da90-496c-83cb-e479244adcae · outbound

This paper cites Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.604071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac2a5530-4246-4eec-967c-638d2c11ac7b · outbound

This paper cites Large-scale autonomous flight with real-time semantic slam under dense forest canopy,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Large-scale autonomous flight with real-time semantic slam under dense forest canopy,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.820885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d6a59954-caec-4187-9b29-896d1fa8ce46 · outbound

This paper cites Learning quadrupedal locomotion over challenging terrain,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Learning quadrupedal locomotion over challenging terrain,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.611503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c466ab7d-a139-410b-a0d9-bc3dce922887 · outbound

This paper cites Proprioception Is All You Need: Terrain Classification for Boreal Forests,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Proprioception Is All You Need: Terrain Classification for Boreal Forests,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.805491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 32a0723a-b2a5-4df2-914f-1322a98d47e4 · outbound

This paper cites Nebula: Quest for robotic autonomy in challenging environments; team costar at the darpa subterranean challenge,.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Nebula: Quest for robotic autonomy in challenging environments; team costar at the darpa subterranean challenge,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.795477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ab84d792-3235-49ec-b55b-8a173f5e34b8 · outbound

This paper cites 2683–2699.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities 2683–2699

Reference 229

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:34:49.954147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e71fa4cf-0378-462e-b755-b293c2c054a7 · outbound

This paper cites The Llama 3 Herd of Models.

Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities The Llama 3 Herd of Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:49.566479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 36245eee-8bd2-447c-931b-969ea5d49886 · inbound

CoFL: Continuous Flow Fields for Language-Conditioned Navigation cites this paper.

CoFL: Continuous Flow Fields for Language-Conditioned Navigation Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-15T17:20:10.481527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5acc5e50-ece6-4841-ad44-52aa2838bce5 · inbound

The Unified Autonomy Stack: Toward a Blueprint for Generalizable Robot Autonomy cites this paper.

The Unified Autonomy Stack: Toward a Blueprint for Generalizable Robot Autonomy Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities

Reference 270

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T19:42:53.489812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.