Paper Citation Record · LEDGER

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments

As of 21 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2606.19675.

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

pith.paper-citation-record.v1
2606.19675 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-26T17:59:50.377281Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

30 of 30 outbound references displayed

verified exact3
verified fuzzy0
unresolved27
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 65962ef1-d2ea-445e-b509-64e79f77d6cf · outbound

This paper cites United Nations, Sep.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments United Nations, Sep

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation 2ced8334-7cba-46e8-89fc-f7067d24752b · outbound

This paper cites Robotic monitoring of forests: a dataset from the EU habitat 9210* in the Tuscan Apennines (central Italy),.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments Robotic monitoring of forests: a dataset from the EU habitat 9210* in the Tuscan Apennines (central Italy),

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation d0a64084-8073-4ffa-91cf-9ae289d2e177 · outbound

This paper cites Ground robot technologies in wildfire risk reduction: The viewpoint of the fire service,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments Ground robot technologies in wildfire risk reduction: The viewpoint of the fire service,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation 4f81bf22-464e-4fe2-9323-0927c17aa0d9 · outbound

This paper cites Building Forest Inventories With Autonomous Legged Robots—System, Lessons, and Challenges Ahead,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments Building Forest Inventories With Autonomous Legged Robots—System, Lessons, and Challenges Ahead,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation a98c88f3-2ab7-43a0-a28f-7380a75c4fbc · outbound

This paper cites TartanDrive: A large- scale dataset for learning off-road dynamics models,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments TartanDrive: A large- scale dataset for learning off-road dynamics models,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation 00e741d0-4a1b-4cbe-9333-38e45bfd0a64 · outbound

This paper cites TartanDrive 2.0: More modalities and better infrastructure to further self-supervised learning research in off-road driving tasks,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments TartanDrive 2.0: More modalities and better infrastructure to further self-supervised learning research in off-road driving tasks,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation 0de99c5a-8344-455d-9bd0-c036b556eb1b · outbound

This paper cites The GOOSE dataset for perception in unstructured environments,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments The GOOSE dataset for perception in unstructured environments,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation db340b64-45cc-4632-baaa-b76cf7bea83f · outbound

This paper cites LAMP 2.0: A robust multi-robot slam system for operation in challenging large-scale underground environments,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments LAMP 2.0: A robust multi-robot slam system for operation in challenging large-scale underground environments,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation 070b544d-19ff-46b4-86f7-8e952fcbd3b9 · outbound

This paper cites M3ED: Multi-robot, multi- sensor, multi-environment event dataset,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments M3ED: Multi-robot, multi- sensor, multi-environment event dataset,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation ab3e6c1b-df79-4e2c-b563-20eb44568980 · outbound

This paper cites GrandTour: A Legged Robotics Dataset in the Wild for Multi-Modal Perception and State Estimation.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments GrandTour: A Legged Robotics Dataset in the Wild for Multi-Modal Perception and State Estimation

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-09T02:20:28.592188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 53121601-6945-4d37-859e-6cd7da335fc9 · outbound

This paper cites CEAR: Comprehensive event camera dataset for rapid perception of agile quadruped robots,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments CEAR: Comprehensive event camera dataset for rapid perception of agile quadruped robots,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation 81f316fb-3303-4dff-9901-543fa5c4fb46 · outbound

This paper cites DiTer: Diverse terrain and multimodal dataset for field robot navigation in outdoor environments,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments DiTer: Diverse terrain and multimodal dataset for field robot navigation in outdoor environments,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation fc09b116-7f0e-4985-bb06-624466c18f5c · outbound

This paper cites DiTer++: Diverse terrain and multi- modal dataset for multi-robot slam in multi-session environments,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments DiTer++: Diverse terrain and multi- modal dataset for multi-robot slam in multi-session environments,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation d77a4501-0f80-4f98-9b52-8792fbce7311 · outbound

This paper cites M-SEVIQ: A multi-band stereo event visual-inertial quadruped-based dataset for perception under rapid motion and challenging illumination,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments M-SEVIQ: A multi-band stereo event visual-inertial quadruped-based dataset for perception under rapid motion and challenging illumination,

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-04T03:29:30.681503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 58c90108-a844-42d0-957e-940a40045602 · outbound

This paper cites ANYmal — toward legged robots for harsh environments,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments ANYmal — toward legged robots for harsh environments,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation 54809f9e-42a3-4749-bbff-84b0ca1a3767 · outbound

This paper cites Blind-Wayfarer: A minimal- ist, probing-driven framework for resilient navigation in perception- degraded environments,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments Blind-Wayfarer: A minimal- ist, probing-driven framework for resilient navigation in perception- degraded environments,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fce3a02-e996-4237-9ff2-ad7d5f0add2c · outbound

This paper cites Proprioception and reaction for walking among entanglements,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments Proprioception and reaction for walking among entanglements,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation 9193830c-de0d-406d-be98-1f2a646897f4 · outbound

This paper cites PrePARE: Predictive proprioception for agile failure event detection in robotic exploration of extreme terrains,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments PrePARE: Predictive proprioception for agile failure event detection in robotic exploration of extreme terrains,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation bf0abd7c-5245-4587-8e26-522cc4b923c6 · outbound

This paper cites VERN: Vegetation-aware robot navigation in dense unstructured outdoor en- vironments,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments VERN: Vegetation-aware robot navigation in dense unstructured outdoor en- vironments,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation 7e4a00a9-2c22-43d9-b308-d7adc6652063 · outbound

This paper cites V APOR: Legged robot navigation in unstructured outdoor environments using offline reinforcement learning,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments V APOR: Legged robot navigation in unstructured outdoor environments using offline reinforcement learning,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Unavailable: canonical work link unavailable.

Observation 9168f255-c1b9-45da-8bbc-51a26c3a4667 · outbound

This paper cites Robotics in forest inventories: SPOT’s first steps,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments Robotics in forest inventories: SPOT’s first steps,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation 7e46ff32-fab3-471f-bbf4-59d55158f986 · outbound

This paper cites Boxi: Design decisions in the context of algorithmic performance for robotics,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments Boxi: Design decisions in the context of algorithmic performance for robotics,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

Source-reported events for the cited work

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Observation aaa4d886-9236-48ed-b0a5-6db21088f470 · outbound

This paper cites A survey on terrain traversability analysis for autonomous ground vehicles: Methods, sensors, and challenges,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments A survey on terrain traversability analysis for autonomous ground vehicles: Methods, sensors, and challenges,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation 64c14efb-559c-4a86-8c45-9e35adbb71ab · outbound

This paper cites Fast traversability estima- tion for wild visual navigation,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments Fast traversability estima- tion for wild visual navigation,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation 177ae8ac-c01d-4c5f-a471-2f715e7d7ea9 · outbound

This paper cites Mini Cheetah: A platform for pushing the limits of dynamic quadruped control,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments Mini Cheetah: A platform for pushing the limits of dynamic quadruped control,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation a9063503-5a74-40a3-a172-b3d9c432effc · outbound

This paper cites Sparse robot swarms: Moving swarms to real-world applications,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments Sparse robot swarms: Moving swarms to real-world applications,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation 5348cb1f-4c23-4292-ad69-b73081c325bb · outbound

This paper cites Forent: A multi-modal dataset for characterizing quadruped robot entrapments in forest environments,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments Forent: A multi-modal dataset for characterizing quadruped robot entrapments in forest environments,

Reference 27

Resolution: verified exact; doi, observed 2026-06-26T18:09:41.139192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 91a77049-7938-4e1c-a615-5ab0cec6eaf2 · outbound

This paper cites Deep residual learning for image recognition,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments Deep residual learning for image recognition,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation b1768334-eb9d-45bd-aa6b-435c74de3fdb · outbound

This paper cites EfficientNet: Rethinking model scaling for convolutional neural networks,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments EfficientNet: Rethinking model scaling for convolutional neural networks,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Observation a3d59fb1-3ada-4b94-97b2-dd29a7d06e22 · outbound

This paper cites Distinctive image features from scale-invariant key- points,.

ForEnt: A Multi-Modal Dataset for Characterizing Quadruped Robot Entrapments in Forest Environments Distinctive image features from scale-invariant key- points,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-26T17:59:50.377281Z

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Pith citing papers

No inbound Pith citation observations are available.