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Paper Citation Record · LEDGER

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification

As of 14 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 1 inbound Pith citation observation for arXiv:2412.12036.

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

pith.paper-citation-record.v1
2412.12036 v2

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:22:48.653772Z

measured 16 of 16 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T04:38:21.916243Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T12:10:22.748061Z

Reference resolution

15 of 15 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved12
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1e9a20a0-e4a5-4e2c-9dba-d58ce5a6444a · outbound

This paper cites doi: 10.1126/scirobotics.abm6597.

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification doi: 10.1126/scirobotics.abm6597

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-11T14:22:48.627534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:22:48.627534Z digest=sha256:1600e5ef7d8d9a4e376750b37506d6d0d528f078467a0dd723f0f4fcd27377ca

Observation 08249331-2581-4944-98ad-9a9d7e6e78ba · outbound

This paper cites doi: https://doi.org/10.

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification doi: https://doi.org/10

Reference 11

Resolution
malformed identifier
raw_fallback, observed 2026-08-11T14:22:49.165394Z

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=2026-08-11T14:22:48.632585Z digest=sha256:5b79539888856989dacdf85f88f9c29a61e2e82f0b146b593a4a48d303ab3735

Observation 9041879f-c9b6-485c-8a90-f94fbe1af423 · outbound

This paper cites URL https://doi.org/10.1109/ICRA.2019.8794351.

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification URL https://doi.org/10.1109/ICRA.2019.8794351

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T14:22:48.642742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:22:48.642742Z digest=sha256:4e89319febc0c3cc8610de47315a4f8e6fb4277dd31bdfbea5323187ff39f625

Observation 850cdc76-8b16-483d-a109-8f6f7ad4c715 · outbound

This paper cites Neural-Swarm: Decentralized Close-Proximity Multirotor Control Using Learned Interactions.

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification Neural-Swarm: Decentralized Close-Proximity Multirotor Control Using Learned Interactions

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-11T14:22:48.885479Z

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=2026-08-11T14:22:48.648685Z digest=sha256:66a55a9959d168f96481068713878f87d29db6fd7135aaaefcdbf3269ee76f07

Observation c82e6bdf-2ba9-4b50-b779-716eedfdfa5f · outbound

This paper cites URL https://digital-library.

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification URL https://digital-library

Reference 1980

Resolution
verified exact
raw_fallback, observed 2026-08-11T14:22:49.150242Z

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=2026-08-11T14:22:48.581330Z digest=sha256:96f8a3b6c871ef4d2edb8613ef4296d51af11da377d6412667b31540ec123cad

Observation a76342a7-bcb2-45a3-9e22-c5c0bacdadf3 · outbound

This paper cites Michael O’Connell, Guanya Shi, Xichen Shi, Kamyar Azizzadenesheli, Anima Anandkumar, Yisong Yue, and Soon-Jo Chung.

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification Michael O’Connell, Guanya Shi, Xichen Shi, Kamyar Azizzadenesheli, Anima Anandkumar, Yisong Yue, and Soon-Jo Chung

Reference 1990

Resolution
unresolved
no resolver link, observed 2026-08-11T14:22:48.623074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:22:48.623074Z digest=sha256:c6d1b4acb5198c68336804cbbf85eb56686dfac46e696f6f5f4c159add29e0de

Observation b96994f6-2bf5-4b73-9061-c01c1645842c · outbound

This paper cites URL http://www.jstor.org/ stable/2346178.

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification URL http://www.jstor.org/ stable/2346178

Reference 1996

Resolution
unresolved
no resolver link, observed 2026-08-11T14:22:48.653772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:22:48.653772Z digest=sha256:774548daba5ff49ec5a2e52f64c1def5d92f2ba303611479f8ca08a5523b9eef

Observation dc493aef-8097-4d0b-accb-96551783a1b9 · outbound

This paper cites doi: 10.1007/978-1-4612-1768-8.

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification doi: 10.1007/978-1-4612-1768-8

Reference 1998

Resolution
unresolved
no resolver link, observed 2026-08-11T14:22:48.614075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:22:48.614075Z digest=sha256:83790a128d683df0b261b2c5c552a793805fa625a8988cf6262b836317c0d77c

Observation c8b7e6a7-356c-4b1e-9084-c59af7d61eb4 · outbound

This paper cites doi: https://doi.org/10.1016/j.arcontrol.2009.12.001.

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification doi: https://doi.org/10.1016/j.arcontrol.2009.12.001

Reference 2010

Resolution
unresolved
no resolver link, observed 2026-08-11T14:22:48.618518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:22:48.618518Z digest=sha256:4a921047a5f18f87abebec33ba5d495cc8ab38cd4405487811e20275b5bbbd2f

Observation 6e75b03d-84ba-4618-8ea3-2c901f140c0c · outbound

This paper cites URL https://www.pnas.org/doi/ abs/10.1073/pnas.1517384113.

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification URL https://www.pnas.org/doi/ abs/10.1073/pnas.1517384113

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-11T14:22:48.586901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:22:48.586901Z digest=sha256:fe1aca4ab53a484faba6f10516712b5d77356bd660f676646e34af694546c347

Observation b5added2-8ad9-4b16-bac0-7e8424c99714 · outbound

This paper cites Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks.

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-11T14:22:48.603765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:22:48.603765Z digest=sha256:fa29c8af0430aa0ab10f5e0901a941e7dab7c11f37961b11ff05d142528d9bec

Observation aae0f9ce-0871-4c8d-9d51-c061d9d86fc3 · outbound

This paper cites URL https://www.pnas.org/doi/abs/10.

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification URL https://www.pnas.org/doi/abs/10

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-11T14:22:48.593308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:22:48.593308Z digest=sha256:8268dcca4d74fe9de5fa0be6228cf9408bcef4af27ed1e912bd4f5eecde95d25

Observation 49bebed9-da24-4dce-9775-80203dfefe7c · outbound

This paper cites URL https://doi.org/10.

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification URL https://doi.org/10

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-11T14:22:48.598080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:22:48.598080Z digest=sha256:045282710b1433bf636ae0d847eb2ce2dbc52adac9c007a6ec8965e39d118469

Observation 9a9a99a4-1a1e-48c8-be47-580b34922a5c · outbound

This paper cites Adaptive-Control-Oriented Meta-Learning for Nonlinear Systems.

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification Adaptive-Control-Oriented Meta-Learning for Nonlinear Systems

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-11T14:22:48.636665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:22:48.636665Z digest=sha256:92338ad15457a78a3eacde2f8c87bdffbaee2388eaba21706f61d443c789d360

Observation d2cea4ac-f2fe-4037-bef8-15b2e119c8a2 · outbound

This paper cites Lennart Ljung.

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification Lennart Ljung

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-11T14:22:48.608513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:22:48.608513Z digest=sha256:7b6ea8025087684248f1a3487389094654e2107994744bfd98d0c7063bc50f30

Pith citing papers

Observation 9d6c7f1c-505f-4974-8dc5-89b96938e1a1 · inbound

AC-SINDy: Compositional Sparse Identification of Nonlinear Dynamics cites this paper.

AC-SINDy: Compositional Sparse Identification of Nonlinear Dynamics LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-06-02T02:03:31.021359Z

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=2026-05-10T04:38:21.916243Z digest=sha256:e16042f6d8d6342317cb4c851f5b770cfb40e028f33e981b8bb9f2c1dc3aaabb