Paper Citation Record · LEDGER

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems

As of 14 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2606.03834.

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

pith.paper-citation-record.v1
2606.03834 v2

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T15:14:50.601545Z

measured 47 of 47 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 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

47 of 47 outbound references displayed

verified exact0
verified fuzzy0
unresolved47
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4978e779-832c-46a4-94b6-7c54f4aad890 · outbound

This paper cites Parametric correspondence and cham- fer matching: Two new techniques for image matching.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Parametric correspondence and cham- fer matching: Two new techniques for image matching

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 172ef80a-2f34-4e3a-820c-98a5a35214e2 · outbound

This paper cites Learning for adaptive and reactive robot control: a dynamical systems approach.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Learning for adaptive and reactive robot control: a dynamical systems approach

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ef846cb-0859-480c-909d-49198d6bf2b1 · outbound

This paper cites Cambridge university press, 2004.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Cambridge university press, 2004

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52316e3a-182d-41c8-aed8-17dd30499aef · outbound

This paper cites Riemannian flow matching policy for robot motion learning.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Riemannian flow matching policy for robot motion learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf250ea5-1b61-4bff-9e6a-85b95cd189ac · outbound

This paper cites Neural ordinary differential equations.Advances in neural information processing systems, 31, 2018.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Neural ordinary differential equations.Advances in neural information processing systems, 31, 2018

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a0bb79a-0477-4c1f-9984-6c1b1025ff6d · outbound

This paper cites Safe and stable control via Lyapunov-guided diffusion models.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Safe and stable control via Lyapunov-guided diffusion models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e937149f-0d72-45eb-a12f-ca9f2ef0a1f1 · outbound

This paper cites Learn- ing robotic manipulation policies from point clouds with conditional flow matching.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Learn- ing robotic manipulation policies from point clouds with conditional flow matching

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e64439e0-df41-4bc6-b36b-6f55c3eb5915 · outbound

This paper cites Fast and robust visuomotor riemannian flow matching policy.IEEE Transactions on Robotics, 41: 5327–5343, 2025.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Fast and robust visuomotor riemannian flow matching policy.IEEE Transactions on Robotics, 41: 5327–5343, 2025

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cdac701-e610-4d8e-83f2-8d981129be78 · outbound

This paper cites Density estimation using real nvp.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Density estimation using real nvp

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f3e99ab-b413-4df5-9297-63f93fa270f4 · outbound

This paper cites Fast and stable learning of dynamical systems based on extreme learning machine.IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49(6):1175–1185, 2017.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Fast and stable learning of dynamical systems based on extreme learning machine.IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49(6):1175–1185, 2017

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d75a3743-7491-4b85-b3aa-13d05b849a49 · outbound

This paper cites Computing discrete Fr´echet distance.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Computing discrete Fr´echet distance

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6b43def-20d5-441a-a8e8-acf9528e9dca · outbound

This paper cites Action- Flow: Equivariant, accurate, and efficient policies with spatially symmetric flow matching.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Action- Flow: Equivariant, accurate, and efficient policies with spatially symmetric flow matching

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b66f33a-d842-4b21-bc28-6e058ac63345 · outbound

This paper cites Mohammad Khansari-Zadeh and Aude Billard.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Mohammad Khansari-Zadeh and Aude Billard

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7387d3f8-e78f-4d11-8127-fffe0f1959a5 · outbound

This paper cites Mohammad Khansari-Zadeh and Aude Billard.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Mohammad Khansari-Zadeh and Aude Billard

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fee82b14-8227-40a7-9121-ec5696373b0a · outbound

This paper cites Glow: Generative flow with invertible 1x1 convolutions.Advances in neural information processing systems, 31, 2018.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Glow: Generative flow with invertible 1x1 convolutions.Advances in neural information processing systems, 31, 2018

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37b99a5c-b9c2-486b-af09-b15eca7fdfc5 · outbound

This paper cites Normalizing flows: An introduction and review of current methods.IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(11):3964–3979, 2020.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Normalizing flows: An introduction and review of current methods.IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(11):3964–3979, 2020

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6037b21b-21f0-4d16-9e84-4507c188df66 · outbound

This paper cites Learning stable deep dynamics models.Advances in neural information processing systems, 32, 2019.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Learning stable deep dynamics models.Advances in neural information processing systems, 32, 2019

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ad8a943-cb66-4b07-aaec-e64555a1115e · outbound

This paper cites An invariance principle in the theory of stability.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems An invariance principle in the theory of stability

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d677203-cbb8-4c5b-9d46-328010af0044 · outbound

This paper cites an unresolved cited work.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Unresolved cited work

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97747583-eff2-4bff-b46f-793b6b5f8a19 · outbound

This paper cites Smooth manifolds.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Smooth manifolds

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7badf14-525a-4128-b704-3e62f5098b86 · outbound

This paper cites Mmp++: Motion manifold primitives with parametric curve models.IEEE Transactions on Robotics, 2024.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Mmp++: Motion manifold primitives with parametric curve models.IEEE Transactions on Robotics, 2024

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44666852-605d-4986-84aa-12302c1b10a6 · outbound

This paper cites Neural learning of vector fields for encoding stable dynamical systems.Neurocomputing, 141:3–14, 2014.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Neural learning of vector fields for encoding stable dynamical systems.Neurocomputing, 141:3–14, 2014

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e34d6488-571d-439f-8857-95607276731c · outbound

This paper cites an unresolved cited work.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32b114f7-67c3-4d80-a478-469677ebda10 · outbound

This paper cites Flow straight and fast: Learning to generate and transfer data with rectified flow.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Flow straight and fast: Learning to generate and transfer data with rectified flow

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c990c255-342f-4176-b9d9-df299b2afba1 · outbound

This paper cites Neural contractive dynamical systems.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Neural contractive dynamical systems

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09a90408-6ea8-4ca5-89d5-b7279f37c45d · outbound

This paper cites Dynamic time warping.Information retrieval for music and motion, pages 69–84, 2007.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Dynamic time warping.Information retrieval for music and motion, pages 69–84, 2007

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfec5e0e-cd55-415d-8780-8447b698a2f7 · outbound

This paper cites Springer Science & Business Media, 2013.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Springer Science & Business Media, 2013

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20de441e-be3b-433b-b4ca-7d073e7e82b9 · outbound

This paper cites Normalizing flows for probabilistic modeling and inference.Journal of Machine Learning Research, 22(57):1–64, 2021.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Normalizing flows for probabilistic modeling and inference.Journal of Machine Learning Research, 22(57):1–64, 2021

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75597b54-0338-482b-9497-84db3958e126 · outbound

This paper cites Complex patterns in a simple system.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Complex patterns in a simple system

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6d6bc21-5b5e-4100-9d02-9d7f8e2f9423 · outbound

This paper cites Stable motion primitives via imitation and contrastive learning.IEEE Transactions on Robotics, 39(5):3909–3928, 2023.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Stable motion primitives via imitation and contrastive learning.IEEE Transactions on Robotics, 39(5):3909–3928, 2023

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6222e0b5-4df1-415f-b046-50ec6e798244 · outbound

This paper cites Puma: Deep metric imitation learning for stable motion primitives.Advanced Intelligent Systems, 6(11): 2400144, 2024.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Puma: Deep metric imitation learning for stable motion primitives.Advanced Intelligent Systems, 6(11): 2400144, 2024

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 174ac0c0-3526-485e-ad95-ffe1f2e413db · outbound

This paper cites Fast diffeomorphic matching to learn globally asymptotically stable nonlinear dynamical systems.Systems & Control Letters, 96:51–59, 2016.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Fast diffeomorphic matching to learn globally asymptotically stable nonlinear dynamical systems.Systems & Control Letters, 96:51–59, 2016

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02ae970e-157c-460d-af4a-2730956908ea · outbound

This paper cites Euclideaniz- ing flows: Diffeomorphic reduction for learning stable dynamical systems.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Euclideaniz- ing flows: Diffeomorphic reduction for learning stable dynamical systems

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6807b02e-49f6-42b0-b394-740fa2f873d4 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems U-net: Convolutional networks for biomedical image segmentation

Reference 34

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0654bc76-5ba1-4c43-a9be-96f9f755dc34 · outbound

This paper cites A micro Lie theory for state estimation in robotics.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems A micro Lie theory for state estimation in robotics

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 125c0681-5288-4560-aea4-4eeb5d820f97 · outbound

This paper cites Stable Autonomous Flow Matching.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Stable Autonomous Flow Matching

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6ecc7b8-637e-4928-bad3-bfd59dd91e25 · outbound

This paper cites Imitationflow: Learning deep stable stochastic dynamic systems by normalizing flows.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Imitationflow: Learning deep stable stochastic dynamic systems by normalizing flows

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 154789fb-e96d-4af1-9f27-c1989caba29c · outbound

This paper cites Learning stable vector fields on lie groups.IEEE Robotics and Automation Letters, 7(4):12569–12576, 2022.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Learning stable vector fields on lie groups.IEEE Robotics and Automation Letters, 7(4):12569–12576, 2022

Reference 38

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15ada962-76e9-4956-8323-dcfdfe22dda8 · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 39

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a688532e-576e-4e0a-92a1-3d34e0b27968 · outbound

This paper cites Neural geometric fabrics: Efficiently learning high-dimensional policies from demonstration.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Neural geometric fabrics: Efficiently learning high-dimensional policies from demonstration

Reference 40

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7790bda6-d568-4760-94b9-b7a4253b5cf9 · outbound

This paper cites ManiFlow: A General Robot Manipulation Policy via Consistency Flow Training.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems ManiFlow: A General Robot Manipulation Policy via Consistency Flow Training

Reference 41

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b327f827-3d2f-4635-af92-e52a0df3b4c0 · outbound

This paper cites Learning riemannian stable dynamical systems via diffeomorphisms.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Learning riemannian stable dynamical systems via diffeomorphisms

Reference 42

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f38b9967-d2ef-4d53-891b-35b84824b444 · outbound

This paper cites Dif- feomorphic transforms for generalised imitation learning.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems Dif- feomorphic transforms for generalised imitation learning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b438f88b-4f74-49cc-9149-782232e4927c · outbound

This paper cites However, the same approach can be employed in the case when ˙XA(xt;θ)is a ball.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems However, the same approach can be employed in the case when ˙XA(xt;θ)is a ball

Reference 44

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f3bea45-342c-4759-be7e-3076dd185388 · outbound

This paper cites In this case, the latent dynamics may remain stable, while the corresponding deformation induced byJ −1 ψθ changes too abruptly in task space.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems In this case, the latent dynamics may remain stable, while the corresponding deformation induced byJ −1 ψθ changes too abruptly in task space

Reference 45

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 257b99b1-46f8-457c-82bb-e976532e6bfc · outbound

This paper cites SinceS 1 is isomorphic to the set of unit complex numbers{e iθ |θ∈R} ⊂C, elements on the torus can be written asx t = (eiθ1,t , eiθ2,t)∈T 2 ⊂C 2 [20, Ch.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems SinceS 1 is isomorphic to the set of unit complex numbers{e iθ |θ∈R} ⊂C, elements on the torus can be written asx t = (eiθ1,t , eiθ2,t)∈T 2 ⊂C 2 [20, Ch

Reference 46

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f991609-e1b2-420c-afe0-cee659f693c2 · outbound

This paper cites patternλ.

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems patternλ

Reference 47

Resolution: unresolved; no resolver link, observed 2026-07-12T15:14:50.601545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.