Paper Citation Record · LEDGER

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach

As of 15 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2501.00714.

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

pith.paper-citation-record.v1
2501.00714 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:49:08.620176Z

measured 17 of 17 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

17 of 17 outbound references displayed

verified exact0
verified fuzzy13
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f8c77c86-e66c-4c97-8a00-27351abbeb44 · outbound

This paper cites The Rise and Potential of Large Language Model Based Agents: A Survey.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach The Rise and Potential of Large Language Model Based Agents: A Survey

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T22:49:08.534823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20738408-d805-4057-abc3-a1475d649914 · outbound

This paper cites Discovering governing equations from data by sparse identification of nonlinear dynamical systems.Proceedings of the national academy of sciences, 113(15):3932–3937, 2016.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Discovering governing equations from data by sparse identification of nonlinear dynamical systems.Proceedings of the national academy of sciences, 113(15):3932–3937, 2016

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T22:49:08.540380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22eefd27-a692-4fc9-aa8f-f4c6b15c8570 · outbound

This paper cites Learning anisotropic interaction rules from individual trajectories in a heterogeneous cellular population.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Learning anisotropic interaction rules from individual trajectories in a heterogeneous cellular population

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:49:08.939534Z

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.

Observation 19d6e4d1-b8af-4d1c-b658-7c8724122071 · outbound

This paper cites Learning hydrodynamic equations for active matter from particle simulations and experiments.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Learning hydrodynamic equations for active matter from particle simulations and experiments

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:49:08.916444Z

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.

Observation 1b9f5eb5-6d38-4e66-9f5e-2bc93d341edf · outbound

This paper cites Learning interaction kernels in mean-field equations of first-order systems of interacting particles.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Learning interaction kernels in mean-field equations of first-order systems of interacting particles

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:49:08.896232Z

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.

Observation dd91ae30-a157-4e0c-96f3-d99a47764b29 · outbound

This paper cites Multiscale modeling meets machine learning: What can we learn? Archives of Computational Methods in Engi- neering, 28:1017–1037, 2021.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Multiscale modeling meets machine learning: What can we learn? Archives of Computational Methods in Engi- neering, 28:1017–1037, 2021

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:49:08.877617Z

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.

Observation 7705558a-1709-4429-b23f-37221b87fc90 · outbound

This paper cites Multiscale simulations of complex systems by learning their effective dynamics.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Multiscale simulations of complex systems by learning their effective dynamics

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T22:49:08.570046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32c3acdc-56ec-4797-85bf-a46a47d96eb7 · outbound

This paper cites Physi- cally informed data-driven modeling of active nematics.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Physi- cally informed data-driven modeling of active nematics

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:49:08.847773Z

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.

Observation b0b603b7-7849-4795-8bea-78d432e80e0d · outbound

This paper cites Mod- eling collective motion: variations on the vicsek model.The European Physical Journal B, 64:451–456, 2008.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Mod- eling collective motion: variations on the vicsek model.The European Physical Journal B, 64:451–456, 2008

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:49:08.830477Z

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.

Observation 9e353ffc-9e62-4046-ab96-f7cd7c8aeb79 · outbound

This paper cites Traffic and related self-driven many-particle systems.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Traffic and related self-driven many-particle systems

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:49:08.815415Z

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.

Observation 9ba50633-c7de-4168-a3b0-839f7e171f0b · outbound

This paper cites Heterophilious dynamics enhances consensus.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Heterophilious dynamics enhances consensus

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:49:08.795235Z

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.

Observation 40a47a01-0974-4261-8ca4-34dcde6aa1ce · outbound

This paper cites A class of markov processes associated with nonlinear parabolic equations.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach A class of markov processes associated with nonlinear parabolic equations

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:49:08.779288Z

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.

Observation b72d6a26-48d7-4f4e-a998-3183bb8403a1 · outbound

This paper cites Topics in propagation of chaos.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Topics in propagation of chaos

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:49:08.764591Z

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.

Observation 7515daec-1c4e-4386-a2ef-d259cbab15cb · outbound

This paper cites Maxwell’s equations.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Maxwell’s equations

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:49:08.751295Z

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.

Observation a4eb7c02-1c77-4789-9172-2fa2fb959e9b · outbound

This paper cites Solving inverse stochastic prob- lems from discrete particle observations using the fokker–planck equation and physics-informed neural networks.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Solving inverse stochastic prob- lems from discrete particle observations using the fokker–planck equation and physics-informed neural networks

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:49:08.737695Z

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.

Observation 46b530e5-638d-459c-8fad-2d9784a8eef8 · outbound

This paper cites Weak collocation regression method: Fast reveal hidden stochastic dynamics from high-dimensional aggregate data.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Weak collocation regression method: Fast reveal hidden stochastic dynamics from high-dimensional aggregate data

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:49:08.720087Z

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.

Observation 8f1b55bf-69fd-4f28-8122-cf7bd22977e5 · outbound

This paper cites Automating the Search for Artificial Life with Foundation Models.

Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach Automating the Search for Artificial Life with Foundation Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T22:49:08.620176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.