Paper Citation Record · LEDGER

Distillation of Foundation Models for Time-dependent PDEs

As of 17 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2608.11937.

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

pith.paper-citation-record.v1
2608.11937 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:30:46.931856Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

21 of 21 outbound references displayed

verified exact1
verified fuzzy7
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 39831d61-a5b1-44fd-9e1f-7bf1725aada0 · outbound

This paper cites A library for learning neural operators.arXiv preprint arXiv:2412.10354,.

Distillation of Foundation Models for Time-dependent PDEs A library for learning neural operators.arXiv preprint arXiv:2412.10354,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T00:30:46.836049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40d1606f-0bca-49e3-8557-6c12cc1b78da · outbound

This paper cites PROSE-FD: A Multimodal PDE Foundation Model for Learning Multiple Operators for Forecasting Fluid Dynamics.

Distillation of Foundation Models for Time-dependent PDEs PROSE-FD: A Multimodal PDE Foundation Model for Learning Multiple Operators for Forecasting Fluid Dynamics

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T00:30:46.845162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a12cadcf-2602-4b13-ae61-a11b01a28096 · outbound

This paper cites Swin transformer v2: Scaling up capacity and resolution.

Distillation of Foundation Models for Time-dependent PDEs Swin transformer v2: Scaling up capacity and resolution

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:30:47.270110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 59de0738-8eef-44dd-af3f-029463cd8b51 · outbound

This paper cites Walrus: A Cross-Domain Foundation Model for Continuum Dynamics.

Distillation of Foundation Models for Time-dependent PDEs Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T00:30:46.863527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23bf282c-ee4f-4911-a4c9-323620545542 · outbound

This paper cites Spectral-inspired Operator Learning with Limited Data and Unknown Physics.

Distillation of Foundation Models for Time-dependent PDEs Spectral-inspired Operator Learning with Limited Data and Unknown Physics

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-16T00:30:47.006902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 17aca8ae-87fa-403f-aa2f-924e9c02fb8a · outbound

This paper cites PDEformer-2: A Versatile Foundation Model for Two-Dimensional Partial Differential Equations.

Distillation of Foundation Models for Time-dependent PDEs PDEformer-2: A Versatile Foundation Model for Two-Dimensional Partial Differential Equations

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T00:30:46.884864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee44a351-ecc7-433b-8970-63b041a11b6e · outbound

This paper cites Unisolver: Pde- conditional transformers towards universal neural PDE solvers.

Distillation of Foundation Models for Time-dependent PDEs Unisolver: Pde- conditional transformers towards universal neural PDE solvers

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:30:47.231555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 85d1e92f-2b55-4bfa-8b9f-b784a624905f · outbound

This paper cites First, TREX relies on the quality of the fine-tuned teacher.

Distillation of Foundation Models for Time-dependent PDEs First, TREX relies on the quality of the fine-tuned teacher

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:30:47.216581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d8931f6f-4d3a-4129-af3e-b1c5c531355b · outbound

This paper cites Cheng et al.

Distillation of Foundation Models for Time-dependent PDEs Cheng et al

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:30:47.200713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 89e62dea-7a9b-4946-a344-14feb912454e · outbound

This paper cites an unresolved cited work.

Distillation of Foundation Models for Time-dependent PDEs Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-16T00:30:47.188364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5fea1e3e-7f14-4b89-a072-a50375d60a08 · outbound

This paper cites an unresolved cited work.

Distillation of Foundation Models for Time-dependent PDEs Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-16T00:30:47.175813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 38ab5fdd-2d19-42bf-be33-7636c41f1dda · outbound

This paper cites an unresolved cited work.

Distillation of Foundation Models for Time-dependent PDEs Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-16T00:30:47.148253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ca4fb874-3e7e-4895-a4ec-2433ae7aea2b · outbound

This paper cites Decoupled weight decay regularization.

Distillation of Foundation Models for Time-dependent PDEs Decoupled weight decay regularization

Reference 1963

Resolution: unresolved; no resolver link, observed 2026-08-16T00:30:46.857553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0069e3e2-2561-4989-92da-ed421524a0e2 · outbound

This paper cites Kingma and Jimmy Ba.

Distillation of Foundation Models for Time-dependent PDEs Kingma and Jimmy Ba

Reference 1984

Resolution: unresolved; no resolver link, observed 2026-08-16T00:30:46.831485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0727b110-8437-47de-b500-465e79b8ef5a · outbound

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

Distillation of Foundation Models for Time-dependent PDEs U-net: Convolutional networks for biomedical image segmentation

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:30:47.244775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d3b7dd2f-700f-4070-89dc-fadca2d9844f · outbound

This paper cites OmniFluids: Physics Pre-trained Modeling of Fluid Dynamics.

Distillation of Foundation Models for Time-dependent PDEs OmniFluids: Physics Pre-trained Modeling of Fluid Dynamics

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-16T00:30:46.891132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e3ee21c-d192-4207-a4f9-7dacac7cc767 · outbound

This paper cites The model uses the same number of modes and channels as the TFNO, resulting in 5,042,836 parameters.

Distillation of Foundation Models for Time-dependent PDEs The model uses the same number of modes and channels as the TFNO, resulting in 5,042,836 parameters

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:30:47.161459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7e6d9938-2f19-4e1e-b14e-6843c182c6a8 · outbound

This paper cites Data-Free Knowledge Distillation for Deep Neural Networks.

Distillation of Foundation Models for Time-dependent PDEs Data-Free Knowledge Distillation for Deep Neural Networks

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-16T00:30:46.853288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bafbaf0-e90e-4cee-a019-0e279ba0c32e · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Distillation of Foundation Models for Time-dependent PDEs Gaussian Error Linear Units (GELUs)

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-16T00:30:46.822691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31f62658-df45-4cfe-adbc-2918e3e57108 · outbound

This paper cites Poseidon: Efficient Foundation Models for PDEs.

Distillation of Foundation Models for Time-dependent PDEs Poseidon: Efficient Foundation Models for PDEs

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-16T00:30:46.827395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57981504-2295-455c-bdba-ed40ad1a6567 · outbound

This paper cites Stuart, and Anima Anandkumar.

Distillation of Foundation Models for Time-dependent PDEs Stuart, and Anima Anandkumar

Reference 2025

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:30:47.285676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.