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Paper Citation Record · LEDGER

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

As of 23 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 18 inbound Pith citation observations for arXiv:2511.15684.

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

pith.paper-citation-record.v1
2511.15684 v2

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T21:23:21.027937Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:30:46.863527Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

15 of 15 outbound references displayed

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  • verified fuzzy0
  • unresolved14
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  • malformed identifier1
  • metadata mismatch0

External citation measurements

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arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 084256ac-b79e-4930-8afb-d20434eb7bd6 · outbound

This paper cites This was an artifact of merging several implementations rather than an intentional decision.

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics This was an artifact of merging several implementations rather than an intentional decision

Reference 1

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source=pdf_text observed=2026-08-03T21:23:18.990518Z digest=sha256:5227882c955127bbb24851a90d7b7d39554b4e39b88bc68e464aead79ce747d5

Observation bde44483-3dab-4588-8a81-ac82d17a762a · outbound

This paper cites However, in multiple dimensions, the padding will overlap in corners resulting in additive corner handling.

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics However, in multiple dimensions, the padding will overlap in corners resulting in additive corner handling

Reference 2

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source=pdf_text observed=2026-08-03T21:23:19.191076Z digest=sha256:941b48562d25df4bb6a52b89f34b6cbc1da6c9759bc6b6e3ff8123781d1cedbf

Observation 07fae610-8bb9-4647-bc8d-7de6f8ae0383 · outbound

This paper cites For non-periodic boundaries, padding is implemented with additional channels containing binary masks for each topological boundary type.

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics For non-periodic boundaries, padding is implemented with additional channels containing binary masks for each topological boundary type

Reference 3

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source=pdf_text observed=2026-08-03T21:23:20.929270Z digest=sha256:3a4452b32311111115d2794676de0b5e97f9f20c33dfccdfa51692b586789617

Observation f24d6146-b2b5-4388-a052-1e6a16eca7fd · outbound

This paper cites The model is forced to learn to infer the time step from history.

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics The model is forced to learn to infer the time step from history

Reference 4

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source=pdf_text observed=2026-08-03T21:23:19.422220Z digest=sha256:2ba8e8d84e5ccfdbb02f8bc01e4b1fb64b91b4015ef7c2bc44be1be4fa2afa76

Observation ced373ea-f349-4db1-8ae8-d4f04e087243 · outbound

This paper cites time-conditioning.

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics time-conditioning

Reference 5

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source=pdf_text observed=2026-08-03T21:23:19.637454Z digest=sha256:d6f855bcf5436bcb9ff0dd43ef7f2859f15268e853e28f999ef6d7e0603fc68c

Observation 1f3fe41c-0ee4-4618-87d6-010a6d3989b6 · outbound

This paper cites an unresolved cited work.

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics Unresolved cited work

Reference 6

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source=pdf_text observed=2026-08-03T21:23:19.736133Z digest=sha256:4bd9a84a2b1fb64ca39d3bbe86584017ef756f3751108fb0a2b8f56838a9897b

Observation 194e7e82-1c49-4ca0-b494-bec1b456e023 · outbound

This paper cites C.1 DATA TRANSFORMATIONS The following elementwise transformations were applied to input fields independent of normalization.

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics C.1 DATA TRANSFORMATIONS The following elementwise transformations were applied to input fields independent of normalization

Reference 7

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source=pdf_text observed=2026-08-03T21:23:19.759500Z digest=sha256:fc08e9597b0da6ef82649516ad32bbd6008d4096c0dbbc0958ddf170f688c34a

Observation fb41b9b5-38f0-46c9-a106-6e7cf3c24581 · outbound

This paper cites •turbulence gravity cooling.

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics •turbulence gravity cooling

Reference 9

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Observation 25d8f5b3-72e3-44f1-bd8a-ac82bef15900 · outbound

This paper cites •turbulent radiative layer 3D.

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics •turbulent radiative layer 3D

Reference 11

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Observation 10c2d54c-585c-4ec6-b56f-69ad6fd431fa · outbound

This paper cites an unresolved cited work.

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics Unresolved cited work

Reference 12

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Observation 8992f2df-0bb5-4add-a488-e70febe9c8d3 · outbound

This paper cites C.2 BOUNDARYHANDLING In the case of periodic boundary conditions, the computations described in Section 3.2 can be performed exactly.

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics C.2 BOUNDARYHANDLING In the case of periodic boundary conditions, the computations described in Section 3.2 can be performed exactly

Reference 13

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Observation e4241105-043f-44cf-9b62-62f6d7abffd5 · outbound

This paper cites We do not know what is beyond the boundary.

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics We do not know what is beyond the boundary

Reference 14

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Observation f85714a8-a580-4a33-a9fb-2f959d7ca437 · outbound

This paper cites The model is unaware of what conditions are enforced at this barrier.

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics The model is unaware of what conditions are enforced at this barrier

Reference 15

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source=pdf_text observed=2026-08-03T21:23:20.782206Z digest=sha256:34e51e7caa0c4db1cd52bc253dfa6a64b42474a5b279d923063652ab181d7751

Observation 45af697e-a664-4ec1-9e09-78c8c095e978 · outbound

This paper cites random” initial conditions. From PDEBench. GT t = 0 Predicted t = 2 t = 4 t = 6 t = 9 CNS Turb (3D) - density Figure 39: Compressible Navier-Stokes in 3D with “turbulent.

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics random” initial conditions. From PDEBench. GT t = 0 Predicted t = 2 t = 4 t = 6 t = 9 CNS Turb (3D) - density Figure 39: Compressible Navier-Stokes in 3D with “turbulent

Reference 17

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source=pdf_text observed=2026-08-03T21:23:21.027937Z digest=sha256:ac718d74c3bf3a1bd7ecf6466c75fab50dc7bdd9c6b7d2ecc42a64c640c5e2ec

Observation 4ff005b7-0a34-442e-8344-eae7d40e3a71 · outbound

This paper cites PDEBENCH: An Extensive Benchmark for Scientific Machine Learning.

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics PDEBENCH: An Extensive Benchmark for Scientific Machine Learning

Reference 2024

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Pith citing papers

Observation 320b4b00-a0c5-4f51-85ea-fd131cd7d1a4 · inbound

OmniMol: Transferring Particle Physics Knowledge to Molecular Dynamics with Point-Edge Transformers cites this paper.

OmniMol: Transferring Particle Physics Knowledge to Molecular Dynamics with Point-Edge Transformers Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 27

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arxiv_id, observed 2026-07-07T03:18:10.578473Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 76d539c8-7103-47b1-bcc7-189e9ca78e5b · inbound

Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs cites this paper.

Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 2025

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Observation 1987cf93-df28-42a2-83b3-5e8326e57637 · inbound

Transformers for dynamical systems learn transfer operators in-context cites this paper.

Transformers for dynamical systems learn transfer operators in-context Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 22

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Observation 71aba3c1-956e-49a1-86af-73c5f21bc226 · inbound

Flowers: A Warp Drive for Neural PDE Solvers cites this paper.

Flowers: A Warp Drive for Neural PDE Solvers Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 2024

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Observation a140315a-bf03-47e5-a599-b755818bb309 · inbound

Replay-Based Continual Learning for Physics-Informed Neural Operators cites this paper.

Replay-Based Continual Learning for Physics-Informed Neural Operators Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 16

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Observation 5af03667-a6ef-46a7-87eb-505172a67753 · inbound

Autoregressive One-Step Generative Modeling for Dynamical System Forecasting cites this paper.

Autoregressive One-Step Generative Modeling for Dynamical System Forecasting Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 50

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Observation 1b1c021c-22b5-44a5-962d-1545c9ac82a8 · inbound

jNO: A JAX Library for Neural Operator and Foundation Model Training cites this paper.

jNO: A JAX Library for Neural Operator and Foundation Model Training Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 8

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Observation badaa388-0ba2-4125-b883-0482826a49fa · inbound

Discovering Physical Directions in Weight Space: Composing Neural PDE Experts cites this paper.

Discovering Physical Directions in Weight Space: Composing Neural PDE Experts Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 19

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Observation ca161c92-f108-42c8-b0b9-b399617b2e4e · inbound

Breakeven complexity: A new perspective on neural partial differential equation solvers cites this paper.

Breakeven complexity: A new perspective on neural partial differential equation solvers Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 21

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Observation 849bddba-5988-405c-b667-49ebb8bd900f · inbound

AOT-POT: Adaptive Operator Transformation for Large-Scale PDE Pre-training cites this paper.

AOT-POT: Adaptive Operator Transformation for Large-Scale PDE Pre-training Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 40

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Observation 024b48e6-2bda-420a-a9f4-4815b9292ee8 · inbound

Function graph transformers universally approximate operators between function spaces cites this paper.

Function graph transformers universally approximate operators between function spaces Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 79

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Observation 25c43cb5-0922-485a-a3d2-fbbc5b4c94d7 · inbound

Small Models, Strong Priors: Architectural Inductive Bias for Parameter-Efficient Neural PDE Solvers cites this paper.

Small Models, Strong Priors: Architectural Inductive Bias for Parameter-Efficient Neural PDE Solvers Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 34

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arxiv_id, observed 2026-07-07T03:18:10.578473Z

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Observation 4d841aa3-f392-4c36-87aa-2728764def26 · inbound

Towards a Foundation Model for the Martian Atmosphere cites this paper.

Towards a Foundation Model for the Martian Atmosphere Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 158

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arxiv_id, observed 2026-07-07T03:18:10.578473Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 3b6c5650-9ac2-4fda-bd85-c8cef55d3e99 · inbound

Sparse probes and murky physics: a case study of interpretability challenges in a foundation model for continuum dynamics cites this paper.

Sparse probes and murky physics: a case study of interpretability challenges in a foundation model for continuum dynamics Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 2

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arxiv_id, observed 2026-07-07T03:18:10.578473Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 95da3b39-2766-49a1-818f-8bb00eb61b7a · inbound

NEXUS: Neural Energy Fields for Physically Consistent Contact-Rich 3D Object Dynamics cites this paper.

NEXUS: Neural Energy Fields for Physically Consistent Contact-Rich 3D Object Dynamics Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 9

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Observation 95cac562-4dcc-4ec3-a78f-a875b38021bd · inbound

Otter Weather: Skillful and Computationally Efficient Medium-Range Weather Forecasting cites this paper.

Otter Weather: Skillful and Computationally Efficient Medium-Range Weather Forecasting Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 24

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arxiv_id, observed 2026-07-07T03:18:10.578473Z

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Observation cde19b91-3b63-4354-99b1-90fb92c9da15 · inbound

Foundation Models for Astrophysics cites this paper.

Foundation Models for Astrophysics Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

Reference 84

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

Distillation of Foundation Models for Time-dependent PDEs cites this paper.

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

Reference 10

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