Paper Citation Record · LEDGER

Latent Mamba Operator for Partial Differential Equations

As of 8 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 7 inbound Pith citation observations for arXiv:2505.19105.

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

pith.paper-citation-record.v1
2505.19105 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:24:44.161633Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T05:22:12.788609Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:37:29.920831Z

Reference resolution

34 of 34 outbound references displayed

verified exact3
verified fuzzy4
unresolved25
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

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Outbound references

Observation 9009e16c-b4d3-4f1c-8643-2b766b532943 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Latent Mamba Operator for Partial Differential Equations An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:43.956383Z

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Observation 4cf595cb-cce8-4d4d-a52b-8ee0b4fff9cf · outbound

This paper cites Training configurations are directly from previous works without extra tuning.

Latent Mamba Operator for Partial Differential Equations Training configurations are directly from previous works without extra tuning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:24:45.079282Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 83e9eea5-e49c-4b69-99cc-9ef88a076b66 · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

Latent Mamba Operator for Partial Differential Equations Efficiently Modeling Long Sequences with Structured State Spaces

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.009890Z

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Observation fec276bf-458b-4edc-9c27-9193f9d6042d · outbound

This paper cites DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training.

Latent Mamba Operator for Partial Differential Equations DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.021281Z

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Observation daf0b013-ef49-4106-8281-d1cfdcf8b957 · outbound

This paper cites GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling.

Latent Mamba Operator for Partial Differential Equations GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.040741Z

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Observation 95b9b567-a5ad-49dd-82f2-e8c218a29413 · outbound

This paper cites Neural Operator: Learning Maps Between Function Spaces.

Latent Mamba Operator for Partial Differential Equations Neural Operator: Learning Maps Between Function Spaces

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.047914Z

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Observation e1f60800-e6de-42f8-9c93-4b6cc993926c · outbound

This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

Latent Mamba Operator for Partial Differential Equations Fourier Neural Operator for Parametric Partial Differential Equations

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.054027Z

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Observation 2bcdb51a-e919-49a6-8e31-f08378d7bc76 · outbound

This paper cites Fourier Neural Operator with Learned Deformations for PDEs on General Geometries.

Latent Mamba Operator for Partial Differential Equations Fourier Neural Operator with Learned Deformations for PDEs on General Geometries

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.060145Z

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Observation e75ed867-a84b-4362-b3c0-7ad25c94a554 · outbound

This paper cites Mitigating spectral bias for the multiscale operator learning.

Latent Mamba Operator for Partial Differential Equations Mitigating spectral bias for the multiscale operator learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.065590Z

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Observation 1b5d7202-b8fc-4c63-9573-9665b3a0b0aa · outbound

This paper cites VMamba: Visual State Space Model.

Latent Mamba Operator for Partial Differential Equations VMamba: Visual State Space Model

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.070890Z

Source-reported events for the cited work

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Observation 2c168a44-b1c3-49a7-8ebf-133258bb2ac3 · outbound

This paper cites Decoupled Weight Decay Regularization.

Latent Mamba Operator for Partial Differential Equations Decoupled Weight Decay Regularization

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.076032Z

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Observation 1fe1bff5-ff30-4ee0-9dcc-6f10661405b6 · outbound

This paper cites A Survey of Mamba.

Latent Mamba Operator for Partial Differential Equations A Survey of Mamba

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.081106Z

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Observation 14509b35-1ace-4f84-9e52-a5f0f9065637 · outbound

This paper cites U-NO: U-shaped Neural Operators.

Latent Mamba Operator for Partial Differential Equations U-NO: U-shaped Neural Operators

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.086004Z

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Observation 0a457367-8444-495a-8fd7-e0effd0dbbe5 · outbound

This paper cites Factorized Fourier Neural Operators.

Latent Mamba Operator for Partial Differential Equations Factorized Fourier Neural Operators

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.108169Z

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Observation a2b34d44-5118-4546-bb9a-2a3e11e91199 · outbound

This paper cites Transolver: A Fast Transformer Solver for PDEs on General Geometries.

Latent Mamba Operator for Partial Differential Equations Transolver: A Fast Transformer Solver for PDEs on General Geometries

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.126748Z

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Observation be025000-b2a2-4815-be23-bd4a6fa6abb2 · outbound

This paper cites Improved Operator Learning by Orthogonal Attention.

Latent Mamba Operator for Partial Differential Equations Improved Operator Learning by Orthogonal Attention

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.132186Z

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Unavailable: canonical work link unavailable.

Observation 2f51545d-183d-4702-9ece-7075e13c28d5 · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

Latent Mamba Operator for Partial Differential Equations Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.136838Z

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Observation 834f78c6-ccbf-4605-b86c-bc9b57881505 · outbound

This paper cites Proof:Let xi ∈Ω denote the i-th element in the input domain, and let zj represent the j-th latent token in the latent domain Ωs.

Latent Mamba Operator for Partial Differential Equations Proof:Let xi ∈Ω denote the i-th element in the input domain, and let zj represent the j-th latent token in the latent domain Ωs

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:24:45.127085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d6c4935e-3f63-4e0c-a97e-f1b1c9063737 · outbound

This paper cites In the experiment, 900 samples with varying die shapes are used for training, while 80 additional samples are reserved for testing.

Latent Mamba Operator for Partial Differential Equations In the experiment, 900 samples with varying die shapes are used for training, while 80 additional samples are reserved for testing

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:24:45.101729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 95811b20-2c59-46b6-a954-aff4d9de306b · outbound

This paper cites an unresolved cited work.

Latent Mamba Operator for Partial Differential Equations Unresolved cited work

Reference 34

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T14:24:45.053877Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8589de7f-6416-4fad-9925-d46099fec9ee · outbound

This paper cites State-space models are accurate and efficient neural operators for dynamical systems.

Latent Mamba Operator for Partial Differential Equations State-space models are accurate and efficient neural operators for dynamical systems

Reference 1990

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.033956Z

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Observation 5715ce46-83a7-4371-9fd7-59d8ca7e51d1 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Latent Mamba Operator for Partial Differential Equations Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 2001

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.004259Z

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Observation d472ff64-4001-4176-9e74-b184c24d7967 · outbound

This paper cites Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality.

Latent Mamba Operator for Partial Differential Equations Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Reference 2004

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:43.984322Z

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Observation f213d3aa-3fb5-493d-9352-626b4aa8441d · outbound

This paper cites CoNO: Complex Neural Operator for Continous Dynamical Physical Systems.

Latent Mamba Operator for Partial Differential Equations CoNO: Complex Neural Operator for Continous Dynamical Physical Systems

Reference 2005

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:24:44.361979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ee5a8a40-9f80-41cb-8a9f-30e8fc278aa0 · outbound

This paper cites Solving High-Dimensional PDEs with Latent Spectral Models.

Latent Mamba Operator for Partial Differential Equations Solving High-Dimensional PDEs with Latent Spectral Models

Reference 2007

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.120866Z

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Observation c969990c-7dda-42aa-95dd-e582e2614c20 · outbound

This paper cites Poseidon: Efficient Foundation Models for PDEs.

Latent Mamba Operator for Partial Differential Equations Poseidon: Efficient Foundation Models for PDEs

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.027049Z

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Observation cd5232d2-43b0-4c77-992d-1849de5f767f · outbound

This paper cites Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice.

Latent Mamba Operator for Partial Differential Equations Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.115067Z

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Unavailable: canonical work link unavailable.

Observation 5d992a2d-fbe2-4dcc-934f-78175b8e1149 · outbound

This paper cites Audio Mamba: Bidirectional State Space Model for Audio Representation Learning.

Latent Mamba Operator for Partial Differential Equations Audio Mamba: Bidirectional State Space Model for Audio Representation Learning

Reference 2018

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T14:24:44.769687Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b1ec6a81-dc2e-4a40-8d52-41e75d24b597 · outbound

This paper cites Centered Self-Attention Layers.

Latent Mamba Operator for Partial Differential Equations Centered Self-Attention Layers

Reference 2020

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:24:44.994477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 949746b6-48c5-49a6-bce6-7f02cc1ae6fc · outbound

This paper cites Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers.

Latent Mamba Operator for Partial Differential Equations Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.015209Z

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Observation 5375fc49-724e-478e-9beb-2a26d95f56c4 · outbound

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

Latent Mamba Operator for Partial Differential Equations U-net: Con- volutional networks for biomedical image segmentation

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:24:45.155643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 71d1f302-a2af-48ed-87fe-f27ead121f1b · outbound

This paper cites State Space Models as Foundation Models: A Control Theoretic Overview.

Latent Mamba Operator for Partial Differential Equations State Space Models as Foundation Models: A Control Theoretic Overview

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:43.968111Z

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Observation 6ed32b77-fe75-4fd8-bedc-fcef093a40be · outbound

This paper cites Spectral Neural Operators.

Latent Mamba Operator for Partial Differential Equations Spectral Neural Operators

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:43.996868Z

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Observation f6c59cbe-c6ad-49ea-97b4-afeab4685300 · outbound

This paper cites Bevanda, P., Sosnowski, S., and Hirche, S.

Latent Mamba Operator for Partial Differential Equations Bevanda, P., Sosnowski, S., and Hirche, S

Reference 2025

Resolution: verified exact; raw_fallback, observed 2026-08-07T14:24:44.935602Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

Observation d938449d-dd49-4a6e-995e-a44b771e9b7b · inbound

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

Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs Latent Mamba Operator for Partial Differential Equations

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-03T05:22:12.788609Z

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Observation 3703aa62-16a5-44fe-a4de-e4674151e02c · inbound

SPAMoE: Spectrum-Aware Hybrid Operator Framework for Full-Waveform Inversion cites this paper.

SPAMoE: Spectrum-Aware Hybrid Operator Framework for Full-Waveform Inversion Latent Mamba Operator for Partial Differential Equations

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:31:00.921351Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d75aa7bc-de33-4542-af3a-167ba3b8e3c2 · inbound

SPAMoE: Spectrum-Aware Hybrid Operator Framework for Full-Waveform Inversion cites this paper.

SPAMoE: Spectrum-Aware Hybrid Operator Framework for Full-Waveform Inversion Latent Mamba Operator for Partial Differential Equations

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-13T08:35:30.948277Z

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Observation 6405095c-f320-4f77-9fa4-dc2e7924907a · inbound

Faster by Design: Interactive Aerodynamics via Neural Surrogates Trained on Expert-Validated CFD cites this paper.

Faster by Design: Interactive Aerodynamics via Neural Surrogates Trained on Expert-Validated CFD Latent Mamba Operator for Partial Differential Equations

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:11:20.646493Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c4a83948-5d7f-4d41-964d-da13d83894a2 · inbound

Stable Long-Horizon PDE Forecasting via Latent Structured Spectral Propagators cites this paper.

Stable Long-Horizon PDE Forecasting via Latent Structured Spectral Propagators Latent Mamba Operator for Partial Differential Equations

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:26:19.782464Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 45ee0a37-7a5e-4524-a7b0-ef0947c51d63 · inbound

Graph Mamba Operator: A Latent Simulator for Interacting Particle Systems cites this paper.

Graph Mamba Operator: A Latent Simulator for Interacting Particle Systems Latent Mamba Operator for Partial Differential Equations

Reference 82

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T00:37:29.922182Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 498ebd18-ebf1-4212-ad00-322e3287456b · inbound

Data-free neural PDE solvers based on Graph Neural Networks and weak forms cites this paper.

Data-free neural PDE solvers based on Graph Neural Networks and weak forms Latent Mamba Operator for Partial Differential Equations

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-31T23:24:55.345347Z

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