Pith. sign in

Paper Citation Record · LEDGER

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting

As of 9 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2508.19389.

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

pith.paper-citation-record.v1
2508.19389 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:53:00.203590Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

32 of 32 outbound references displayed

  • verified exact4
  • verified fuzzy19
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1c04ccb6-b7dd-472c-89ba-8462c253c927 · outbound

This paper cites Road traffic forecasting: Recent advances and new challenges.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Road traffic forecasting: Recent advances and new challenges

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.618588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.100772Z digest=sha256:634b1d58add27c43b062e0c6410ef1d174dc49f78b4bd1832a747c9a650c3409

Observation b9fc781c-5f6d-48d8-8b47-1ff8290155c6 · outbound

This paper cites A comparative study on traffic modeling techniques for predicting and simulating traffic behavior.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting A comparative study on traffic modeling techniques for predicting and simulating traffic behavior

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.608701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.104567Z digest=sha256:81d691f826a48ead09dea9d060f639beaf04a71c8af534f1580b9299c57d8a23

Observation 735ba95e-0718-461c-8fc8-d10c3aeb7160 · outbound

This paper cites Smith and Michael J.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Smith and Michael J

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.598891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.108047Z digest=sha256:4f80d8d878816dbd27844e8393d580130f1b6a975dbb502b3e4b96aeb301b1e8

Observation e5e1ad4e-b590-4688-a19d-3c350101b779 · outbound

This paper cites Road traffic congestion in the developing world.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Road traffic congestion in the developing world

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.588819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.111737Z digest=sha256:1d4a846c95caffa705f6fb3e18644c0885358f7e6b4f8042859049f5bb8dfd4c

Observation d8ae1b10-6694-4976-8386-2e9c77e8b8d8 · outbound

This paper cites Shafik and Hesham A.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Shafik and Hesham A

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.578246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.115096Z digest=sha256:6f7485bb517417e0429459868ff911a19b8b51322823d7fd40cdaa87e1a0e658

Observation 38c9c0fe-6717-4f68-a397-313cd1b03be7 · outbound

This paper cites On kinematic waves ii.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting On kinematic waves ii

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.567721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.118373Z digest=sha256:7ff3c8e0816bb75916d22b1c5c54bf3df510a7b17fc3758402bc27b87504c406

Observation a9bfcf65-ef4a-4436-b062-1e37b505e9f2 · outbound

This paper cites second order.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting second order

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.556963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.121796Z digest=sha256:d2a0b6908c39dbb0e8f90f9182646badb5f284e83a2e7c1f1baef4e2f1abb484

Observation 26c721d2-6294-4445-812b-6b078bd063ad · outbound

This paper cites Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:00.124943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:53:00.124943Z digest=sha256:cbb7dd95ef17416d4ac85973312b382d42446821dba6c34d12b5ea96ba2370d8

Observation fc0ecff5-8db8-41f7-be0b-199a0f36132f · outbound

This paper cites Spatial temporal incidence dynamic graph neural networks for traffic flow forecasting.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Spatial temporal incidence dynamic graph neural networks for traffic flow forecasting

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.546682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.128638Z digest=sha256:23dbac38b2798e5d08e5b878b4df0101530148fba455f807bf582ad6112a5bf2

Observation 55c12268-9aa3-4d65-b794-f977d745a99b · outbound

This paper cites Spatial-temporal graph attention networks: A deep learning approach for traffic forecasting.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Spatial-temporal graph attention networks: A deep learning approach for traffic forecasting

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.536714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.132058Z digest=sha256:663f1a374ad003617c799c9a2a2a1329210a8e55d4fb8c8139a4a585d4351f78

Observation 77cce044-6ef5-4b36-bea9-9a1fe1857c80 · outbound

This paper cites Stgat: Spatial-temporal graph attention networks for traffic flow forecasting.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Stgat: Spatial-temporal graph attention networks for traffic flow forecasting

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.525894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.135300Z digest=sha256:de3370fffe1f88ccd26feb4a4fe8d2a0e934b5c283061d1fd09cee0fe01b1acf

Observation 8d9295bd-c927-4fe9-9b47-f80a10e683e7 · outbound

This paper cites Attention based spatiotemporal graph attention networks for traffic flow forecasting.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Attention based spatiotemporal graph attention networks for traffic flow forecasting

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.515419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.138594Z digest=sha256:eeccf53f5ff8c2551806c8af3bd850dbdf0c2923339c7a2ca170090f27588bb8

Observation 611873ef-8ac3-4bd4-a844-4ae0d8d36cc3 · outbound

This paper cites Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:00.141776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:53:00.141776Z digest=sha256:500fec7e20b93ffdf35374b725a6caabbccef1601726d56ecc89fe50c7672cbd

Observation 4e01fe9b-4cfc-48ce-a4d1-724b1ea390c4 · outbound

This paper cites Physics-informed deep learning for traffic state estimation: A hybrid paradigm informed by second-order traffic models.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Physics-informed deep learning for traffic state estimation: A hybrid paradigm informed by second-order traffic models

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.498248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.145012Z digest=sha256:426dbe84a5926045d89973e6567bd115cab13ae0ede177bc42f52cd822406aac

Observation cc5ba737-89ec-48ec-80da-24f093367bd4 · outbound

This paper cites Physics-informed neural networks (pinns)-based traffic state estimation: An application to traffic network.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Physics-informed neural networks (pinns)-based traffic state estimation: An application to traffic network

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.487199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.148109Z digest=sha256:fa47ac56c9cc09c6a696cf0cdf5ee7dfbbff6943876c17f852905b862fb6b5c4

Observation 585a662c-6d19-4349-b060-9196261fc816 · outbound

This paper cites DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:00.151329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:53:00.151329Z digest=sha256:3b63f8fe235a92c1bbcabb729ad675a96478592486de4744705fa5e1f28b4cea

Observation 03a540a8-8ba4-44cf-aa82-ba008c92a1ba · outbound

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

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Fourier Neural Operator for Parametric Partial Differential Equations

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:00.154826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:53:00.154826Z digest=sha256:9558d6f0f9e8c442ebc3e3709c8158b962bafb433b3e8e78fbb6ecb065ead42e

Observation 8a534dcd-39e2-4daf-9637-58723bc31db8 · outbound

This paper cites ON-Traffic: An Operator Learning Framework for Online Traffic Flow Estimation and Uncertainty Quantification from Lagrangian Sensors.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting ON-Traffic: An Operator Learning Framework for Online Traffic Flow Estimation and Uncertainty Quantification from Lagrangian Sensors

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:53:00.374700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.158059Z digest=sha256:ed641cc0dfb930c63a468119ad6260245e84f5c727522dacd388caa18d50c4e0

Observation 83c96760-4ed3-454f-b852-f5d38443dc44 · outbound

This paper cites Fourier neural operator for learning solutions to macroscopic traffic flow models: Application to the forward and inverse problems.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Fourier neural operator for learning solutions to macroscopic traffic flow models: Application to the forward and inverse problems

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.476568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.161301Z digest=sha256:81cd814ec97658c0218a39319d3e1064e1dfc073b0f2ee7cc3a6ec6b1527c0ef

Observation d27a73d3-42de-4bb2-bf86-42297f35c9c2 · outbound

This paper cites Variable-Input Deep Operator Networks.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Variable-Input Deep Operator Networks

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:53:00.361168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.164754Z digest=sha256:f794c40ce47fb93c88789dd78d21338db0c4365c3afca0182b676468b9dfeddb

Observation a1c54b74-4712-4504-8586-221159bb94c5 · outbound

This paper cites Finite basis physics-informed neural networks (fbpinns): a scalable domain decomposition approach for solving differential equations.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Finite basis physics-informed neural networks (fbpinns): a scalable domain decomposition approach for solving differential equations

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.465814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.168238Z digest=sha256:b7ddd5e6913ae44e65cb587fe68d8ffe1901aeea7cd89391a235b5f3d4245923

Observation 8bcb7ba7-8997-450e-ac83-51c8f3afc8c7 · outbound

This paper cites An advanced physics-informed neural operator for comprehensive design optimization of highly-nonlinear systems: An aerospace composites processing case study.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting An advanced physics-informed neural operator for comprehensive design optimization of highly-nonlinear systems: An aerospace composites processing case study

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.455726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.171517Z digest=sha256:9e3fd40c64facd75831d3857aa991d49362e96cbd01f31a554fc058153583bee

Observation 0f6068cd-ff9a-4d3e-96b7-da12b4eb8c85 · outbound

This paper cites Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:00.174651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:53:00.174651Z digest=sha256:23d8541672d8e4ae0ce2521b0b70b9ecf06f5c8180b940225ba738627cc554b3

Observation 03f9c405-1dd7-4f4b-9008-7aac24952776 · outbound

This paper cites Integrating fourier neural operators with diffusion models to improve spectral representation of synthetic earthquake ground motion response.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Integrating fourier neural operators with diffusion models to improve spectral representation of synthetic earthquake ground motion response

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:00.178056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:53:00.178056Z digest=sha256:2e7c11e1ae6fc5daf3fb4e74fe910b6539850240e461cb9565c875c9de6a6d97

Observation 2ce849e5-0417-46c4-9cdc-11900dc654d1 · outbound

This paper cites Physics field super-resolution reconstruction via enhanced diffusion model and fourier neural operator.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Physics field super-resolution reconstruction via enhanced diffusion model and fourier neural operator

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.445395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.181189Z digest=sha256:7c502db1473a1418e553f3dfb5b5a96e7fd9dbddf6faa25d111df0d8a1f0d15e

Observation a5573e64-9144-4e7a-aac9-247a06faa454 · outbound

This paper cites Pde-refiner: Achieving accurate long rollouts with neural pde solvers.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Pde-refiner: Achieving accurate long rollouts with neural pde solvers

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:00.184208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:53:00.184208Z digest=sha256:5b93ab53a6a01ecafe42145cd917b5372afff4d51ebad7af658e9650e07f1b32

Observation 39547171-e877-41de-ba70-7f16e93f9b67 · outbound

This paper cites Aroma: Preserving spatial structure for latent pde modeling with local neural fields.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Aroma: Preserving spatial structure for latent pde modeling with local neural fields

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.428793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.187289Z digest=sha256:8fc6ef509e7bbb4ecba459a08de82c6a0c54c8b74d3d9e177a0ee79c4f22b531

Observation ec831649-d697-48e9-bf8c-d2b95256b817 · outbound

This paper cites Gnot: A general neural operator transformer for operator learning.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Gnot: A general neural operator transformer for operator learning

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:53:00.418208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.190597Z digest=sha256:1989139476d0df93206a8b256523bd9e0d20b53688899cd1e887686b60845423

Observation f4c66dd6-d217-44af-ae3e-4e882b86d6ba · outbound

This paper cites GITO: Graph-Informed Transformer Operator for Learning Complex Partial Differential Equations.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting GITO: Graph-Informed Transformer Operator for Learning Complex Partial Differential Equations

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:53:00.264879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.193734Z digest=sha256:9296fc2c637d60e5dfb1bd18ed27a519069901b9f4a67ef5573793e93466be99

Observation 10c2d905-78b4-45b5-8962-1e75e5d042f3 · outbound

This paper cites Denoising Diffusion Implicit Models.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Denoising Diffusion Implicit Models

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:00.197168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:53:00.197168Z digest=sha256:5d0fa6ee423f967113dd7d67b5317fd51f7ce11772ffffdc5ad376ac3c816f76

Observation 4da6eb6b-3ac6-4d3c-a04b-4aba58393b27 · outbound

This paper cites A Godunov type scheme for a class of LWR traffic flow models with non-local flux.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting A Godunov type scheme for a class of LWR traffic flow models with non-local flux

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:53:00.239833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:53:00.200354Z digest=sha256:0318f44cd20d9aa4485909824680465d613e7d11236b3ef2840095dbeaafc915

Observation 6579ab85-ba57-4e2a-8849-959d5d86fc8c · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:00.203590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:53:00.203590Z digest=sha256:b13ff47668174deda036d98e4b91bd42003862b98b9286576b902d6b85575a08

Pith citing papers

No inbound Pith citation observations are available.