Paper Citation Record · LEDGER

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective

As of 13 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2412.19547.

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

pith.paper-citation-record.v1
2412.19547 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:18:15.964503Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

45 of 45 outbound references displayed

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External citation measurements

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Outbound references

Observation 2fbae4a8-aa63-40b7-85f9-c8bec5b94240 · outbound

This paper cites Nddr-cnn: Layerwise feature fusing in multi-task cnns by neural discriminative dimensionality reduction,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Nddr-cnn: Layerwise feature fusing in multi-task cnns by neural discriminative dimensionality reduction,

Reference 1

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Observation 82100af5-b74e-428b-8434-3406fa3325c6 · outbound

This paper cites Rethinking hard-parameter sharing in multi-domain learning,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Rethinking hard-parameter sharing in multi-domain learning,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.550250Z

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Observation d20a2c4d-839c-4e4b-8edd-e6f9cb6650c3 · outbound

This paper cites Multitask-guided deep clustering with boundary adaptation,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Multitask-guided deep clustering with boundary adaptation,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.539572Z

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Observation 5f8a252e-cdd2-4194-a2c0-278d08892ca0 · outbound

This paper cites Parallel solution of nonlinear projection equations in a multitask learning framework,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Parallel solution of nonlinear projection equations in a multitask learning framework,

Reference 4

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Observation 11f92b97-5b75-4e5e-8aae-0a0659b0cb98 · outbound

This paper cites Cross-stitch networks for multi-task learning,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Cross-stitch networks for multi-task learning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.529356Z

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Observation 9a580c1c-6b81-4d58-801d-a9e2da2eaf56 · outbound

This paper cites ControlVideo: Training-free Controllable Text-to-Video Generation.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective ControlVideo: Training-free Controllable Text-to-Video Generation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T00:18:15.824461Z

Source-reported events for the cited work

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Observation 5d841296-b75d-48ef-985e-fbb038e041dc · outbound

This paper cites Learning deep representation for face alignment with auxiliary attributes,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Learning deep representation for face alignment with auxiliary attributes,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.518985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0b22012b-81c1-4ef8-a10d-eedb6ab6c3ff · outbound

This paper cites Learning multiple tasks with multilinear relationship networks,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Learning multiple tasks with multilinear relationship networks,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.507936Z

Source-reported events for the cited work

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Observation 7857c496-a36b-47bb-b9f3-a7c17606f43f · outbound

This paper cites Uni-Perceiver v2: A Generalist Model for Large-Scale Vision and Vision-Language Tasks.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Uni-Perceiver v2: A Generalist Model for Large-Scale Vision and Vision-Language Tasks

Reference 9

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Source-reported events for the cited work

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Observation 54933430-5e14-4509-9b4b-29228b17890c · outbound

This paper cites Multi-task self-training for learning general representations,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Multi-task self-training for learning general representations,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.496525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 251ac2f1-c950-4153-accc-3766b54714eb · outbound

This paper cites Auxiliary Tasks in Multi-task Learning.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Auxiliary Tasks in Multi-task Learning

Reference 11

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Source-reported events for the cited work

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Observation 4ff03ab5-74ad-462e-b2be-9e2541e5c547 · outbound

This paper cites Which tasks should be learned together in multi-task learning?.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Which tasks should be learned together in multi-task learning?

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.485813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e1240cc0-30cc-4323-b48f-2ab9947af83e · outbound

This paper cites Adaptive auxiliary task weighting for reinforcement learning,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Adaptive auxiliary task weighting for reinforcement learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.473273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1ecd527d-0ffa-4a93-88bd-5036c747f747 · outbound

This paper cites Adapting Auxiliary Losses Using Gradient Similarity.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Adapting Auxiliary Losses Using Gradient Similarity

Reference 14

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Source-reported events for the cited work

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Observation 71f59636-6673-4284-8dd0-d36198dc7189 · outbound

This paper cites Auto-Lambda: Disentangling Dynamic Task Relationships.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Auto-Lambda: Disentangling Dynamic Task Relationships

Reference 15

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Source-reported events for the cited work

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Observation 697b481d-2464-4cf1-8b4a-f57a644bd476 · outbound

This paper cites Multi-task learning using uncertainty to weigh losses for scene geometry and semantics,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Multi-task learning using uncertainty to weigh losses for scene geometry and semantics,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.451355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2da56126-22cc-4318-bc49-3584538396b0 · outbound

This paper cites Indoor segmentation and support inference from rgbd images,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Indoor segmentation and support inference from rgbd images,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.440651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 046a15c8-4615-450b-b5d6-95f3e10ca4fd · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective The cityscapes dataset for semantic urban scene understanding,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.430555Z

Source-reported events for the cited work

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Observation 540a47ce-4e5a-4f1e-9738-915e00b4da89 · outbound

This paper cites Detect what you can: Detecting and representing objects using holistic models and body parts,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Detect what you can: Detecting and representing objects using holistic models and body parts,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.420106Z

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Observation b380731e-981d-4cd3-bc07-24ad909e5546 · outbound

This paper cites End-to-end multitask learning with vision trans- former,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective End-to-end multitask learning with vision trans- former,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.409996Z

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Observation f6dbe1bf-39fe-4566-ad5f-f55507053719 · outbound

This paper cites Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 21

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Observation 4e5fb378-bc90-4499-b7ac-e41fa2360d57 · outbound

This paper cites Towards impartial multi-task learning,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Towards impartial multi-task learning,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.399529Z

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Observation 87ce7ae5-d8f2-4663-92b3-a39ad2c74780 · outbound

This paper cites Real-time memory efficient multitask learning model for autonomous driving,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Real-time memory efficient multitask learning model for autonomous driving,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.389247Z

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Observation 0f278646-0ab9-43c5-baa4-8b4c8283c341 · outbound

This paper cites Umt-net: A uniform multi-task network with adaptive task weighting,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Umt-net: A uniform multi-task network with adaptive task weighting,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.378441Z

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Observation 4e035bbd-b044-4ae6-a8d9-76702ecef741 · outbound

This paper cites Task weighting based on particle filter in deep multi-task learning with a view to uncertainty and performance,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Task weighting based on particle filter in deep multi-task learning with a view to uncertainty and performance,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.366336Z

Source-reported events for the cited work

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Observation 3d5426da-a61e-40a4-9636-04653e9a87be · outbound

This paper cites Evolutionary multitasking with global and local auxiliary tasks for constrained multi- objective optimization,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Evolutionary multitasking with global and local auxiliary tasks for constrained multi- objective optimization,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.355874Z

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Observation dcac3283-cdfe-4119-9b50-a250169ab374 · outbound

This paper cites Multitask learning for joint diagnosis of multiple mental disorders in resting-state fmri,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Multitask learning for joint diagnosis of multiple mental disorders in resting-state fmri,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.345543Z

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Observation 44ca86bc-9067-467b-8410-96bf5bcef4eb · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.335257Z

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Observation 0dafd452-7cf6-4fb8-af65-95988cb74485 · outbound

This paper cites Multi-Task Learning as Multi-Objective Optimization.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Multi-Task Learning as Multi-Objective Optimization

Reference 29

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Observation 5dbef300-be37-46ca-881c-06ebf83855ac · outbound

This paper cites Pareto multi-task learning,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Pareto multi-task learning,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.324913Z

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Observation a7971171-12fb-422e-8e6d-7bbf1e86ed31 · outbound

This paper cites Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.314202Z

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Observation 5cfcd0a7-3b99-4b07-b740-e582fa4e22ff · outbound

This paper cites Gradient surgery for multi-task learning,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Gradient surgery for multi-task learning,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.303561Z

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Observation 869a061e-d4a5-4b2a-a78d-35c6106ac1e8 · outbound

This paper cites Conflict-averse gradient descent for multi-task learning,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Conflict-averse gradient descent for multi-task learning,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.292898Z

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Observation 3f9effab-3c97-40ed-a5f5-32e0d9baa698 · outbound

This paper cites Imagenet large scale visual recognition challenge,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Imagenet large scale visual recognition challenge,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.282406Z

Source-reported events for the cited work

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Observation 2244324b-41c3-4495-9b70-80dcc78ebdc8 · outbound

This paper cites Dynamic task prioritization for multitask learning,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Dynamic task prioritization for multitask learning,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.272260Z

Source-reported events for the cited work

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Observation 14529610-7424-4b12-b7be-6e15bd4ca3bb · outbound

This paper cites End-to-end multi-task learning with attention,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective End-to-end multi-task learning with attention,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.261460Z

Source-reported events for the cited work

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Observation 827f8ffa-68d8-4574-a927-29a52c486f37 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 37

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Observation 8e7f2acd-f403-401c-9980-3ac1545947f8 · outbound

This paper cites Mti-net: Multi-scale task interaction networks for multi-task learning,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Mti-net: Multi-scale task interaction networks for multi-task learning,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.249743Z

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Observation 05b30514-1aa9-4343-9f62-dbccc376725e · outbound

This paper cites Multi-task learning for dense prediction tasks: A survey,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Multi-task learning for dense prediction tasks: A survey,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.237985Z

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Observation 16fe9e81-17ad-4f94-9d7a-01c4447bb986 · outbound

This paper cites Deep residual learning for image recognition,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Deep residual learning for image recognition,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.226819Z

Source-reported events for the cited work

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Observation 6a7f7e68-78a0-411a-ab45-0885c17613d6 · outbound

This paper cites All tokens matter: Token labeling for training better vision transformers,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective All tokens matter: Token labeling for training better vision transformers,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.215852Z

Source-reported events for the cited work

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Observation c2d192f5-6bee-4eac-bcc9-ec2d916b2210 · outbound

This paper cites Composite Learning for Robust and Effective Dense Predictions.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Composite Learning for Robust and Effective Dense Predictions

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-08-11T00:18:16.001689Z

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Observation 439a49be-68d9-418a-8dc4-017713260a54 · outbound

This paper cites Learning multiple layers of features from tiny images,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Learning multiple layers of features from tiny images,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.204123Z

Source-reported events for the cited work

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Observation 21f12610-a9eb-4043-b2de-d9e0e1a10e07 · outbound

This paper cites Very deep convolutional networks for large-scale image recognition,.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Very deep convolutional networks for large-scale image recognition,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:18:16.192060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 564de44e-ede2-4202-aeb6-aa37e71981a2 · outbound

This paper cites an unresolved cited work.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Unresolved cited work

Reference 2022

Resolution: unresolved; raw_fallback, observed 2026-08-11T00:18:16.461901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.