Paper Citation Record · LEDGER

Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2111.10603.

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

pith.paper-citation-record.v1
2111.10603 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 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 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:18:57.016813Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T18:37:15.940790Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 209e67a7-cce9-4d72-b7e6-dbd73a342b44 · inbound

An End-to-End Robust Point Cloud Semantic Segmentation Network with Single-Step Conditional Diffusion Models cites this paper.

An End-to-End Robust Point Cloud Semantic Segmentation Network with Single-Step Conditional Diffusion Models Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T13:22:08.621779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective cites this paper.

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

Resolution: unresolved; no resolver link, observed 2026-08-11T00:18:15.884844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47f94d36-0331-4981-92f6-2dcb37f410a9 · inbound

Fantastic Multi-Task Gradient Updates and How to Find Them In a Cone cites this paper.

Fantastic Multi-Task Gradient Updates and How to Find Them In a Cone Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T19:55:16.839556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30e47178-7d78-4285-bcf6-4f99de4d5a7a · inbound

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class cites this paper.

FastCAR: Fast Classification And Regression for Task Consolidation in Multi-Task Learning to Model a Continuous Property Variable of Detected Object Class Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T12:14:50.575784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8eb7ccda-32aa-4ce8-a931-5fbd297f81a9 · inbound

Controlled Data Rebalancing in Multi-Task Learning for Real-World Image Super-Resolution cites this paper.

Controlled Data Rebalancing in Multi-Task Learning for Real-World Image Super-Resolution Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:16.595380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffcb26d4-d58d-476f-840f-3c2605cd73f5 · inbound

FairHuman: Boosting Hand and Face Quality in Human Image Generation with Minimum Potential Delay Fairness in Diffusion Models cites this paper.

FairHuman: Boosting Hand and Face Quality in Human Image Generation with Minimum Potential Delay Fairness in Diffusion Models Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T20:29:50.028433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdd831d0-f166-4805-a240-6d54f924f8d0 · inbound

AutoScale: Linear Scalarization Guided by Multi-Task Optimization Metrics cites this paper.

AutoScale: Linear Scalarization Guided by Multi-Task Optimization Metrics Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T18:53:59.976364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee2a7dcc-610b-42d3-a27d-23060c3d36c5 · inbound

Delve into the Applicability of Advanced Optimizers for Multi-Task Learning cites this paper.

Delve into the Applicability of Advanced Optimizers for Multi-Task Learning Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:20:59.026124Z

Source-reported events for the cited work

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

Observation 0931f30e-ffaf-4633-a320-25e618009b06 · inbound

Flatness and Gradient Alignment Are Both Necessary: Spectral-Aware Gradient-Aligned Exploration for Multi-Distribution Learning cites this paper.

Flatness and Gradient Alignment Are Both Necessary: Spectral-Aware Gradient-Aligned Exploration for Multi-Distribution Learning Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:20:55.394262Z

Source-reported events for the cited work

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

Observation ebf2bbd7-c066-412a-9686-61f5c1c226a3 · inbound

Flatness and Gradient Alignment Are Both Necessary: Spectral-Aware Gradient-Aligned Exploration for Multi-Distribution Learning cites this paper.

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-02T14:40:14.390479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 959698ef-f12b-444a-8051-8c1203665e43 · inbound

ExPLoRe: Expert Patch-Level Loss Routing for Multi-Objective Masked Image Modeling cites this paper.

ExPLoRe: Expert Patch-Level Loss Routing for Multi-Objective Masked Image Modeling Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-01T09:45:40.104876Z

Source-reported events for the cited work

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

Observation 9e9540f7-01c9-46a9-8b99-0b9ade3dbc71 · inbound

Exploring Line Bundle Standard Models with Transformers cites this paper.

Exploring Line Bundle Standard Models with Transformers Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-07-02T18:37:15.942242Z

Source-reported events for the cited work

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

Observation f59f50f1-589c-44b4-b3e6-b022de86c9f8 · inbound

Exploring Line Bundle Standard Models with Transformers cites this paper.

Exploring Line Bundle Standard Models with Transformers Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-02T09:22:54.419084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b6508e0-d203-4c0a-8d58-f746c7b42423 · inbound

Multi-Task Learning for Heterogeneous Prediction from Video Game State with Transfer Learning cites this paper.

Multi-Task Learning for Heterogeneous Prediction from Video Game State with Transfer Learning Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T07:56:34.625595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a72693b-dc93-4892-8668-43d842934e5d · inbound

Learning in Deep Networks under Dale's Constraint cites this paper.

Learning in Deep Networks under Dale's Constraint Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 240

Resolution: unresolved; no resolver link, observed 2026-08-10T17:39:43.367160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4863d3b7-21ad-4c15-ab23-e427a7bacc6d · inbound

Unsupervised Domain Adaptation for Multitask Image Analysis in Realistic Context with Extreme Label Shift; Application to the CTAO first Large Sized Telescope cites this paper.

Unsupervised Domain Adaptation for Multitask Image Analysis in Realistic Context with Extreme Label Shift; Application to the CTAO first Large Sized Telescope Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T13:50:28.206292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 776c5db8-bd00-4a08-92f2-54dd46faaa44 · inbound

Efficient Hessian-Free Methods for Multi-Objective Bilevel Optimization with Nonconvex Lower Level cites this paper.

Efficient Hessian-Free Methods for Multi-Objective Bilevel Optimization with Nonconvex Lower Level Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T04:18:57.016813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.