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Paper Citation Record · LEDGER

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

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 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 11 of 11 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 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:14:50.575784Z

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 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.

source=pdf_text observed=2026-08-07T12:14:50.575784Z digest=sha256:6ef4d42792b242f505b76fb2776c0b2b4096c618ed36fc21ba55ec52b306af1d

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.

source=pdf_text observed=2026-08-07T10:20:16.595380Z digest=sha256:1f9958492026bed4584f7eb0000d3c271d115c7648f17b88abe84cf219d0fead

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.

source=pdf_text observed=2026-08-06T20:29:50.028433Z digest=sha256:82671f7ab7446f513fc492de0e40a71708402006c0945537c6d563e57aa640fb

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.

source=pdf_text observed=2026-08-05T18:53:59.976364Z digest=sha256:b31cb18e0c0e6e972e9cd50105991b13789797a7ebc8865bf411dca50b7922bc

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T16:42:48.902337Z digest=sha256:6262cd70ef963a174057a8de8c04942ef55f4d04c3830357f2e231d3de4e241b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T03:18:36.518485Z digest=sha256:830f68df5181c361ff2e8434e0053288da951dd43255614f4992e592e205090c

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.

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:40:14.390479Z digest=sha256:db9e1c2c46a465baa93c635471fb4f32f9e23c73eccc4965a11fe7c30081da33

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-07-01T06:15:35.508989Z digest=sha256:b7f7f15468968e9a1f3addd13b7bf215c340d908d33b9abf0df9c05ce0592b48

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-07-02T18:34:23.173135Z digest=sha256:ec21525a8480c00cbb2fbce9082ab9a7ba44821087c4218e896f05e6f14a136f

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.

source=pdf_text observed=2026-08-02T09:22:54.419084Z digest=sha256:5cf6cdf67515e287f715150ab885d8c454a68ffb7331cbe812ce6b188b02e79e

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.

source=pdf_text observed=2026-08-01T07:56:34.625595Z digest=sha256:2aa7035e16e8f07e7972206972eb86d97cf744e03d413949850a358c45694bb1