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Paper Citation Record · LEDGER

Sample Efficient Linear Meta-Learning by Alternating Minimization

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2105.08306.

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

pith.paper-citation-record.v1
2105.08306 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:10:44.946179Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T11:56:56.009111Z

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 b69eb140-ffa9-49e3-a38c-c1bfca8c2884 · inbound

PromptRefine: Enhancing Few-Shot Performance on Low-Resource Indic Languages with Example Selection from Related Example Banks cites this paper.

PromptRefine: Enhancing Few-Shot Performance on Low-Resource Indic Languages with Example Selection from Related Example Banks Sample Efficient Linear Meta-Learning by Alternating Minimization

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T20:29:54.087975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:29:54.087975Z digest=sha256:572ab4278fef08085f261267b18a87c2142b3c21798ff6a26dbc5b9fd3b6f350

Observation a6c7bafc-b400-42fd-aecd-5ca855204ccc · inbound

On The Concurrence of Layer-wise Preconditioning Methods and Provable Feature Learning cites this paper.

On The Concurrence of Layer-wise Preconditioning Methods and Provable Feature Learning Sample Efficient Linear Meta-Learning by Alternating Minimization

Reference 103

Resolution
unresolved
no resolver link, observed 2026-08-09T14:47:40.740251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:47:40.740251Z digest=sha256:05f43f7b82a4773b6e77b594f1c0ab242035a4f98641d4f1c28c73d81308d944

Observation 754faaeb-50c0-4d6c-bcf6-8761031094e5 · inbound

Collaborative and Efficient Fine-tuning: Leveraging Task Similarity cites this paper.

Collaborative and Efficient Fine-tuning: Leveraging Task Similarity Sample Efficient Linear Meta-Learning by Alternating Minimization

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-03T03:49:40.538573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:49:40.538573Z digest=sha256:44ba8772762c86d96d5f8767f50fe5f53a9e82b71da1b050c5da241b5802567c

Observation adb75f6d-12d3-48d1-bdfb-5061a7af9b1c · inbound

Multi-Task Representation Learning for Conservative Linear Bandits cites this paper.

Multi-Task Representation Learning for Conservative Linear Bandits Sample Efficient Linear Meta-Learning by Alternating Minimization

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:12:27.892795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-13T07:12:06.759848Z digest=sha256:b907eba86fd80623ece17ff5960ffaae6847067b8ddc15e0fa978ceaac18feca

Observation 4a1241d1-e7aa-4711-a87d-1dedb16a30e3 · inbound

Double Preconditioning (DoPr): Optimization for Test-Time Performance, not Validation Loss cites this paper.

Double Preconditioning (DoPr): Optimization for Test-Time Performance, not Validation Loss Sample Efficient Linear Meta-Learning by Alternating Minimization

Reference 251

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T11:56:56.010536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-06-28T02:35:39.845487Z digest=sha256:2a3bf0f4503992e8f0edcf90b780ab2fc7ef63ca42964663d6954fd605d26e5a

Observation c7ef8b83-49ce-4ac0-9c6b-95af26dd96b4 · inbound

ThinkRetrieve: Retrieval-Augmented Reasoning Traces for Test-Time Scaling cites this paper.

ThinkRetrieve: Retrieval-Augmented Reasoning Traces for Test-Time Scaling Sample Efficient Linear Meta-Learning by Alternating Minimization

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-12T14:10:44.946179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:10:44.946179Z digest=sha256:cdf888ac321697c03775d851b3db504c5d08f4f639fb2c3f6a6b0f8e67ff39d3