Paper Citation Record · LEDGER

Learning to Multi-Task by Active Sampling

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1702.06053.

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

pith.paper-citation-record.v1
1702.06053 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:48:45.565773Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-20T07:18:07.312432Z

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 3b3be701-7cd8-4b75-be77-73e5a9f0424b · inbound

Feature Partitioning for Efficient Multi-Task Architectures cites this paper.

Feature Partitioning for Efficient Multi-Task Architectures Learning to Multi-Task by Active Sampling

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-14T13:48:45.565773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce5de5dc-6ebc-41ad-8ae1-ededf9251501 · inbound

A Tensor Low-Rank Approximation for Value Functions in Multi-Task Reinforcement Learning cites this paper.

A Tensor Low-Rank Approximation for Value Functions in Multi-Task Reinforcement Learning Learning to Multi-Task by Active Sampling

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T19:13:44.769337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63da4f79-cbc2-45a5-8b1a-8082ceaea982 · inbound

Vision Generalist Model: A Survey cites this paper.

Vision Generalist Model: A Survey Learning to Multi-Task by Active Sampling

Reference 154

Resolution: unresolved; no resolver link, observed 2026-08-07T04:43:58.014654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86f9bb76-31f0-4a8a-899f-490890e2120e · inbound

Heterogeneity-Aware Dataset Scheduling for Efficient Audio Large Language Model Training cites this paper.

Heterogeneity-Aware Dataset Scheduling for Efficient Audio Large Language Model Training Learning to Multi-Task by Active Sampling

Reference 40

Resolution: metadata mismatch; local_arxiv, observed 2026-05-20T07:18:07.313802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7b6acbd8-61a2-467c-8169-3c7126350885 · inbound

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

Learning in Deep Networks under Dale's Constraint Learning to Multi-Task by Active Sampling

Reference 185

Resolution: unresolved; no resolver link, observed 2026-08-10T17:39:43.082719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.