Pith. sign in

Paper Citation Record · LEDGER

Maestro: Uncovering Low-Rank Structures via Trainable Decomposition

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2308.14929.

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

pith.paper-citation-record.v1
2308.14929 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T21:19:39.248766Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T19:33:42.331727Z

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 a6caecd1-51d3-4de4-ac5b-3637adbc0d13 · inbound

Aequa: Fair Model Rewards in Collaborative Learning via Slimmable Networks cites this paper.

Aequa: Fair Model Rewards in Collaborative Learning via Slimmable Networks Maestro: Uncovering Low-Rank Structures via Trainable Decomposition

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-08T21:19:39.248766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T21:19:39.248766Z digest=sha256:74fca995a6723f91f8fe83f4214c6130a9718172bbf16856db21004e6a4c2846

Observation 74d17b3a-fa00-451d-a0f1-0e6c992e4ce2 · inbound

Forget the Data and Fine-Tuning! Just Fold the Network to Compress cites this paper.

Forget the Data and Fine-Tuning! Just Fold the Network to Compress Maestro: Uncovering Low-Rank Structures via Trainable Decomposition

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T19:04:45.574257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T19:04:45.574257Z digest=sha256:3c1a6ae1f05f89c248edaf6f7f913a53fab511e37b2f188cb4c9961a4c53c485

Observation 9764ebea-c89f-4da1-b8eb-fbe53c0211a3 · inbound

Response-Conditioned Parallel-to-Sequential Orchestration for Multi-Agent Systems cites this paper.

Response-Conditioned Parallel-to-Sequential Orchestration for Multi-Agent Systems Maestro: Uncovering Low-Rank Structures via Trainable Decomposition

Reference 114

Resolution
verified exact
arxiv_id, observed 2026-05-20T19:33:42.334728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-20T19:30:13.469451Z digest=sha256:64bc99ff82f049de3aea13e296d2fdabd9731fe2d81170bdaa241fafa1808376