Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MetaTune: Meta-Learning Based Cost Model for Fast and Efficient Auto-tuning Frameworks
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2102.04199.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:11:25.963826Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T09:51:00.647940Z
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 69c7033b-9341-4a94-b76a-c39c11ad4fcc · inbound
COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer Learning cites this paper.
COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer Learning MetaTune: Meta-Learning Based Cost Model for Fast and Efficient Auto-tuning Frameworks
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:11:25.963826Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a251c330-a455-4c39-9431-cb65a0ffef1a · inbound
TCL: Enabling Fast and Efficient Cross-Hardware Tensor Program Optimization via Continual Learning cites this paper.
TCL: Enabling Fast and Efficient Cross-Hardware Tensor Program Optimization via Continual Learning MetaTune: Meta-Learning Based Cost Model for Fast and Efficient Auto-tuning Frameworks
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T09:51:00.652710Z
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.