Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Is Large Language Model Good at Database Knob Tuning? A Comprehensive Experimental Evaluation
As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2408.02213.
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 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T20:56:16.619940Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T03:43:02.171133Z
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 3ca780df-b0dd-4755-a8d1-4c224b850f2a · inbound
A Case for Agentic Tuning: From Documentation to Action in PostgreSQL cites this paper.
A Case for Agentic Tuning: From Documentation to Action in PostgreSQL Is Large Language Model Good at Database Knob Tuning? A Comprehensive Experimental Evaluation
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T03:43:02.174789Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0976df44-76ee-49c0-9bc9-c771d57f992d · inbound
When to Use Which? Benchmarking Optimisers for Configurable Systems under Varying Budgets cites this paper.
When to Use Which? Benchmarking Optimisers for Configurable Systems under Varying Budgets Is Large Language Model Good at Database Knob Tuning? A Comprehensive Experimental Evaluation
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T20:56:16.619940Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e38ecef2-b701-4ae1-86ee-e367f43dbcbf · inbound
IDSTune: A Multi-Agent Collaborative Framework for Integrated Database System Tuning cites this paper.
IDSTune: A Multi-Agent Collaborative Framework for Integrated Database System Tuning Is Large Language Model Good at Database Knob Tuning? A Comprehensive Experimental Evaluation
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T06:05:21.593364Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.