Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Benchmarking End-To-End Performance of AI-Based Chip Placement Algorithms
As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.15026.
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 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-27T02:11:34.174504Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T19:08:49.856956Z
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 41fcd4f4-c55a-4de6-bd5a-98b6630a623b · inbound
CapBench: A Multi-PDK Dataset for Machine-Learning-Based Post-Layout Capacitance Extraction cites this paper.
CapBench: A Multi-PDK Dataset for Machine-Learning-Based Post-Layout Capacitance Extraction Benchmarking End-To-End Performance of AI-Based Chip Placement Algorithms
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T09:01:00.056560Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation df5693fa-e65e-4154-b75a-1c11b9626757 · inbound
PDAGENT-BENCH: Characterizing, Grounding, and Architecting LLM Agents for VLSI Physical Design cites this paper.
PDAGENT-BENCH: Characterizing, Grounding, and Architecting LLM Agents for VLSI Physical Design Benchmarking End-To-End Performance of AI-Based Chip Placement Algorithms
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T19:08:49.858617Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.