Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Leveraging Large Language Models for Solving Rare MIP Challenges
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2409.04464.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T21:27:15.041889Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-21T03:59:32.501001Z
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 416ce0a2-4183-4c4a-804d-488cedfd8ddd · inbound
A Survey of Optimization Modeling Meets LLMs: Progress and Future Directions cites this paper.
A Survey of Optimization Modeling Meets LLMs: Progress and Future Directions Leveraging Large Language Models for Solving Rare MIP Challenges
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T21:27:15.041889Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6a131182-a535-4e25-9d96-fd63ca3a9949 · inbound
Foundational Design Principles and Patterns for Building Robust and Adaptive GenAI-Native Systems cites this paper.
Foundational Design Principles and Patterns for Building Robust and Adaptive GenAI-Native Systems Leveraging Large Language Models for Solving Rare MIP Challenges
Reference 60
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T22:11:52.696751Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation a8edc6a2-c95e-469a-af4a-ca22583c672f · inbound
Large Language Models for Operations Research: A Comprehensive Survey cites this paper.
Large Language Models for Operations Research: A Comprehensive Survey Leveraging Large Language Models for Solving Rare MIP Challenges
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T03:59:32.502657Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.