Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Evaluating the Generalization Ability of Quantized LLMs: Benchmark, Analysis, and Toolbox
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2406.12928.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T16:10:24.457738Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 1ed240f6-d27d-4786-ac11-27568c9f2e0a · inbound
A Decade of Deep Learning: A Survey on The Magnificent Seven cites this paper.
A Decade of Deep Learning: A Survey on The Magnificent Seven Evaluating the Generalization Ability of Quantized LLMs: Benchmark, Analysis, and Toolbox
Reference 2022
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T16:10:24.457738Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8567caa7-7102-4181-a4d9-49600e8e32d4 · inbound
Quantized Large Language Models in Biomedical Natural Language Processing: Evaluation and Recommendation cites this paper.
Quantized Large Language Models in Biomedical Natural Language Processing: Evaluation and Recommendation Evaluating the Generalization Ability of Quantized LLMs: Benchmark, Analysis, and Toolbox
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T10:38:33.439349Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 343407d5-e3dd-4677-8ed5-093eaf0e6492 · inbound
K-Quantization and its Impact on Output Performance cites this paper.
K-Quantization and its Impact on Output Performance Evaluating the Generalization Ability of Quantized LLMs: Benchmark, Analysis, and Toolbox
Reference 58
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T05:38:04.590418Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.