Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MQBench: Towards Reproducible and Deployable Model Quantization Benchmark
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2111.03759.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:50:07.377873Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T15:16:58.731796Z
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 140a9275-d8b2-42de-8e43-c97d3e00c5db · inbound
NeUQI: Near-Optimal Uniform Quantization Parameter Initialization for Low-Bit LLMs cites this paper.
NeUQI: Near-Optimal Uniform Quantization Parameter Initialization for Low-Bit LLMs MQBench: Towards Reproducible and Deployable Model Quantization Benchmark
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:50:07.377873Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eafdccf2-2892-40e1-a880-2b1f36cb1ebf · inbound
Progressive Element-wise Gradient Estimation for Neural Network Quantization cites this paper.
Progressive Element-wise Gradient Estimation for Neural Network Quantization MQBench: Towards Reproducible and Deployable Model Quantization Benchmark
Reference 11
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T15:16:58.759186Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 68d124ff-27aa-463a-9aa8-c0b70886a85a · inbound
Efficient Tuning Before Low-Bit Post-Training Quantization for Stochastic Gradient Descent-optimized Models cites this paper.
Efficient Tuning Before Low-Bit Post-Training Quantization for Stochastic Gradient Descent-optimized Models MQBench: Towards Reproducible and Deployable Model Quantization Benchmark
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T06:58:40.928481Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.