Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Improving Quantization with Post-Training Model Expansion
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2503.17513.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T12:09:57.908970Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T23:52:53.019252Z
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 0e535ed3-b364-49a3-90a1-a43a51c32b7f · inbound
Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs cites this paper.
Gradual Binary Search and Dimension Expansion : A general method for activation quantization in LLMs Improving Quantization with Post-Training Model Expansion
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T12:09:57.908970Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 458f9eb8-514f-4c4d-868e-13eeebb425e9 · inbound
Provable Post-Training Quantization: Theoretical Analysis of OPTQ and Qronos cites this paper.
Provable Post-Training Quantization: Theoretical Analysis of OPTQ and Qronos Improving Quantization with Post-Training Model Expansion
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T23:52:53.023344Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation eb27f43b-6c2e-4215-b110-708e8b337510 · inbound
When Can Depth Replace Precision? A Resource Theory of Quantized Neural Computation cites this paper.
When Can Depth Replace Precision? A Resource Theory of Quantized Neural Computation Improving Quantization with Post-Training Model Expansion
Reference 138
- Resolution
- unresolved
- no resolver link, observed 2026-07-30T23:38:38.591216Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.