Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
INT2.1: Towards Fine-Tunable Quantized Large Language Models with Error Correction through Low-Rank Adaptation
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2306.08162.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:00:19.503155Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T11:32:37.158188Z
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 b8e8029a-98e8-4fea-9816-130cc78f2513 · inbound
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey cites this paper.
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey INT2.1: Towards Fine-Tunable Quantized Large Language Models with Error Correction through Low-Rank Adaptation
Reference 128
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T11:32:37.159666Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d9fbfd4e-e824-401d-b391-772d2b489a83 · inbound
Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models cites this paper.
Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models INT2.1: Towards Fine-Tunable Quantized Large Language Models with Error Correction through Low-Rank Adaptation
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:00:19.503155Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 200862cd-924e-415c-889b-9bcebea329f2 · inbound
Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs cites this paper.
Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs INT2.1: Towards Fine-Tunable Quantized Large Language Models with Error Correction through Low-Rank Adaptation
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T15:52:44.877779Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.