Paper Citation Record · LEDGER

L4Q: Parameter Efficient Quantization-Aware Fine-Tuning on Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.04902.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2402.04902 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T10:26:45.444990Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-02T02:26:26.288934Z

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 f3a392f7-95dc-4c83-b71e-024c83b9fa6a · inbound

LowRA: Accurate and Efficient LoRA Fine-Tuning of LLMs under 2 Bits cites this paper.

LowRA: Accurate and Efficient LoRA Fine-Tuning of LLMs under 2 Bits L4Q: Parameter Efficient Quantization-Aware Fine-Tuning on Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-08T10:26:45.444990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48040bbd-4457-4085-ae98-e6fee911a13b · inbound

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead cites this paper.

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead L4Q: Parameter Efficient Quantization-Aware Fine-Tuning on Large Language Models

Reference 147

Resolution: unresolved; no resolver link, observed 2026-08-06T21:36:33.513616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0e8191e-a3c3-4be4-a457-07a3b660c81e · inbound

LLM Compression with Jointly Optimizing Architectural and Quantization choices cites this paper.

LLM Compression with Jointly Optimizing Architectural and Quantization choices L4Q: Parameter Efficient Quantization-Aware Fine-Tuning on Large Language Models

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:26:26.291122Z

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 37aaca53-1674-4d18-9d8c-b2499547982e · inbound

TASQ: Temporal-Adaptive Bit Sparsification Quantization for Diffusion Models cites this paper.

TASQ: Temporal-Adaptive Bit Sparsification Quantization for Diffusion Models L4Q: Parameter Efficient Quantization-Aware Fine-Tuning on Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-08T01:04:45.762544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.