Paper Citation Record · LEDGER

GIFT-SW: Gaussian noise Injected Fine-Tuning of Salient Weights for LLMs

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2408.15300.

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

pith.paper-citation-record.v1
2408.15300 v1

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 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:25:29.324004Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T05:47:07.672283Z

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 c7005290-dc20-4d64-b071-9661a2aa3008 · inbound

Improving LoRA with Variational Learning cites this paper.

Improving LoRA with Variational Learning GIFT-SW: Gaussian noise Injected Fine-Tuning of Salient Weights for LLMs

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T00:25:29.324004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 523e0051-c5bd-4a44-ad7c-e5e7988f3850 · inbound

From 2:4 to 8:16 sparsity patterns in LLMs for Outliers and Weights with Variance Correction cites this paper.

From 2:4 to 8:16 sparsity patterns in LLMs for Outliers and Weights with Variance Correction GIFT-SW: Gaussian noise Injected Fine-Tuning of Salient Weights for LLMs

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-19T05:47:07.675126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3bb102d2-c0d5-4828-8536-cd6d2b436c5d · inbound

Motivating Next-Gen Accelerators with Flexible (N:M) Activation Sparsity via Benchmarking Lightweight Post-Training Sparsification Approaches cites this paper.

Motivating Next-Gen Accelerators with Flexible (N:M) Activation Sparsity via Benchmarking Lightweight Post-Training Sparsification Approaches GIFT-SW: Gaussian noise Injected Fine-Tuning of Salient Weights for LLMs

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:41:25.862900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation db059159-49d4-450f-af3d-46e5f1e1d03b · inbound

Super-Tuning: From Activation-Aware Pruning to Sparse Fine-Tuning cites this paper.

Super-Tuning: From Activation-Aware Pruning to Sparse Fine-Tuning GIFT-SW: Gaussian noise Injected Fine-Tuning of Salient Weights for LLMs

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-13T04:08:39.594367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.