Paper Citation Record · LEDGER

Exploring and Reshaping the Weight Distribution in LLM

As of 18 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2509.00046.

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

pith.paper-citation-record.v1
2509.00046 v1

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:03:06.024248Z

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

9 of 9 outbound references displayed

verified exact0
verified fuzzy4
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a03b4629-a58f-489e-8f03-c7427b7bf793 · outbound

This paper cites These research findings had improved LoRA training for large models to varying degrees.

Exploring and Reshaping the Weight Distribution in LLM These research findings had improved LoRA training for large models to varying degrees

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:03:06.126082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b4cd6423-9a93-4676-a191-16f05256c2e6 · outbound

This paper cites On weight initialization in deep neural networks.

Exploring and Reshaping the Weight Distribution in LLM On weight initialization in deep neural networks

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T17:03:06.020754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c871be18-5e4c-4091-ad9c-ea217cf1f26b · outbound

This paper cites an unresolved cited work.

Exploring and Reshaping the Weight Distribution in LLM Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-05T17:03:06.103159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0be831ed-cedc-4d19-b92c-a639912cadec · outbound

This paper cites SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model.

Exploring and Reshaping the Weight Distribution in LLM SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T17:03:06.017314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b6686b6-5f02-42c6-8620-500168fdad92 · outbound

This paper cites AFLoRA: Adaptive Freezing of Low Rank Adaptation in Parameter Efficient Fine-Tuning of Large Models.

Exploring and Reshaping the Weight Distribution in LLM AFLoRA: Adaptive Freezing of Low Rank Adaptation in Parameter Efficient Fine-Tuning of Large Models

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-05T17:03:06.024248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 922da3e2-cf1f-4225-afa3-0426737c7b41 · outbound

This paper cites Let the weight matrix in any given layer be represented by matrix X.

Exploring and Reshaping the Weight Distribution in LLM Let the weight matrix in any given layer be represented by matrix X

Reference 1980

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:03:06.092949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b062fb5a-e925-4b35-9e63-f91df1136b76 · outbound

This paper cites Other distribution models, such as multivariate α-stable distribution (Li et al., 2024), were also used in modeling and analyzing model parameters.

Exploring and Reshaping the Weight Distribution in LLM Other distribution models, such as multivariate α-stable distribution (Li et al., 2024), were also used in modeling and analyzing model parameters

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:03:06.114734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dbf23cf5-02e7-463c-a302-41a2aeb15c19 · outbound

This paper cites an unresolved cited work.

Exploring and Reshaping the Weight Distribution in LLM Unresolved cited work

Reference 2024

Resolution: unresolved; raw_fallback, observed 2026-08-05T17:03:06.139462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 68eadc85-7703-417f-b0d2-63e248730197 · outbound

This paper cites In addition to the models themselves, the referen ce models also include SmolLM2-1.7B and LLaMA3.2-8B- Instruct, which have more weights.

Exploring and Reshaping the Weight Distribution in LLM In addition to the models themselves, the referen ce models also include SmolLM2-1.7B and LLaMA3.2-8B- Instruct, which have more weights

Reference 2025

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:03:06.082865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

No inbound Pith citation observations are available.