Paper Citation Record · LEDGER

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models

As of 17 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2601.16991.

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

pith.paper-citation-record.v1
2601.16991 v3

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T11:47:19.013126Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

27 of 27 outbound references displayed

verified exact0
verified fuzzy0
unresolved27
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e1942df3-4318-4716-9c29-19af8278299c · outbound

This paper cites OLoRA: Orthonormal Low-Rank Adaptation of Large Language Models.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models OLoRA: Orthonormal Low-Rank Adaptation of Large Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.941572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07e53ed3-32cc-468b-9d69-fc6eb781037d · outbound

This paper cites The Llama 3 Herd of Models.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models The Llama 3 Herd of Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.954020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bceffdee-e3e1-4c41-8c1b-723a297f3cd8 · outbound

This paper cites SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.957236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 487fcc5f-1e92-4ee8-b0c6-fcdd4c193f07 · outbound

This paper cites Compresso: Structured Pruning with Collaborative Prompting Learns Compact Large Language Models.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models Compresso: Structured Pruning with Collaborative Prompting Learns Compact Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.960006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a27c13db-4b11-4840-8e0c-9480694bbcef · outbound

This paper cites LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.965575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13d570d9-3a83-4207-96f0-631a0e3de7e2 · outbound

This paper cites Dynamic Low-Rank Sparse Adaptation for Large Language Models.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models Dynamic Low-Rank Sparse Adaptation for Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.968474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63db9635-342b-42c6-9623-22c2914d282a · outbound

This paper cites Mixtral of Experts.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models Mixtral of Experts

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.971307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb4a4133-1aa6-49b9-9167-76d301d32700 · outbound

This paper cites SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.974003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbbe116f-5986-4e9b-851e-916a318179a5 · outbound

This paper cites Sparse Fine-tuning for Inference Acceleration of Large Language Models.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models Sparse Fine-tuning for Inference Acceleration of Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.976787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f460d260-4f8b-4ac8-975d-e2dcc2e462b1 · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.979637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70240f9c-be65-4733-a243-bc25adf70fb6 · outbound

This paper cites SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.982394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b50acfb4-faf9-482d-b512-a90c432d1e82 · outbound

This paper cites DoRA: Weight-Decomposed Low-Rank Adaptation.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models DoRA: Weight-Decomposed Low-Rank Adaptation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.985173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49e2b9d0-afac-44c5-b61e-7e65bf53e567 · outbound

This paper cites PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.987891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab9538ff-bd48-4d6c-bde3-346ec3751bbb · outbound

This paper cites https://ai.meta.com/blog/ llama-4-multimodal-intelligence/ [Accessed: 2025-04-05].

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models https://ai.meta.com/blog/ llama-4-multimodal-intelligence/ [Accessed: 2025-04-05]

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.990878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14a0358b-3384-4c6e-9d8e-236a936f55b0 · outbound

This paper cites GPT-4 Technical Report.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models GPT-4 Technical Report

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.993568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 505ab54c-14aa-4e74-a3b9-fadeb63b9cde · outbound

This paper cites A Simple and Effective Pruning Approach for Large Language Models.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models A Simple and Effective Pruning Approach for Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.996406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fead918-b3db-4ff9-a4dc-300b453ef88c · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.999183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e55e3f5e-b0aa-4b84-88d9-5b2677592d1c · outbound

This paper cites LoRA-GA: Low-Rank Adaptation with Gradient Approximation.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models LoRA-GA: Low-Rank Adaptation with Gradient Approximation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:19.001908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa94d0d5-9420-4ada-868f-ae926a198e00 · outbound

This paper cites LoRA-Pro: Are Low-Rank Adapters Properly Optimized?.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models LoRA-Pro: Are Low-Rank Adapters Properly Optimized?

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:19.004644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f690e976-331a-45ab-a40b-0650d905e719 · outbound

This paper cites Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:19.007455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb8a0118-c2d0-412d-a04b-8d700c39c3c6 · outbound

This paper cites Qwen3 Technical Report.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models Qwen3 Technical Report

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:19.010255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f796b6cc-370a-44bb-b192-68665ea90df1 · outbound

This paper cites MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:19.013126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b74b6600-58a3-47ad-9cbb-f65b496f9671 · outbound

This paper cites Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.962735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad67ffc0-bcc1-4ac2-8b56-d8561be6ac55 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models Training Verifiers to Solve Math Word Problems

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.944765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a46afe7-0550-47c3-b2ad-d7e6881fc708 · outbound

This paper cites QLoRA: Efficient Finetuning of Quantized LLMs.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models QLoRA: Efficient Finetuning of Quantized LLMs

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.950879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf33f51c-f033-4e76-a1ff-2fc64f2a370c · outbound

This paper cites Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.937690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2f7631e-4626-4ba4-b622-9ec015d7eec1 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T11:47:18.947899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.