Paper Citation Record · LEDGER

FineGates: LLMs Finetuning with Compression using Stochastic Gates

As of 12 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2412.12951.

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

pith.paper-citation-record.v1
2412.12951 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:37:39.109971Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

21 of 21 outbound references displayed

verified exact0
verified fuzzy0
unresolved21
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bb345255-2aad-4735-83ba-1ce1393706c9 · outbound

This paper cites LoRA-XS: Low-Rank Adaptation with Extremely Small Number of Parameters.

FineGates: LLMs Finetuning with Compression using Stochastic Gates LoRA-XS: Low-Rank Adaptation with Extremely Small Number of Parameters

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:38.959932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d611bb79-8524-4824-a725-3b8f8a684f6b · outbound

This paper cites One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning.

FineGates: LLMs Finetuning with Compression using Stochastic Gates One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:38.975262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fae90cd4-f1a1-4ce9-a1b3-424393506691 · outbound

This paper cites SparseAdapter: An Easy Approach for Improving the Parameter-Efficiency of Adapters.

FineGates: LLMs Finetuning with Compression using Stochastic Gates SparseAdapter: An Easy Approach for Improving the Parameter-Efficiency of Adapters

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:38.989122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70ba8ea8-e90b-49c6-a122-d4831967591a · outbound

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

FineGates: LLMs Finetuning with Compression using Stochastic Gates The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.025487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43228dba-83be-4515-b305-06cf25f23d0a · outbound

This paper cites Parameter-Efficient Sparsity for Large Language Models Fine-Tuning.

FineGates: LLMs Finetuning with Compression using Stochastic Gates Parameter-Efficient Sparsity for Large Language Models Fine-Tuning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.038878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9534321c-2b14-4854-b86e-977c9c0ecf84 · outbound

This paper cites NoRA: Nested Low-Rank Adaptation for Efficient Fine-Tuning Large Models.

FineGates: LLMs Finetuning with Compression using Stochastic Gates NoRA: Nested Low-Rank Adaptation for Efficient Fine-Tuning Large Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.044748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22da5c8f-a4da-46f6-a705-eeeca38ae19b · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

FineGates: LLMs Finetuning with Compression using Stochastic Gates RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.051681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7900e55e-a855-4440-96ea-a5c8f17129ff · outbound

This paper cites Decoupled Weight Decay Regularization.

FineGates: LLMs Finetuning with Compression using Stochastic Gates Decoupled Weight Decay Regularization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.058919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5969d639-2c32-4121-a031-fc2e550a8b9f · outbound

This paper cites AdapterFusion: Non-Destructive Task Composition for Transfer Learning.

FineGates: LLMs Finetuning with Compression using Stochastic Gates AdapterFusion: Non-Destructive Task Composition for Transfer Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.065819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60fb603f-49ca-4d9e-a071-01d9c8b8f477 · outbound

This paper cites Knowledge Editing in Language Models via Adapted Direct Preference Optimization.

FineGates: LLMs Finetuning with Compression using Stochastic Gates Knowledge Editing in Language Models via Adapted Direct Preference Optimization

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.085414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation edd36266-ceea-4be3-a9e3-f06f940be680 · outbound

This paper cites QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models.

FineGates: LLMs Finetuning with Compression using Stochastic Gates QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.098228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cdab6a2-10f5-4154-b204-6b905bddb292 · outbound

This paper cites LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning.

FineGates: LLMs Finetuning with Compression using Stochastic Gates LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.104166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbffbc6e-f309-4b74-9466-41507d492341 · outbound

This paper cites APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference.

FineGates: LLMs Finetuning with Compression using Stochastic Gates APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.109971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96c5b90a-b226-431f-b89f-30b89c2db25e · outbound

This paper cites Structured Pruning Learns Compact and Accurate Models.

FineGates: LLMs Finetuning with Compression using Stochastic Gates Structured Pruning Learns Compact and Accurate Models

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.091398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c54b1ee3-738c-4924-8ee5-168f49988073 · outbound

This paper cites VeRA: Vector-based Random Matrix Adaptation.

FineGates: LLMs Finetuning with Compression using Stochastic Gates VeRA: Vector-based Random Matrix Adaptation

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.015019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e566352a-b8d7-4344-a89e-df74ff9a09fd · outbound

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

FineGates: LLMs Finetuning with Compression using Stochastic Gates LoRA: Low-Rank Adaptation of Large Language Models

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.008120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6ea905d-3e74-4795-b540-3fd15a901fe5 · outbound

This paper cites Adarankgrad: Adaptive gradient-rank and moments for memory-efficient llms training and fine-tuning.

FineGates: LLMs Finetuning with Compression using Stochastic Gates Adarankgrad: Adaptive gradient-rank and moments for memory-efficient llms training and fine-tuning

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.073074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80f7dbd3-0b05-4750-ac40-522008e61992 · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

FineGates: LLMs Finetuning with Compression using Stochastic Gates Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:39.032181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c609644-d4c2-46a8-bfaf-0397e417528d · outbound

This paper cites Distilling the Knowledge in a Neural Network.

FineGates: LLMs Finetuning with Compression using Stochastic Gates Distilling the Knowledge in a Neural Network

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:38.999966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4a3c265-805d-4a26-ad1d-978f1e2a96e0 · outbound

This paper cites Mixture-of-LoRAs: An Efficient Multitask Tuning for Large Language Models.

FineGates: LLMs Finetuning with Compression using Stochastic Gates Mixture-of-LoRAs: An Efficient Multitask Tuning for Large Language Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:38.982037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d150909c-3950-405c-8c12-b12358e4a58a · outbound

This paper cites Low-Rank Quantization-Aware Training for LLMs.

FineGates: LLMs Finetuning with Compression using Stochastic Gates Low-Rank Quantization-Aware Training for LLMs

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-11T13:37:38.968326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.