Paper Citation Record · LEDGER

Memory-Efficient Fine-Tuning of Transformers via Token Selection

As of 11 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2501.18824.

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

pith.paper-citation-record.v1
2501.18824 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T22:27:57.510013Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

14 of 14 outbound references displayed

verified exact0
verified fuzzy4
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8ef818ad-cc31-4e93-a54e-1e0305bf1f79 · outbound

This paper cites an unresolved cited work.

Memory-Efficient Fine-Tuning of Transformers via Token Selection Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-09T22:27:57.767486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b1a0b597-b711-43eb-8665-10a9fb8ca343 · outbound

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

Memory-Efficient Fine-Tuning of Transformers via Token Selection LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T22:27:57.499818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation caed8a28-d24e-424a-9427-b31fa3f31015 · outbound

This paper cites In Forty-first Interna- tional Conference on Machine Learning, ICML 2024.

Memory-Efficient Fine-Tuning of Transformers via Token Selection In Forty-first Interna- tional Conference on Machine Learning, ICML 2024

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:27:57.715211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8fb641aa-1811-40ec-b500-8e2c05b7479e · outbound

This paper cites Training Deep Nets with Sublinear Memory Cost.

Memory-Efficient Fine-Tuning of Transformers via Token Selection Training Deep Nets with Sublinear Memory Cost

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-09T22:27:57.445032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fd6fc28-1f56-45c1-b38b-90404370fb59 · outbound

This paper cites Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey.

Memory-Efficient Fine-Tuning of Transformers via Token Selection Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-09T22:27:57.455539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af9e9e14-1c63-4ddb-9b35-615c3d4b5723 · outbound

This paper cites In NeurIPS.

Memory-Efficient Fine-Tuning of Transformers via Token Selection In NeurIPS

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:27:57.731228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8879a57c-552e-43c6-8cdb-c62724b90775 · outbound

This paper cites Orca: Progressive Learning from Complex Explanation Traces of GPT-4.

Memory-Efficient Fine-Tuning of Transformers via Token Selection Orca: Progressive Learning from Complex Explanation Traces of GPT-4

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-09T22:27:57.483737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 882d0c3e-f029-4b2b-b090-c3fbaad403bf · outbound

This paper cites In Findings of the As- sociation for Computational Linguistics, ACL 2024, Bangkok, Thailand and virtual meeting, August 11- 16, 2024, pages 467–484.

Memory-Efficient Fine-Tuning of Transformers via Token Selection In Findings of the As- sociation for Computational Linguistics, ACL 2024, Bangkok, Thailand and virtual meeting, August 11- 16, 2024, pages 467–484

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:27:57.748100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 32863bfb-49ed-4d04-9512-44cdb087025f · outbound

This paper cites an unresolved cited work.

Memory-Efficient Fine-Tuning of Transformers via Token Selection Unresolved cited work

Reference 2823

Resolution: unresolved; raw_fallback, observed 2026-08-09T22:27:57.697322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1a791c04-31be-45ec-8a38-b614ad31caa0 · outbound

This paper cites LoRA Dropout as a Sparsity Regularizer for Overfitting Control.

Memory-Efficient Fine-Tuning of Transformers via Token Selection LoRA Dropout as a Sparsity Regularizer for Overfitting Control

Reference 4597

Resolution: unresolved; no resolver link, observed 2026-08-09T22:27:57.473492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47dc1100-b9fc-4f12-bdf1-3798e5d97740 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Memory-Efficient Fine-Tuning of Transformers via Token Selection Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 7328

Resolution: unresolved; no resolver link, observed 2026-08-09T22:27:57.438842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c711569-6e18-461d-bef6-0b8ad40ea50b · outbound

This paper cites Sarkar Snigdha Sarathi Das, Haoran Zhang, Peng Shi, Wenpeng Yin, and Rui Zhang.

Memory-Efficient Fine-Tuning of Transformers via Token Selection Sarkar Snigdha Sarathi Das, Haoran Zhang, Peng Shi, Wenpeng Yin, and Rui Zhang

Reference 8502

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:27:57.785368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 67236b7d-9c31-4678-b13d-145df330ff74 · outbound

This paper cites What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning.

Memory-Efficient Fine-Tuning of Transformers via Token Selection What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning

Reference 8515

Resolution: unresolved; no resolver link, observed 2026-08-09T22:27:57.466632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17ac2900-f37b-4dd1-b210-3a57563853f0 · outbound

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

Memory-Efficient Fine-Tuning of Transformers via Token Selection Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 8740

Resolution: unresolved; no resolver link, observed 2026-08-09T22:27:57.494378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.