Paper Citation Record · LEDGER

Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2401.04151.

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

pith.paper-citation-record.v1
2401.04151 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 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 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:39:15.112684Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T01:56:28.082849Z

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 aa91e398-5f96-4f74-8425-5620fcb0f043 · inbound

GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection cites this paper.

GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-16T23:51:50.267050Z

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 549faef3-f56d-47a5-a59f-9845a7187398 · inbound

COAP: Memory-Efficient Training with Correlation-Aware Gradient Projection cites this paper.

COAP: Memory-Efficient Training with Correlation-Aware Gradient Projection Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-12T12:41:58.476443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 633d513e-30ba-426f-8b95-e4914ac942ce · inbound

Domain-adaptative Continual Learning for Low-resource Tasks: Evaluation on Nepali cites this paper.

Domain-adaptative Continual Learning for Low-resource Tasks: Evaluation on Nepali Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-11T12:46:10.136805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5a21a27-83b8-4fb9-b0b3-e7605dcd7369 · inbound

Optimizing Large Language Models with an Enhanced LoRA Fine-Tuning Algorithm for Efficiency and Robustness in NLP Tasks cites this paper.

Optimizing Large Language Models with an Enhanced LoRA Fine-Tuning Algorithm for Efficiency and Robustness in NLP Tasks Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T04:33:58.745420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 936165a6-735a-48aa-8781-a13dfd1e8e1a · inbound

GWT: Scalable Optimizer State Compression for Large Language Model Training cites this paper.

GWT: Scalable Optimizer State Compression for Large Language Model Training Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-23T05:57:36.560070Z

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 45e386fb-90c4-46cf-a2be-b0bb72a60b23 · inbound

Sparse Gradient Compression for Fine-Tuning Large Language Models cites this paper.

Sparse Gradient Compression for Fine-Tuning Large Language Models Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-09T19:36:17.865189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e1eff25-4cd1-4051-8c2d-52f462d793c4 · inbound

A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models cites this paper.

A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-08T13:31:42.043331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d2440e1-5467-40fe-a287-2a3902ad38b2 · inbound

HRP: High-Rank Preheating for Superior LoRA Initialization cites this paper.

HRP: High-Rank Preheating for Superior LoRA Initialization Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-08T11:51:10.367578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd537a85-b282-4731-aec7-96b6677bb8b2 · inbound

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting cites this paper.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T14:46:01.867719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8de89e86-fb84-41c7-92c5-cc8898bca693 · inbound

One Rank at a Time: Cascading Error Dynamics in Sequential Learning cites this paper.

One Rank at a Time: Cascading Error Dynamics in Sequential Learning Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-07T13:10:39.293469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b6b1f12-c26b-44b4-ad24-37fe461fe5ab · inbound

GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation cites this paper.

GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T11:17:59.334061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02751e2b-b7ab-4063-afd0-1cc9765b7aea · inbound

Continual Gradient Low-Rank Projection Fine-Tuning for LLMs cites this paper.

Continual Gradient Low-Rank Projection Fine-Tuning for LLMs Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T20:35:05.707590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b6b4978-fe65-40f1-8cd1-f3b1e682c82b · inbound

CR-Net: Scaling Parameter-Efficient Training with Cross-Layer Low-Rank Structure cites this paper.

CR-Net: Scaling Parameter-Efficient Training with Cross-Layer Low-Rank Structure Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-18T14:52:41.226701Z

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 ab3e1090-b895-457f-96a7-364cefe9d59d · inbound

Geometrically Principled Randomized Optimization for Efficient LLM Training cites this paper.

Geometrically Principled Randomized Optimization for Efficient LLM Training Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T12:51:26.589123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8c8da44-a547-4ce8-9d39-9f5760cb8e1b · inbound

BoostLoRA: Growing Effective Rank by Boosting Adapters cites this paper.

BoostLoRA: Growing Effective Rank by Boosting Adapters Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-12T10:06:27.701529Z

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 79b0b52b-7e68-448a-a44d-96174b20f417 · inbound

Structural Correspondence and Universal Approximation in Diagonal plus Low-Rank Neural Networks cites this paper.

Structural Correspondence and Universal Approximation in Diagonal plus Low-Rank Neural Networks Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:36:07.904465Z

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 25fe2bd5-ce72-440e-8b00-41b57b0b42af · inbound

Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training cites this paper.

Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 203

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:05:56.682285Z

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 d3e60335-3195-4253-a95e-3f9efbce9a45 · inbound

SMoA: Spectrum Modulation Adapter for Parameter-Efficient Fine-Tuning cites this paper.

SMoA: Spectrum Modulation Adapter for Parameter-Efficient Fine-Tuning Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-21T06:03:59.406406Z

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 915fac9a-2630-4c5e-a13b-ef25451f86a7 · inbound

ChunkFT: Byte-Streamed Optimization for Memory-Efficient Full Fine-Tuning cites this paper.

ChunkFT: Byte-Streamed Optimization for Memory-Efficient Full Fine-Tuning Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:49:41.042736Z

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 f9e8e486-ad04-4021-bd09-540f1ee3dc7a · inbound

DECA: Decentralizing Block-Wise Adam for Efficient LLM Full-Parameter Fine-Tuning on Non-IID Data cites this paper.

DECA: Decentralizing Block-Wise Adam for Efficient LLM Full-Parameter Fine-Tuning on Non-IID Data Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:56:28.084885Z

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 827f161a-4c36-4e19-b0a1-6ddabec7817c · inbound

Theoretical Foundations of Communication-Efficient, Robust, and Practical Distributed and Federated Optimization cites this paper.

Theoretical Foundations of Communication-Efficient, Robust, and Practical Distributed and Federated Optimization Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 281

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:15.112684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.