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Paper Citation Record · LEDGER

The Scaling Law for LoRA Base on Mutual Information Upper Bound

As of 12 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2501.03152.

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

pith.paper-citation-record.v1
2501.03152 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:58:52.619058Z

measured 19 of 19 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

19 of 19 outbound references displayed

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  • verified fuzzy1
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 68c52571-d031-4cc8-8afd-012665368e96 · outbound

This paper cites Sparse Low-rank Adaptation of Pre-trained Language Models.

The Scaling Law for LoRA Base on Mutual Information Upper Bound Sparse Low-rank Adaptation of Pre-trained Language Models

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b3a54f99-1edb-4b6f-8359-5b0d7da3857f · outbound

This paper cites In Proceedings of the 62nd Annual Meeting of the Association for Compu- tational Linguistics (Volume 1: Long Papers), pages 1932–1945.

The Scaling Law for LoRA Base on Mutual Information Upper Bound In Proceedings of the 62nd Annual Meeting of the Association for Compu- tational Linguistics (Volume 1: Long Papers), pages 1932–1945

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-10T21:58:52.953660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 28d21235-2da8-4b27-8229-d00da5723e08 · outbound

This paper cites The Llama 3 Herd of Models.

The Scaling Law for LoRA Base on Mutual Information Upper Bound The Llama 3 Herd of Models

Reference 6

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source=pdf_text observed=2026-08-10T21:58:52.553978Z digest=sha256:0d601d565b21167bc28f7d872efe93f213a39d7f8a275bddfc3cec9e85613f06

Observation ba757bc8-b355-4435-9040-cfd4061f6034 · outbound

This paper cites In-context Autoencoder for Context Compression in a Large Language Model.

The Scaling Law for LoRA Base on Mutual Information Upper Bound In-context Autoencoder for Context Compression in a Large Language Model

Reference 7

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:58:52.558962Z digest=sha256:31904682db70de5e6ae6b0a68af24e6e78dc7126ea4f14fb710450806d2675a9

Observation 019b5182-381d-42ab-b947-6a1e708f9a56 · outbound

This paper cites LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition.

The Scaling Law for LoRA Base on Mutual Information Upper Bound LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition

Reference 9

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:58:52.569132Z digest=sha256:3ee2159789a8cbd7f0eb68acfc3d95d916e9e3cbd5ae165429192afd9169c9f4

Observation c9e70e27-54a6-4b89-bb42-9ae954f6f404 · outbound

This paper cites Towards Incremental Learning in Large Language Models: A Critical Review.

The Scaling Law for LoRA Base on Mutual Information Upper Bound Towards Incremental Learning in Large Language Models: A Critical Review

Reference 10

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Unavailable: canonical work link unavailable.

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Observation 452ce9ff-988e-43a2-9400-d3e8d88adf0c · outbound

This paper cites When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications.

The Scaling Law for LoRA Base on Mutual Information Upper Bound When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

Reference 12

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Observation 25d77728-3c89-49b4-b4d7-b43ce2105560 · outbound

This paper cites A Survey on LoRA of Large Language Models.

The Scaling Law for LoRA Base on Mutual Information Upper Bound A Survey on LoRA of Large Language Models

Reference 13

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Observation 4bb3142e-730b-465f-b617-bdea726661ba · outbound

This paper cites IRCAN: Mitigating Knowledge Conflicts in LLM Generation via Identifying and Reweighting Context-Aware Neurons.

The Scaling Law for LoRA Base on Mutual Information Upper Bound IRCAN: Mitigating Knowledge Conflicts in LLM Generation via Identifying and Reweighting Context-Aware Neurons

Reference 15

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metadata mismatch
local_arxiv, observed 2026-08-10T21:58:52.727602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation bae52bfb-41b7-478b-9f05-0f695f45ca6b · outbound

This paper cites Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models.

The Scaling Law for LoRA Base on Mutual Information Upper Bound Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models

Reference 16

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Unavailable: canonical work link unavailable.

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Observation c05772d7-7620-4f5c-b558-4ec2cbf3b27e · outbound

This paper cites MoRAL: MoE Augmented LoRA for LLMs' Lifelong Learning.

The Scaling Law for LoRA Base on Mutual Information Upper Bound MoRAL: MoE Augmented LoRA for LLMs' Lifelong Learning

Reference 17

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Observation 19cd457d-ea9d-4d08-be66-a3eb4c070df3 · outbound

This paper cites When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method.

The Scaling Law for LoRA Base on Mutual Information Upper Bound When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 19

Resolution
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no resolver link, observed 2026-08-10T21:58:52.619058Z

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Unavailable: canonical work link unavailable.

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Observation 7ac267db-060f-4923-8662-4df32315cbea · outbound

This paper cites Pointer Sentinel Mixture Models.

The Scaling Law for LoRA Base on Mutual Information Upper Bound Pointer Sentinel Mixture Models

Reference 2016

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source=pdf_text observed=2026-08-10T21:58:52.594103Z digest=sha256:88d4f31e980d51938a204ed4771269ba80142a501793bbebf9a19673c0e8a959

Observation cb1b10a5-34d8-4051-953e-aa65ff95121f · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

The Scaling Law for LoRA Base on Mutual Information Upper Bound Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 2018

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source=pdf_text observed=2026-08-10T21:58:52.538147Z digest=sha256:d18167956025172a72b3ae76a7986771198afe406ec358a0eca2d6f17ba34fda

Observation 68e264ce-2140-4cc2-80a9-6c425b73a9f6 · outbound

This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.

The Scaling Law for LoRA Base on Mutual Information Upper Bound HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 2019

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:58:52.613977Z digest=sha256:50f6129b7bf4ce5fd92913d1fb4c80ab41865342f23248afb972f96df04221ac

Observation 7d4ca7e0-040e-4c1c-aa51-337297d673ac · outbound

This paper cites Scaling Laws for Neural Language Models.

The Scaling Law for LoRA Base on Mutual Information Upper Bound Scaling Laws for Neural Language Models

Reference 2020

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Observation 73840786-7bef-4d21-a9d1-b3a7ab8ff8c2 · outbound

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

The Scaling Law for LoRA Base on Mutual Information Upper Bound LoRA: Low-Rank Adaptation of Large Language Models

Reference 2021

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Observation 3e716698-8a13-4248-8873-dd8a0e038cb2 · outbound

This paper cites GPT-4 Technical Report.

The Scaling Law for LoRA Base on Mutual Information Upper Bound GPT-4 Technical Report

Reference 2023

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Observation 6980b089-ed59-4f17-9c18-55bffee3eff8 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

The Scaling Law for LoRA Base on Mutual Information Upper Bound Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 2024

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Pith citing papers

No inbound Pith citation observations are available.