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Paper Citation Record · LEDGER

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization

As of 18 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 7 inbound Pith citation observations for arXiv:2501.13669.

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

pith.paper-citation-record.v1
2501.13669 v2

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:48:09.232556Z

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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:16:41.545919Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:48:39.897925Z

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 b1fdb145-edf6-4151-9ec7-104192ad5a75 · outbound

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

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization LoRA: Low-Rank Adaptation of Large Language Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-10T15:48:09.198507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:48:09.198507Z digest=sha256:37518cebd78bc6ff2b9d7078940a11d240275a98734cdb9c6e19f98c69d26268

Observation e70865d5-88c7-42d0-89b8-f1855a627193 · outbound

This paper cites A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA.

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-10T15:48:09.202117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:48:09.202117Z digest=sha256:caceaaae676bc96cfc47aca8e53227b2032305ea9a89f2abd49fed6f88a79b98

Observation 4394c8d1-fdcc-4b2b-ba5c-f84eda8a976f · outbound

This paper cites and Joty, S.

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization and Joty, S

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:48:09.367007Z

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.

source=pdf_text observed=2026-08-10T15:48:09.212647Z digest=sha256:df2f552c6ead6c8371aa0049b50831153d7b6cb2973ec648edaa065129ddb317

Observation 99ed3f3a-10e2-4439-a35a-8b6e26d07237 · outbound

This paper cites Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning.

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T15:48:09.216082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:48:09.216082Z digest=sha256:bc09fd0b3bd54be8a956b7866426ded948498c691f483f1ca852629b0c19fa8e

Observation b15f408f-1404-40a2-b615-3684ce2875b3 · outbound

This paper cites and Feng, Y.

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization and Feng, Y

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:48:09.356655Z

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.

source=pdf_text observed=2026-08-10T15:48:09.219517Z digest=sha256:4810fafacebaf2ccdd4e734f2f94cc13eb0069e1802d8fce9bfc4b3bcb9c84af

Observation 6e74f434-3076-4636-bd6c-895693d6f52c · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization LLaMA: Open and Efficient Foundation Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T15:48:09.222872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:48:09.222872Z digest=sha256:0f8e025fcf1f320c745683d7518bdca3ba3fd16183f834a04b34601cebc433a5

Observation c85b423b-3223-46a9-8f85-c00ffa391539 · outbound

This paper cites Learning to prompt for continual learning.

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization Learning to prompt for continual learning

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:48:09.346478Z

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.

source=pdf_text observed=2026-08-10T15:48:09.226378Z digest=sha256:c0d9f93df9bd979164349e6daf04376f2a5b0ca4e1aa18ba2871ef8b3c9821d8

Observation 35aae84b-805b-4103-8dd8-8057454f0445 · outbound

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

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization LoRA-Pro: Are Low-Rank Adapters Properly Optimized?

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T15:48:09.229492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:48:09.229492Z digest=sha256:586846c69c415ca5bf8d16f527fc1125c72fcb79e445b4b7a8ab731b3076a604

Observation 25fb14e9-3569-468e-bc09-9c9c4cdf5d2b · outbound

This paper cites Crowdsourcing Multiple Choice Science Questions.

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization Crowdsourcing Multiple Choice Science Questions

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-10T15:48:09.232556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:48:09.232556Z digest=sha256:c158ede695717c0dfc25b3212bc75487ae593438c3d85501b37ff0f391dd751d

Observation 26528d6c-6f83-4808-a67a-43be8481a683 · outbound

This paper cites Continual learning of neural machine translation within low forgetting risk regions.

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization Continual learning of neural machine translation within low forgetting risk regions

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:48:09.377244Z

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.

source=pdf_text observed=2026-08-10T15:48:09.194858Z digest=sha256:1984ec542d111f4be22e98fff767a54f8c95c784621039d1dc90720ed754e999

Observation ad5a4959-e3c8-4ce2-9288-e9c6209d88a7 · outbound

This paper cites Full Parameter Fine-tuning for Large Language Models with Limited Resources.

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization Full Parameter Fine-tuning for Large Language Models with Limited Resources

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-10T15:48:09.205619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:48:09.205619Z digest=sha256:6bec05004d831e7456110d009eab43ca845d929360b439d88f70a68b3d8f7444

Observation ba665177-3c62-4cbb-99c0-f5e461067757 · outbound

This paper cites The Llama 3 Herd of Models.

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization The Llama 3 Herd of Models

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-10T15:48:09.187110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:48:09.187110Z digest=sha256:36cdb7421076386a263309b1ab81cb3d1cb7e95cbe53cfce06f170caf78a85c2

Observation 1fa7aade-254d-465b-b2d4-0c1759052836 · outbound

This paper cites GPT-4 Technical Report.

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization GPT-4 Technical Report

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-10T15:48:09.209187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:48:09.209187Z digest=sha256:5c353cb59dad8dd24f3d2aeaee59efe5f4cda743d2a5e6776906bc906fa49ef9

Observation 10362ff7-80da-4dff-abf8-c47cf79f888c · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-10T15:48:09.191348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:48:09.191348Z digest=sha256:8a46213852f989388fed6b705a2320e09fb9878f1cba54e4be2a8e8528ae5cba

Pith citing papers

Observation c2a425a5-f885-41d3-9b9a-315bb942bb31 · inbound

Memorization and Knowledge Injection in Gated LLMs cites this paper.

Memorization and Knowledge Injection in Gated LLMs How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-16T05:16:41.545919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T05:16:41.545919Z digest=sha256:a97813906b98953eda38781a3f7d612e35d3bcaa26c4a4fb8ff32caf94c40fe4

Observation b9596d81-af4b-4be6-b67f-4a788950bc15 · inbound

Time Series Foundation Models for Multivariate Financial Time Series Forecasting cites this paper.

Time Series Foundation Models for Multivariate Financial Time Series Forecasting How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-06T18:49:25.873848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:49:25.873848Z digest=sha256:8a6024ea67d2ea96de4fa80b46f8138a0639418db529c8a5e17f3f0eac937ea5

Observation 09cbdec8-e815-49f7-912e-cedb07a11b06 · inbound

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval cites this paper.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-04T23:23:41.525376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:23:41.525376Z digest=sha256:00223f616a36a29d4c67caaa97bc0ba0ff353160bfaea89d3b71b8eba63099ce

Observation 319b1bc1-b991-40c3-bae2-da6c529c6a94 · inbound

MedXIAOHE: A Comprehensive Recipe for Building Medical MLLMs cites this paper.

MedXIAOHE: A Comprehensive Recipe for Building Medical MLLMs How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization

Reference 56

Resolution
verified exact
arxiv_id, observed 2026-05-15T22:56:50.460181Z

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.

source=pdf_text observed=2026-05-15T22:52:30.992054Z digest=sha256:c6e06eaaae4e6ff2a70c2755f6d51a6cd8afdb5571ee75bef15870028b7c3fed

Observation 77785bd3-0de9-4bd4-a6c8-5aac75750fa7 · inbound

One Algorithm, Two Goals: Dual Scoring for Parameter and Data Selection in LLM Fine-Tuning cites this paper.

One Algorithm, Two Goals: Dual Scoring for Parameter and Data Selection in LLM Fine-Tuning How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:51:07.467799Z

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.

source=pdf_text observed=2026-05-08T13:40:50.908566Z digest=sha256:2097c7119b9093531ce80ffb2e0436eced12a4ba25ebad61145851c182dca6ff

Observation 8024744e-d69d-4b3f-8437-27cc47238bdd · inbound

Fine-Tuning Without Forgetting via Loss-Adaptive Learning Rates cites this paper.

Fine-Tuning Without Forgetting via Loss-Adaptive Learning Rates How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-05-20T07:18:07.037798Z

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.

source=pdf_text observed=2026-05-20T07:14:59.396900Z digest=sha256:7ec8c71dbb8bab7dc50eb9c131a3db0b37816962d3ccca87a0b1d043b30e4798

Observation c68c8346-c38b-4a80-bf4d-2840eaff01f1 · inbound

LLM Evolution as an Industry-Scale Ecosystem: A Lifecycle Perspective on Continual Learning cites this paper.

LLM Evolution as an Industry-Scale Ecosystem: A Lifecycle Perspective on Continual Learning How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization

Reference 90

Resolution
verified exact
arxiv_id, observed 2026-07-03T16:48:39.899620Z

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.

source=pdf_text observed=2026-06-27T05:02:18.347642Z digest=sha256:5c7605f17b0bb1b2cd025c2338694e28f3f890d4e6d6a003c57faa61643c423c