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Paper Citation Record · LEDGER

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing

As of 21 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 2 inbound Pith citation observations for arXiv:2507.21084.

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

pith.paper-citation-record.v1
2507.21084 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:27:58.622292Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T21:14:08.511356Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

48 of 48 outbound references displayed

  • verified exact4
  • verified fuzzy0
  • unresolved44
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation b03571c5-ddac-4998-9006-12ce5220aa69 · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.353276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.353276Z digest=sha256:c7bfcba93b72b22a09926fe5a4f4f9c11b367cb708bf90ecc5a5bdb09236b9ca

Observation 0cd459ac-38b1-442f-b641-e80440043b0f · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 2

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unresolved
no resolver link, observed 2026-08-15T19:27:58.359540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.359540Z digest=sha256:a0fa9f775db70d0bc9d03893f8945b1d53efc893ac51539bb9ec83e8d59ceb34

Observation fd094568-64c4-472b-8507-0298963ca994 · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:27:59.843130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.365953Z digest=sha256:774d1bd11acc8ec260927bb087317ee41b5b5ad613eafb43812dd7a7f4a0da9b

Observation 5f7d004d-df4b-4e4e-b2ae-1a9020a2c033 · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:27:59.825756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.372006Z digest=sha256:edd5cefd836a2400682e16ec9706a5a89715be4737390f32b219f54aa0c4e5d0

Observation ef603dff-49f7-4128-95a8-88ecd569afff · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:27:59.808128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.377946Z digest=sha256:a797323375563fb6e633eecdebffaa75770e309bae0e457d6c9fa862caf42d0d

Observation 7ea77796-7498-46c8-b5a1-f5cb1b85fcac · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:27:59.788501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.384623Z digest=sha256:225197565a74bbfa4f9a2038a37a6c5d153a81916d49ba49837315dd59d02a0d

Observation 66394463-0f33-40e6-af47-9e02e5818c68 · outbound

This paper cites BatchTopK Sparse Autoencoders.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing BatchTopK Sparse Autoencoders

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.390564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.390564Z digest=sha256:6d3795e2b012d9b62867abd756844c76182a3113a16de3e17fd0ba0452242f6e

Observation a72076ad-6db8-4615-8ecf-4a965e830e38 · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.395921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.395921Z digest=sha256:0ab9d4811ea04327f62b7f8bc44a82e92bf31ca3b48b0ae0407394def79a3a13

Observation a92a72f2-087f-4e6f-b035-3e9e44b2446b · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:27:59.748652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.401415Z digest=sha256:753cdf4e8b70962ba8bcd0e5e6f695cf32467aee5cf6f5b9074b8eebbb4aa348

Observation aaa5e8da-72c2-45b9-a071-474c33f64265 · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:27:59.730208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.407169Z digest=sha256:91b6ae996101f12307fef14bc6b033085bfa0565bed4d2bc770516363ed3fcca

Observation c91bcb09-0ab8-4742-b826-39c967946464 · outbound

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

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.412113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.412113Z digest=sha256:75b5c704f5903dd1b8cbc6c98a333c4fe75674bc6f666e79138bb51300516c39

Observation 4f35c893-7250-4861-ae2c-feffbf722ffb · outbound

This paper cites The Llama 3 Herd of Models.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing The Llama 3 Herd of Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.418645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.418645Z digest=sha256:fa46363f68958e47c383c93c9ed1c0353a60ca62f5eb0ef71b7555258306062b

Observation 3a5d3998-81cb-4156-b55c-9be7fd75a035 · outbound

This paper cites Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.423921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.423921Z digest=sha256:d21b3b687a201d6d9ee2981555cb2fe574f6e78e2aacb78312b06e68db4453d2

Observation 96cc91e4-bddf-4409-9522-f3d40e3a30e5 · outbound

This paper cites Dissecting Fine-Tuning Unlearning in Large Language Models.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Dissecting Fine-Tuning Unlearning in Large Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.429142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.429142Z digest=sha256:0175aabbacdf3d1a8674f3e4ed47796d11718a03b1201a3c175f4e3d31f3092d

Observation 94a64031-8273-416d-a7ab-6ced6f3c33d1 · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.435818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.435818Z digest=sha256:0c85c0ec5ab6960926d633ae6de05d8840bafab1fd039c04b9c005705d301c27

Observation f7998681-d363-4953-a5c0-af9becae64ee · outbound

This paper cites Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.440969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.440969Z digest=sha256:e6e00f64b7fc36dea444b1f2c86f34ca906329d866060192ee74ebf34216750d

Observation 7447eb9b-e3ee-4125-90e2-6a12b70b00b1 · outbound

This paper cites Sums of four polygonal numbers: precise formulas.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Sums of four polygonal numbers: precise formulas

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.446641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.446641Z digest=sha256:719413c84bd47dad1356884947b940ec965bb652c4be6316082d11ae8ffb24c6

Observation f2904b5e-4be9-47c0-a63d-3379e27851bc · outbound

This paper cites SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.451596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.451596Z digest=sha256:a79a36a9379d3e60c045413a203f120d80244f46c28315c20652766ce38d0fba

Observation bf72b1a3-e464-452b-89d9-47c62043611d · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.456614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.456614Z digest=sha256:c069b947a0648055c69208043970fc26e4c74eef8de8b4a52b8654ec3c29b45f

Observation d68ca24c-7242-44b2-8730-2e6a2c25ba2e · outbound

This paper cites The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.462055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.462055Z digest=sha256:3160b4e48b2a8aba72d481918beef21e3c24cb157e03b4d04c89b168c6d4b319

Observation deeb1838-a1e3-418c-8d89-5e8790146095 · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 21

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:27:59.694108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.466946Z digest=sha256:5bcc64ffcaea9e9ecdd86c85c30cfbb63274e275a8b40b4cd1c5af08483a648e

Observation 408cbe22-ac8c-4ee6-a8bb-30f9d58d2f46 · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.471657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.471657Z digest=sha256:11c68261c885a2a7ba30444b3dcbcb05402b154f83964d23ceb6d118b2c2bac9

Observation 28ec945a-e7fa-4972-8abc-085faa002938 · outbound

This paper cites Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-15T19:27:59.235577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.476203Z digest=sha256:90c13ef2e182d86dcfa9f61aa3f48a53d3e7078896fff32a08846f10f11c8bee

Observation c8dda7d9-ae90-49da-82a0-cbf1148265d8 · outbound

This paper cites Fine-tuning large language models for domain adaptation: Exploration of training strategies, scaling, model merging and synergistic capabilities.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Fine-tuning large language models for domain adaptation: Exploration of training strategies, scaling, model merging and synergistic capabilities

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.481370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.481370Z digest=sha256:79b23ad86bfda2dd2c5af162d554a1b9ce513536c362548428b4bc438fce89a2

Observation 06a6b41e-61e1-4970-9948-21a8e1b739eb · outbound

This paper cites Eight Methods to Evaluate Robust Unlearning in LLMs.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Eight Methods to Evaluate Robust Unlearning in LLMs

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.487509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.487509Z digest=sha256:bc4c0de341e6ff41cba0a8eedf7ca95d3b1fccd11573278355f1bc7b60307e70

Observation dc05f647-39f1-4a55-8792-824d887baff1 · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:27:59.660721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.493365Z digest=sha256:29e20d7091c75a1ec115bc7d5d411ed172496f98beaa1b6ba39d9a0a0751d57e

Observation 97ed5bea-8990-434c-a99d-34a34280de65 · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.498643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.498643Z digest=sha256:2d88d64a0b4c9e3308929fb214ccc2f1cc0a348501562e2e32f0c0fd23421528

Observation 1ea37918-a725-4a4a-bffc-d3db13faa455 · outbound

This paper cites An optimal control deep learning method to design artificial viscosities for Discontinuous Galerkin schemes.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing An optimal control deep learning method to design artificial viscosities for Discontinuous Galerkin schemes

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.504121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.504121Z digest=sha256:32e9c833ffb4df9e001cd612dfa525608307a5e37e92f273a6c16b19c058196f

Observation 4bc47687-e78f-40dd-8c93-755ecee7395d · outbound

This paper cites Automatically Interpreting Millions of Features in Large Language Models.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Automatically Interpreting Millions of Features in Large Language Models

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.510302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.510302Z digest=sha256:3c60e592138e5a335102a05c9702bde8d467af520125eca2f77d420b7246ae62

Observation 482702c0-7c49-4aca-8039-fe2da421a66d · outbound

This paper cites Criterion for ultra-fast bubble walls: the impact of hydrodynamic obstruction.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Criterion for ultra-fast bubble walls: the impact of hydrodynamic obstruction

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.516400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.516400Z digest=sha256:e6e707ed3b5554360963578e37882fbb0567a132353944fd280fde115d1ad2ec

Observation cb8b5def-cde5-48d9-befd-88b7ab6ece46 · outbound

This paper cites Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.521943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.521943Z digest=sha256:58c68f43bf44eaab3867e237b60fd2295634b6f9875db7e95b5c2465a126b157

Observation 1cb72d04-9639-465d-9bd7-20bd3a2bae93 · outbound

This paper cites Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.527178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.527178Z digest=sha256:e9dac8d64ae51a2670af29a510b6b060f4959d4c5314caaec318963957c9787c

Observation e9c49e96-915c-4cf4-8478-029fac4002f8 · outbound

This paper cites MUSE: Machine Unlearning Six-Way Evaluation for Language Models.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing MUSE: Machine Unlearning Six-Way Evaluation for Language Models

Reference 33

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unresolved
no resolver link, observed 2026-08-15T19:27:58.533567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.533567Z digest=sha256:e590cc82837acefddf21bee72561082c6b34ad7ea14006de9c5ff64690e207c8

Observation 0cf5f4f0-26f5-4019-af86-3fb95baed2ea · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 34

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unresolved
no resolver link, observed 2026-08-15T19:27:58.539174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.539174Z digest=sha256:33c31a6a34a6684d1aa223d77e52d80caf407a2bb5aeb38feacada796c268cb8

Observation 6d937444-0033-47bd-8e01-88ccba3e543b · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:27:59.632619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.543881Z digest=sha256:76ad56a9024f7e40e3fc75fca6e0825763e271ae17764ae84424e863cf558fc2

Observation de53d78a-af3e-4591-9bbf-86d8a170051f · outbound

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

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.549385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4f89e0ad-3867-4a20-b77a-1e2650fc596b · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.554799Z

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Unavailable: canonical work link unavailable.

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Observation 126e7a3b-f045-45f9-ab10-bf6e60ee0002 · outbound

This paper cites Emergent Abilities of Large Language Models.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Emergent Abilities of Large Language Models

Reference 38

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unresolved
no resolver link, observed 2026-08-15T19:27:58.560796Z

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Unavailable: canonical work link unavailable.

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Observation fe42743d-c9d3-407b-8329-ec84921a077d · outbound

This paper cites Marked boundary rigidity for surfaces of Anosov type.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Marked boundary rigidity for surfaces of Anosov type

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-08-15T19:27:58.787257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.566108Z digest=sha256:798d847cf788e3e10526eb57837e74314f1320f6bb47714d53d2f9e4710d9226

Observation c2b5620f-0bd3-4687-89d8-a82610d28cb1 · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 40

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unresolved
raw_fallback, observed 2026-08-15T19:27:59.604328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.573755Z digest=sha256:ec72120bf1e6b736149a08b7073167f226bf31d921fca79b815c02f609f5ec02

Observation f4f10265-84a5-4eab-b468-e4bd4ebbed69 · outbound

This paper cites an unresolved cited work.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Unresolved cited work

Reference 41

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unresolved
raw_fallback, observed 2026-08-15T19:27:59.586057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 7116b90b-2c85-46c6-8f67-f2a6cbdedffb · outbound

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Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Enhancing Workflow Security in Multi-Cloud Environments through Monitoring and Adaptation upon Cloud Service and Network Security Violations

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-08-15T19:27:58.759545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 4f1dfc6f-cc09-46a5-a3bb-8f5eb7733153 · outbound

This paper cites Towards Comprehensive Post Safety Alignment of Large Language Models via Safety Patching.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Towards Comprehensive Post Safety Alignment of Large Language Models via Safety Patching

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.589843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.589843Z digest=sha256:a38779be70edf73cb89f448c4e77a907ab3d9eda5ec46d2d50c299d03e9f0b49

Observation 7b2a693d-e6e0-4c9c-a279-011eb370c1d7 · outbound

This paper cites LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.596613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.596613Z digest=sha256:818a76e59754339ae920a52114642836247266293991a16d2d82ee7cd5ea9ffb

Observation 2b674e2f-163b-430b-bac1-1b61f4e599df · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-15T19:27:58.604287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.604287Z digest=sha256:479deaf6dff582c2316014cb949e35d669443e70a3b5c93600604dba2c7ca5bb

Observation c9f3573e-ce04-4213-8dd5-6372ebb77e72 · outbound

This paper cites AIIR-MIX: Multi-Agent Reinforcement Learning Meets Attention Individual Intrinsic Reward Mixing Network.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing AIIR-MIX: Multi-Agent Reinforcement Learning Meets Attention Individual Intrinsic Reward Mixing Network

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-08-15T19:27:58.675776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation bdb5a2fc-781a-400b-a132-f8697de84041 · outbound

This paper cites online" 'onlinestring :=.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing online" 'onlinestring :=

Reference 47

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unresolved
no resolver link, observed 2026-08-15T19:27:58.615677Z

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Unavailable: canonical work link unavailable.

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Observation 76b41e00-cd8d-47fe-97e8-c7bf7cb4bd9a · outbound

This paper cites write newline.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing write newline

Reference 48

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unresolved
no resolver link, observed 2026-08-15T19:27:58.622292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:27:58.622292Z digest=sha256:e4038fe3d5cf512b71935baf5b7804dbc0148872f44774b184a0fb8b58da0ca6

Pith citing papers

Observation 3e797dea-8b52-46ce-8657-942452ac7369 · inbound

Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models cites this paper.

Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing

Reference 149

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verified exact
arxiv_id, observed 2026-05-16T12:40:54.414854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation fba70547-72d3-4315-bcfc-69b48146fbed · inbound

Mechanism-Guided Selective Unlearning for RLVR-Induced Reasoning cites this paper.

Mechanism-Guided Selective Unlearning for RLVR-Induced Reasoning Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing

Reference 6

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arxiv_id, observed 2026-07-04T00:29:15.418144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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