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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 18 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 2026-08-18T06:34:40.430872+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=sha256:3f3ca07383ee57a06a8ae52e26aefc9cbb4d085b66ced98581a094867f6b833a

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

Resolution
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:acd9619c5e8dc12eb0ca77290985b473a381e283088995d9be7bfd2795d0bc72

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.365953Z digest=sha256:3a12f69ddba3c23f35caa72ec3743e9daa879068e4ba9ea78d2acfc85a822aff

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.372006Z digest=sha256:cc719e4a16b6d82c87bf90768639723735c4060d6eeee72c384ce070bd29fe28

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.377946Z digest=sha256:c0171156372009d9ab84c75eac6d0fe2c677ce5baef74742006c25a983b087d3

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.384623Z digest=sha256:66e2c1984d380f3d498232ad4c2527d6a4afa1e6fe0cb7aed5d8ace01bb18710

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=sha256:755a0354eda6879e7ec427e73b172a50d145e96bfb0bb358169854e80a2e1c76

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:a8fc88af52d66a6c0e3160040b80809e170000045ed513bc042fe38946f3b428

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.401415Z digest=sha256:ffb3b69b66258fee2750d2cbf4b1af9632955f52269e28a23ed864dbfa5d66c6

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.407169Z digest=sha256:89a2bed46403c7c0673573db32fde2549bedd012e7eb4ee7fd715c0cd09cea13

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=sha256:5d42e125914e038c80b182cf938b8ffa6ba03284d4a5cc10033e033fd39bca52

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=sha256:9555ea4b564e09cf42f3ae44651a57f28aa49b86ebfe6757118882971e049192

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=sha256:8efcb88f2569f27b4edaf76029890e9404f0a376a0c31eb15b93473b2d13dd6c

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:d630e85c227e6eac230c8d3517dbd8e4c93e5b5cd63cd253868f3652395dcdd2

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:d278e1c5f645c063c2e74302cad421acbfd22b7460a0b633660c47cf69d7f1ed

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=sha256:540c28cf57b47ab7985ee43774585560911ddf3a64561e326056271d5660be30

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:f8e9d4ef30fb7642b50150e9beb10930711b581d6e648b68880fcd095f4d1654

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=sha256:9a388e59314b4b2157d14fb434074c34600c68a9b98646d1bd9203e9ffe9c950

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:e7da696ff7c337270f2c2ffbbdc8bbd449f2c3bc53c60b9c2f4d6764151c4989

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=sha256:294ae89fcdbc2cb79ecb3794fd9d3c73fc118f872727b5bae6a33819c75cf59c

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.466946Z digest=sha256:3b8d0a9c1fb83e509aa4878eb1e28a72ec89d6be533c92e213f8c95b2fdb006c

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:d7ebfafdd4693acac1af25d8f6a80d0440c1eab35ffdbd3025e27368a27c24b8

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.476203Z digest=sha256:89b676d27fe69bd7f761379e2377660f76cde251c283ebc4629c29336bfa57a7

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:f232957e738c864622f9eb29d4f92d369e40df3eb5077e026c57e49d22231703

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=sha256:3b41b17527a06c616bc618616f9e5afee040629a6daca30d2de1855a464e2f55

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.493365Z digest=sha256:3bef23b88458a16ca72fb4de11a53d3a65205db6f1b92f909ed63995f7fb90a2

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=sha256:56afd168400cf2b3b8a79b5d24a7695873e129d6861167d750278dc93a6cfa03

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:c387d6d13eff5fa16f30ed4d2ade9e9b787ac98ab15a723208db6ba0f17ba540

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=sha256:4faa8cf95792e2a28db6079493c20e5b2578c5e2f9898348b16d52ec691ba300

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:d1aa604bd6785e30b739c75970120dbc0fb09717c6782400dcd69a291e3a9e99

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=sha256:5c17df9ee1ecd056634a40f02d2d221c015137b782fef7d1dd313a2c55ec2727

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:f64ba0dd010d3180c0acf2797ad30ac66ebce2e068dd064e43fd23aec7c09e3c

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

Resolution
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:a343556d2c6b5268a61929f8439d9c405a0dabfb0fb46dcf3a72e017660c87f4

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

Resolution
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=sha256:2d81bc9ffac6f8c8326f8e84720dec313abdf17d8916c2f1f9d167708e946fa4

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T19:27:58.543881Z digest=sha256:6e101d9861f844335f40c9e93ed6596e8498f200dc4f26e84e4bf5ef30375d16

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

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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

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

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

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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

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verified exact
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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.

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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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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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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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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.

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

This paper cites Enhancing Workflow Security in Multi-Cloud Environments through Monitoring and Adaptation upon Cloud Service and Network Security Violations.

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

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verified exact
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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.

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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

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Unavailable: canonical work link unavailable.

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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

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

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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

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

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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

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verified exact
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+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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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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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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arxiv_id, observed 2026-05-16T12:40:54.414854Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+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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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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