Paper Citation Record · LEDGER

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs?

As of 13 August 2026, this Paper Citation Record lists 73 of 73 outbound references and 1 inbound Pith citation observation for arXiv:2411.18797.

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

pith.paper-citation-record.v1
2411.18797 v2

Coverage vector

measured 73 of 73 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:57:23.013714Z

measured 74 of 74 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T13:54:40.579092Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T13:54:40.666674Z

Reference resolution

73 of 73 outbound references displayed

verified exact0
verified fuzzy0
unresolved73
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 15b92369-5cce-4d0d-8900-070ac5d3e8c0 · outbound

This paper cites online" 'onlinestring :=.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? online" 'onlinestring :=

Reference 1

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Observation dfb5ca2d-0141-4179-910f-8f9fa64d8b01 · outbound

This paper cites write newline.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? write newline

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T10:57:22.706937Z

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Observation f3f920e6-7596-4b90-bfd3-4ab66959ae0b · outbound

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

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 3

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Observation 1502b42e-e933-48b6-b857-f0a7d110769f · outbound

This paper cites To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T10:57:22.716641Z

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Observation eeeced10-2696-4b10-980e-7b130c814355 · outbound

This paper cites an unresolved cited work.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T10:57:22.721338Z

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Observation dbfe4973-7730-4401-bbfb-55010ee4aaed · outbound

This paper cites Prediction Is All MoE Needs: Expert Load Distribution Goes from Fluctuating to Stabilizing.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Prediction Is All MoE Needs: Expert Load Distribution Goes from Fluctuating to Stabilizing

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T10:57:22.725505Z

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Observation 51b69988-6035-46c2-a37b-ee49b85d820d · outbound

This paper cites DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T10:57:22.730008Z

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Unavailable: canonical work link unavailable.

Observation 57db2527-c9f5-4fff-99ea-2cb83b6ef981 · outbound

This paper cites StableMoE: Stable Routing Strategy for Mixture of Experts.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? StableMoE: Stable Routing Strategy for Mixture of Experts

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T10:57:22.734391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0485aedf-9da6-400d-98d5-ce89e3a21d4f · outbound

This paper cites an unresolved cited work.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

Reference 9

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Source-reported events for the cited work

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Observation e94127a3-c1f4-431a-96b4-c3ce0b429893 · outbound

This paper cites The Llama 3 Herd of Models.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? The Llama 3 Herd of Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T10:57:22.743542Z

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Observation 4f17ce8e-fd9a-4a5f-941b-c4ee817a8e84 · outbound

This paper cites Who's Harry Potter? Approximate Unlearning in LLMs.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Who's Harry Potter? Approximate Unlearning in LLMs

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T10:57:22.747764Z

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Observation cd6cc208-bb50-41b7-bae0-76c7a395743e · outbound

This paper cites an unresolved cited work.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

Reference 12

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This paper cites an unresolved cited work.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

Reference 13

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Observation 868e6910-f857-4240-86d6-839cfbcb3306 · outbound

This paper cites an unresolved cited work.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

Reference 14

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Observation 7168f1c1-bc32-4127-841b-ee8617e6e62c · outbound

This paper cites Measuring Massive Multitask Language Understanding.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Measuring Massive Multitask Language Understanding

Reference 15

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Observation 66256271-2e14-421c-a264-7855b5a9b408 · outbound

This paper cites An Overview of Catastrophic AI Risks.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? An Overview of Catastrophic AI Risks

Reference 16

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Observation 1c54db95-6764-44aa-bbe6-b55ef123c740 · outbound

This paper cites ORPO: Monolithic Preference Optimization without Reference Model.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? ORPO: Monolithic Preference Optimization without Reference Model

Reference 17

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Unavailable: canonical work link unavailable.

Observation fd2bde0f-a613-47b9-8742-cdc4eff4ff75 · outbound

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

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? LoRA: Low-Rank Adaptation of Large Language Models

Reference 18

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Observation 09c392ca-f8e7-410e-96cc-7734440f3c92 · outbound

This paper cites an unresolved cited work.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

Reference 19

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Observation 99aaf1ca-1981-47cb-bcda-58869d736fde · outbound

This paper cites an unresolved cited work.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

Reference 20

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Observation b1c85b37-119b-4e4e-878e-02c346a10f0d · outbound

This paper cites Editing Models with Task Arithmetic.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Editing Models with Task Arithmetic

Reference 21

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Observation acb9eb0d-1e5c-4db0-8778-a26398335301 · outbound

This paper cites Knowledge Sanitization of Large Language Models.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Knowledge Sanitization of Large Language Models

Reference 22

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Observation 6734327f-0ee6-4fdc-924e-c298bdcb2ee7 · outbound

This paper cites Knowledge Unlearning for Mitigating Privacy Risks in Language Models.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Knowledge Unlearning for Mitigating Privacy Risks in Language Models

Reference 23

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Observation 1aee6993-1ce1-4400-a885-220489536c0f · outbound

This paper cites WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models

Reference 24

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Observation 36e0bda4-e0ef-4b62-829e-337f39a1233b · outbound

This paper cites SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning

Reference 25

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Observation e3e1e154-9316-46bd-af92-3c504c616cef · outbound

This paper cites Mixtral of Experts.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Mixtral of Experts

Reference 26

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Observation 08ac2b93-4d2d-43a9-b897-1b2d75bd93af · outbound

This paper cites RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models

Reference 27

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Observation 7209d567-bf4f-4a24-972e-8a37ba7ce326 · outbound

This paper cites Scalable and Efficient MoE Training for Multitask Multilingual Models.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Scalable and Efficient MoE Training for Multitask Multilingual Models

Reference 28

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Observation 1a587fa1-a5de-43f8-9f13-99459a25195d · outbound

This paper cites Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints

Reference 29

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Observation ff2296b6-96d4-4ec3-ad3a-61b1076f06d9 · outbound

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Privacy Adhering Machine Un-learning in NLP

Reference 30

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Reference 31

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Observation 6d44fc03-48fb-49eb-a392-11a6ff80d1c9 · outbound

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

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning

Reference 32

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Jamba: A Hybrid Transformer-Mamba Language Model

Reference 33

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 34

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

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Observation 4fe51d17-4876-4f4f-ae85-ea5b4a34ef22 · outbound

This paper cites Large Language Model Unlearning via Embedding-Corrupted Prompts.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Large Language Model Unlearning via Embedding-Corrupted Prompts

Reference 36

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Observation 0d8ec195-df60-4b9e-a301-cf15269430b4 · outbound

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Rethinking Machine Unlearning for Large Language Models

Reference 37

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This paper cites Towards Safer Large Language Models through Machine Unlearning.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Towards Safer Large Language Models through Machine Unlearning

Reference 38

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? TOFU: A Task of Fictitious Unlearning for LLMs

Reference 40

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

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Observation 5452f49f-9697-4fdb-acaa-b6172e881ae4 · outbound

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? In-Context Unlearning: Language Models as Few Shot Unlearners

Reference 43

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? On the Adversarial Robustness of Mixture of Experts

Reference 44

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 46

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? ModuleFormer: Modularity Emerges from Mixture-of-Experts

Reference 47

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? MUSE: Machine Unlearning Six-Way Evaluation for Language Models

Reference 48

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? TrustLLM: Trustworthiness in Large Language Models

Reference 49

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

Reference 50

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Guardrail Baselines for Unlearning in LLMs

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 52

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Large Scale Knowledge Washing

Reference 53

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Let the Expert Stick to His Last: Expert-Specialized Fine-Tuning for Sparse Architectural Large Language Models

Reference 54

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications

Reference 55

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

Reference 56

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? DEPN: Detecting and Editing Privacy Neurons in Pretrained Language Models

Reference 57

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

Reference 58

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This paper cites Qwen2 Technical Report.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Qwen2 Technical Report

Reference 59

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Machine Unlearning of Pre-trained Large Language Models

Reference 60

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Large Language Model Unlearning

Reference 61

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

Reference 62

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Forget-Me-Not: Learning to Forget in Text-to-Image Diffusion Models

Reference 63

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning

Reference 64

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

Reference 65

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Observation 68111964-a8f7-49a4-b076-84d6d2679909 · outbound

This paper cites MoEfication: Transformer Feed-forward Layers are Mixtures of Experts.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? MoEfication: Transformer Feed-forward Layers are Mixtures of Experts

Reference 66

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Observation cf1dd255-a3dc-49e9-b28c-5f67df367aaa · outbound

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-12T10:57:23.799577Z

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Observation 00943a6d-bdee-453e-882e-659efbf19cdd · outbound

This paper cites LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-training.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-training

Reference 68

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Unavailable: canonical work link unavailable.

Observation 277afdb5-fd6f-4f71-9a36-0c0953a6c8cb · outbound

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? ST-MoE: Designing Stable and Transferable Sparse Expert Models

Reference 70

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Unavailable: canonical work link unavailable.

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-12T10:57:23.000906Z

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Unavailable: canonical work link unavailable.

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? @esa (Ref

Reference 72

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4da59a9-0209-4663-9825-3dbaeb679bd6 · outbound

This paper cites an unresolved cited work.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? Unresolved cited work

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-12T10:57:23.009433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 441b6dd3-f05c-4558-a5c6-094828d67f68 · outbound

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SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? for fill-in-the-blank tasks and ``Please briefly answer the following question. Question:

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-12T10:57:23.013714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 174ba3f9-533c-4ace-9d5b-8665b4c96ff8 · inbound

A Survey on Generative Model Unlearning: Fundamentals, Taxonomy, Evaluation, and Future Direction cites this paper.

A Survey on Generative Model Unlearning: Fundamentals, Taxonomy, Evaluation, and Future Direction SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs?

Reference 270

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