Paper Citation Record · LEDGER

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption

As of 21 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 1 inbound Pith citation observation for arXiv:2506.05242.

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

pith.paper-citation-record.v1
2506.05242 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:30:14.023076Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T04:25:19.998499Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T06:16:28.698911Z

Reference resolution

55 of 55 outbound references displayed

verified exact2
verified fuzzy32
unresolved20
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3718e690-801e-4175-a2fa-85a1e421d8d7 · outbound

This paper cites Toward expert-level medical question answering with large language models,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Toward expert-level medical question answering with large language models,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.725928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce68a85b-aedd-42f6-8e20-a9c0d4535db6 · outbound

This paper cites LLMs in Mobile Apps: Practices, Challenges, and Opportunities.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption LLMs in Mobile Apps: Practices, Challenges, and Opportunities

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:30:14.550029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fd355c66-7841-4502-a5a9-cb08f72957fe · outbound

This paper cites Building AI Security: The On-Premise Advan- tage.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Building AI Security: The On-Premise Advan- tage

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.083277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a24733dd-36fc-4596-a7dd-afc089c1d0de · outbound

This paper cites Beyond clouds: Locally runnable llms as a secure solution for ai applications,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Beyond clouds: Locally runnable llms as a secure solution for ai applications,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.066976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d318c1ef-e825-47d0-a4bd-8785c73dc030 · outbound

This paper cites Ai-generated research paper fabrication and plagiarism in the scientific community,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Ai-generated research paper fabrication and plagiarism in the scientific community,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.050534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2088af7b-dc1a-4d26-a586-a2cd138ffb73 · outbound

This paper cites How cybercriminals are using chatgpt to build hacking tools and ransomware,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption How cybercriminals are using chatgpt to build hacking tools and ransomware,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.033680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7ef628b2-7e5e-40bb-8f2e-765c5b3a1eb2 · outbound

This paper cites Code Llama: Open Foundation Models for Code.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Code Llama: Open Foundation Models for Code

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.773900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07106c95-3c07-41e0-80f2-945a19cb6bc1 · outbound

This paper cites Distill gpt-2 story generator,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Distill gpt-2 story generator,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.014089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bb0e2860-439d-4c92-b2ee-4ccc17c8bb34 · outbound

This paper cites Training language models to follow instructions with human feedback.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Training language models to follow instructions with human feedback

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.783557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f6ba961-6626-4eac-ab24-6aa26147bca8 · outbound

This paper cites Training language models to follow instructions with human feedback,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Training language models to follow instructions with human feedback,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.994370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7068ceef-d48e-4e25-803e-4df318822326 · outbound

This paper cites Deep reinforcement learning from human preferences,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Deep reinforcement learning from human preferences,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.979553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9d11f7de-3bf4-4be4-b6f1-c1d05d21c881 · outbound

This paper cites Fast Machine Unlearning Without Retraining Through Selective Synaptic Dampening.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Fast Machine Unlearning Without Retraining Through Selective Synaptic Dampening

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.798955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 372dc9fd-588e-41c9-8a9d-b77acbdfcaf3 · outbound

This paper cites Dissecting Language Models: Machine Unlearning via Selective Pruning.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Dissecting Language Models: Machine Unlearning via Selective Pruning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.804320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7e479e4-47f4-47f6-9e77-9487e7fdc55b · outbound

This paper cites Machine unlearning,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Machine unlearning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.964185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e1ae82ce-eb74-46d2-8372-901a76dfd44c · outbound

This paper cites Watermarking Large Language Models and the Generated Content: Opportunities and Challenges.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Watermarking Large Language Models and the Generated Content: Opportunities and Challenges

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.815362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdcda08a-356b-4496-9ab1-61e08432b8e4 · outbound

This paper cites Watermarking Techniques for Large Language Models: A Survey.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Watermarking Techniques for Large Language Models: A Survey

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.820538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40ae7243-bf1d-47b4-9afa-e382afbd94ea · outbound

This paper cites Mark Your LLM: Detecting the Misuse of Open-Source Large Language Models via Watermarking.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Mark Your LLM: Detecting the Misuse of Open-Source Large Language Models via Watermarking

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.826133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d797321-22bd-4eec-a428-08062cbf0b38 · outbound

This paper cites Periodic watermarking for copyright protection of large language models in cloud computing security,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Periodic watermarking for copyright protection of large language models in cloud computing security,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.949494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 17fec9c0-e0c6-43f7-8eea-fcfb6f2e8b88 · outbound

This paper cites Defending against alignment- breaking attacks via robustly aligned LLM,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Defending against alignment- breaking attacks via robustly aligned LLM,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.933862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 50c097e5-2eac-4338-8d17-159d2115b634 · outbound

This paper cites GradSafe: Detecting jailbreak prompts for LLMs via safety-critical gradient analysis,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption GradSafe: Detecting jailbreak prompts for LLMs via safety-critical gradient analysis,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.918369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1d6a4443-3616-48ba-8499-01ac72c0f22c · outbound

This paper cites Defending large language models against jailbreaking attacks through goal prioritization,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Defending large language models against jailbreaking attacks through goal prioritization,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.901812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 12b59fed-3d2f-4120-aa38-3d248f580665 · outbound

This paper cites Choose your neuron: Incorporating domain knowledge through neuron-importance,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Choose your neuron: Incorporating domain knowledge through neuron-importance,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.886541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6abcd5e6-e8a4-4af5-9a68-85d466d0ff6e · outbound

This paper cites Understanding Neural Networks and Individual Neuron Importance via Information-Ordered Cumulative Ablation.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Understanding Neural Networks and Individual Neuron Importance via Information-Ordered Cumulative Ablation

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:30:14.420674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 434afef5-fc51-4c04-a3f1-ba16e0418e55 · outbound

This paper cites Does large language model contain task-specific neurons?.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Does large language model contain task-specific neurons?

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.869479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 55d329ed-6840-4960-88c7-c38b749eb4f5 · outbound

This paper cites Darknetz: towards model privacy at the edge using trusted execution environments,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Darknetz: towards model privacy at the edge using trusted execution environments,

Reference 25

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T10:30:14.396543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9d508c49-b8a0-469f-9943-b3bb4b138548 · outbound

This paper cites (2024) Host llm in gpu tee.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption (2024) Host llm in gpu tee

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.851815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 16bb8db4-c0a3-4990-a21b-68723e1377f8 · outbound

This paper cites Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.876755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60949abe-39cc-49ac-8d9b-4268e19d944b · outbound

This paper cites Multitask learning,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Multitask learning,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.836555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 929075ea-cc74-435c-9c8b-d15c50849d65 · outbound

This paper cites Enron email dataset,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Enron email dataset,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.820969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e8b64dea-f0b7-464c-bc2c-6b945885c08e · outbound

This paper cites Jailbroken: how does llm safety training fail?.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Jailbroken: how does llm safety training fail?

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.804585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 634c8eeb-175c-47ff-9cc7-eec3d43e0713 · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.896685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e2e9356-96a9-43a0-b49e-d3ba516843ae · outbound

This paper cites Surrogateprompt: Bypassing the safety filter of text-to-image models via substitution,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Surrogateprompt: Bypassing the safety filter of text-to-image models via substitution,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.902155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6dd11fa6-cf36-4988-a97b-05bf35229274 · outbound

This paper cites DAWN: Dynamic Adversarial Watermarking of Neural Networks.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption DAWN: Dynamic Adversarial Watermarking of Neural Networks

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.907273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b64b727b-604a-41c8-bf76-3c12e75dbe5d · outbound

This paper cites DeepSigns: A Generic Watermarking Framework for IP Protection of Deep Learning Models.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption DeepSigns: A Generic Watermarking Framework for IP Protection of Deep Learning Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.912478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00840d6f-f5da-4916-bc6e-fc29c3b16b10 · outbound

This paper cites BlackMarks: Blackbox Multibit Watermarking for Deep Neural Networks.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption BlackMarks: Blackbox Multibit Watermarking for Deep Neural Networks

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.917867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ead85a25-af06-4ac4-aae8-9e995da9ffa9 · outbound

This paper cites Adversarial watermarking transformer: Towards tracing text provenance with data hiding,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Adversarial watermarking transformer: Towards tracing text provenance with data hiding,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.787725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9bb85b59-ffbb-46ab-84c2-564b76cb9f69 · outbound

This paper cites Do not write that jailbreak paper,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Do not write that jailbreak paper,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.772060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 14ae4ca5-9d8c-4e2e-b520-78bb5eb45a98 · outbound

This paper cites Ciphertext-policy attribute- based encryption,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Ciphertext-policy attribute- based encryption,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.755240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7e32de95-88ac-4aaf-907c-0dbb0214c976 · outbound

This paper cites Fast, compact, and expressive attribute-based encryption,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Fast, compact, and expressive attribute-based encryption,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.738462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ef383207-c5d7-4759-8470-d46e9c494428 · outbound

This paper cites Advanced encryption standard,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Advanced encryption standard,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.722631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 03da96fb-8b10-4dea-ac0e-509cffc16c4d · outbound

This paper cites Report on the development of the advanced encryption standard (aes),.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Report on the development of the advanced encryption standard (aes),

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.707363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c304c723-4ff8-4df0-84ad-1a424a524e26 · outbound

This paper cites Scaling up membership inference: When and how attacks succeed on large language models,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Scaling up membership inference: When and how attacks succeed on large language models,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.690609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5370d93d-cc80-44a7-9c49-8efceeeaf31a · outbound

This paper cites Analyzing leakage of personally identifiable information in language models,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Analyzing leakage of personally identifiable information in language models,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.673701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0f495aa6-fd97-4e5e-98c8-eba951ad7fee · outbound

This paper cites Movement pruning: adaptive sparsity by fine-tuning,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Movement pruning: adaptive sparsity by fine-tuning,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.656540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b3ecbf80-c8d6-4a80-ace0-6c7aafa3e068 · outbound

This paper cites Michel, O.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Michel, O

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.639045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 326e2e36-5433-4060-a42b-15c08159e067 · outbound

This paper cites Train large, then compress: rethinking model size for ef- ficient training and inference of transformers,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Train large, then compress: rethinking model size for ef- ficient training and inference of transformers,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.621530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d18f41a3-6b08-446f-8551-f07cefbc5e26 · outbound

This paper cites Charm: A framework for rapidly prototyping cryptosystems,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Charm: A framework for rapidly prototyping cryptosystems,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.605791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 782994ef-eb39-48e8-80e9-03b5c0b34a2e · outbound

This paper cites Crypto: Simple symmet- ric gpg file encryption and decryption,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Crypto: Simple symmet- ric gpg file encryption and decryption,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.590175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d66f4ded-f4bc-4e88-b3d9-3e787a847cfd · outbound

This paper cites Cython: C-extensions for python,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Cython: C-extensions for python,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.574771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 328f47a9-323c-445e-ade6-089522282683 · outbound

This paper cites Opt: Open pre-trained transformer language models,.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Opt: Open pre-trained transformer language models,

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:14.001426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d88729a2-790e-4d97-b82f-89d193cf8ca7 · outbound

This paper cites Galactica: A Large Language Model for Science.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Galactica: A Large Language Model for Science

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:14.012873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b02a224-ac02-416c-bce7-997f7fef6b3b · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Gemma 2: Improving Open Language Models at a Practical Size

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:14.017966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de65a8d8-0768-4228-b9eb-3b4fe9a5274e · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:14.023076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 317f59da-9b4c-4acf-8bc5-4b789745c2ff · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption OPT: Open Pre-trained Transformer Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:14.006714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef09c261-98ff-4d95-90e5-f4872f9f1cd2 · outbound

This paper cites Scaling Up Membership Inference: When and How Attacks Succeed on Large Language Models.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Scaling Up Membership Inference: When and How Attacks Succeed on Large Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.959463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation facf4a61-669e-415a-8ac3-7358f7f32d34 · inbound

Permit: Permission-Aware Representation Intervention for Controlled Generation in Large Language Models cites this paper.

Permit: Permission-Aware Representation Intervention for Controlled Generation in Large Language Models SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:16:28.704910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.