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Paper Citation Record · LEDGER

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models

As of 22 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2505.04015.

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

pith.paper-citation-record.v1
2505.04015 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:45:04.280196Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

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  • verified fuzzy15
  • unresolved13
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3cc4f265-9d21-4a1f-885f-9462fb201e19 · outbound

This paper cites Scaling Laws for Neural Language Models.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Scaling Laws for Neural Language Models

Reference 1

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Observation 6c8969c2-572a-4d47-9113-d4193a16c727 · outbound

This paper cites Model complexity of deep learning: A survey,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Model complexity of deep learning: A survey,

Reference 2

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Observation 44f65bda-7420-4e28-8810-4c195236c0ac · outbound

This paper cites Backdoor learning: A survey,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Backdoor learning: A survey,

Reference 4

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Observation adaeb16b-a56e-4939-9bf9-40780edd45d5 · outbound

This paper cites Computing systems for autonomous driving: State of the art and challenges,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Computing systems for autonomous driving: State of the art and challenges,

Reference 5

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Observation 5968b526-f444-4bb8-be4c-33d1d2393564 · outbound

This paper cites Machine learning for medical imaging,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Machine learning for medical imaging,

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-15T23:45:04.618810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T23:45:04.179758Z digest=sha256:fa0f1d2e05aa05bb8d4397143d9d1e63da782a4fad57bdd25f3a6db670f57386

Observation 5c567ebb-d0fa-4531-be9a-2a4c1013b712 · outbound

This paper cites Machine learning for quantitative finance applications: A survey,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Machine learning for quantitative finance applications: A survey,

Reference 7

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raw_fallback, observed 2026-08-15T23:45:04.605409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 09df6819-04c8-4773-8e71-ef0d82d3000a · outbound

This paper cites Trojan signatures in dnn weights,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Trojan signatures in dnn weights,

Reference 8

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raw_fallback, observed 2026-08-15T23:45:04.591993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 07652c74-6c5e-4c60-9760-496154aca83a · outbound

This paper cites Cleann: Accelerated trojan shield for embedded neural networks,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Cleann: Accelerated trojan shield for embedded neural networks,

Reference 9

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raw_fallback, observed 2026-08-15T23:45:04.577955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation fca53d68-0d90-418e-815e-9cbefbb7f38b · outbound

This paper cites Anti-backdoor learning: Training clean models on poisoned data,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Anti-backdoor learning: Training clean models on poisoned data,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f5404cda-bf37-48f3-9490-451bcb38378c · outbound

This paper cites Backdoorbench: A comprehensive benchmark of backdoor learning,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Backdoorbench: A comprehensive benchmark of backdoor learning,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 9b1043c2-b9ee-4440-91ad-d79137002330 · outbound

This paper cites Enhancing fine- tuning based backdoor defense with sharpness-aware minimization,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Enhancing fine- tuning based backdoor defense with sharpness-aware minimization,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 3747c66c-a174-4b4b-96f6-ce6f7ae8a7ab · outbound

This paper cites Neural cleanse: Identifying and mitigating backdoor attacks in neural networks,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Neural cleanse: Identifying and mitigating backdoor attacks in neural networks,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation fc72bd32-5e26-4395-9a0b-22a6a3d35958 · outbound

This paper cites AST: Audio Spectrogram Transformer.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models AST: Audio Spectrogram Transformer

Reference 14

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Observation 9d9a63f3-9525-4a92-9a30-98fb320b9ded · outbound

This paper cites St-adapter: Parameter- efficient image-to-video transfer learning,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models St-adapter: Parameter- efficient image-to-video transfer learning,

Reference 15

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source=pdf_text observed=2026-08-15T23:45:04.220256Z digest=sha256:84e48ba4dcfa54cbe6bbe31b8d32dc1bdb0e198c8b168bb9916c3c0a775e012f

Observation d1e2a554-b09d-4204-972f-1009183a0388 · outbound

This paper cites A closer look at robustness of vision transformers to backdoor attacks,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models A closer look at robustness of vision transformers to backdoor attacks,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T23:45:04.224712Z digest=sha256:7bfd175f630c60953ababbf11dde5f811c65d768b425329ea8e68c250812b2a3

Observation c51ea591-5f66-4806-97c2-75486207b11a · outbound

This paper cites Adversarial attacks on deep-learning models in natural language processing: A survey,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Adversarial attacks on deep-learning models in natural language processing: A survey,

Reference 17

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Observation a9fe1caa-675d-4326-b414-5240e1bfc1d7 · outbound

This paper cites BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain

Reference 18

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Observation ace553e5-fd58-4023-b97a-e2f4f38740c6 · outbound

This paper cites Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Reference 19

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Observation 7281c749-37d6-42aa-a85f-9b38ae4defe1 · outbound

This paper cites Trojaning attack on neural networks,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Trojaning attack on neural networks,

Reference 20

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f926c54e-9740-4a60-b093-cf1d8a5b6f7c · outbound

This paper cites WaNet -- Imperceptible Warping-based Backdoor Attack.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models WaNet -- Imperceptible Warping-based Backdoor Attack

Reference 21

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Observation d9db498b-f28b-40da-83c5-540c98d421e5 · outbound

This paper cites A new backdoor attack in cnns by training set corruption without label poisoning,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models A new backdoor attack in cnns by training set corruption without label poisoning,

Reference 22

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 3aadee94-cb18-40ef-94ee-fba2e2a3852d · outbound

This paper cites Neural trojans,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Neural trojans,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 4043547c-fe42-4ecf-8762-400bdd1cec01 · outbound

This paper cites Fine-pruning: Defending against backdooring attacks on deep neural networks,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Fine-pruning: Defending against backdooring attacks on deep neural networks,

Reference 24

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T23:45:04.258770Z digest=sha256:b28e3009071770bfe42c131ab60418b9dd1d870db3501d66259b347e04a72140

Observation 9e8b6d0f-3376-483c-a905-5db9e2dd352c · outbound

This paper cites Delving deep into rectifiers: Surpassing human-level performance on imagenet classification,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Delving deep into rectifiers: Surpassing human-level performance on imagenet classification,

Reference 25

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Observation 00c815de-f72c-446e-ab91-c05d39a878c8 · outbound

This paper cites Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)

Reference 26

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source=pdf_text observed=2026-08-15T23:45:04.267425Z digest=sha256:476f26f96399f5d9c0acc5ba4653ff19f578c8cd29b15583fdb96be6502619df

Observation 7d459484-c06b-4312-a9d3-dcb7af7d639b · outbound

This paper cites Gaussian Error Linear Units (GELUs).

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Gaussian Error Linear Units (GELUs)

Reference 27

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Observation 0178b737-5699-4986-a7a3-c9b3551f138c · outbound

This paper cites Sigmoid-weighted linear units for neural network function approximation in reinforcement learning,.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Sigmoid-weighted linear units for neural network function approximation in reinforcement learning,

Reference 28

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no resolver link, observed 2026-08-15T23:45:04.276230Z

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Observation dc9f5d20-5c11-4e25-9d57-f97c30526b6d · outbound

This paper cites Cifar-10 (canadian institute for advanced research),.

MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models Cifar-10 (canadian institute for advanced research),

Reference 29

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raw_fallback, observed 2026-08-15T23:45:04.410863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Pith citing papers

No inbound Pith citation observations are available.