An Empirical Study of Vulnerability Detection using Federated Learning | Paper Citation Record

Observation 28ed6b1d-d53d-45a0-8bb8-82f8b220401c · outbound

This paper cites Reef: A framework for collecting real- world vulnerabilities and fixes,.

An Empirical Study of Vulnerability Detection using Federated Learning Reef: A framework for collecting real- world vulnerabilities and fixes,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.820957Z

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Observation d36ba755-fb74-4abd-9abb-de6d420ea335 · outbound

This paper cites Learning to locate and describe vulnerabilities,.

An Empirical Study of Vulnerability Detection using Federated Learning Learning to locate and describe vulnerabilities,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.809987Z

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Observation 091a0eeb-8c4e-419f-b638-e5914325add1 · outbound

This paper cites Toward improved deep learning-based vulnerability detection,.

An Empirical Study of Vulnerability Detection using Federated Learning Toward improved deep learning-based vulnerability detection,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.799366Z

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Observation 3402a6d5-479a-4a4f-836a-b28dea2a562d · outbound

This paper cites Sysevr: A framework for using deep learning to detect software vulnerabilities,.

An Empirical Study of Vulnerability Detection using Federated Learning Sysevr: A framework for using deep learning to detect software vulnerabilities,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.788628Z

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Observation eddc6e80-e92f-403b-8162-1909f21f9f61 · outbound

This paper cites Vuldeepecker: A deep learning-based system for vulnerability detection,.

An Empirical Study of Vulnerability Detection using Federated Learning Vuldeepecker: A deep learning-based system for vulnerability detection,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.778598Z

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Observation de096b10-4918-452d-974e-1fb69c3dcdc8 · outbound

This paper cites Vulchecker: Graph-based vulnerability localization in source code,.

An Empirical Study of Vulnerability Detection using Federated Learning Vulchecker: Graph-based vulnerability localization in source code,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.768859Z

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Observation 4e987683-27f9-4c08-98db-a7c949bae9d3 · outbound

This paper cites Vuldeelocator: A deep learning-based fine-grained vulnerability detector,.

An Empirical Study of Vulnerability Detection using Federated Learning Vuldeelocator: A deep learning-based fine-grained vulnerability detector,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.758685Z

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Observation 8f2cbc49-f55c-416c-87cf-0795ba4a6f19 · outbound

This paper cites Devign: Effective vulnerability identification by learning comprehensive program semantics via graph neural networks,.

An Empirical Study of Vulnerability Detection using Federated Learning Devign: Effective vulnerability identification by learning comprehensive program semantics via graph neural networks,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.748671Z

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Observation d0e7eb0f-d966-4f81-be51-efb7b369f62b · outbound

This paper cites Deep learning based vulnerability detection: Are we there yet?.

An Empirical Study of Vulnerability Detection using Federated Learning Deep learning based vulnerability detection: Are we there yet?

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.739389Z

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Observation dbf1130b-50a0-4e65-a2c4-8429ef8842c7 · outbound

This paper cites Coca: Improving and explaining graph neural network-based vulnerability detection systems,.

An Empirical Study of Vulnerability Detection using Federated Learning Coca: Improving and explaining graph neural network-based vulnerability detection systems,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.729360Z

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Observation dcfbe5eb-b5e7-4ab9-b323-cc3f985da6e8 · outbound

This paper cites Dataflow analysis-inspired deep learning for efficient vulnerability detection,.

An Empirical Study of Vulnerability Detection using Federated Learning Dataflow analysis-inspired deep learning for efficient vulnerability detection,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.718738Z

Source-reported events for the cited work

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Observation 376b899b-56a5-49c8-b090-c167a6a6adcb · outbound

This paper cites Reentrancy vulnerability detection and localization: A deep learning based two-phase approach,.

An Empirical Study of Vulnerability Detection using Federated Learning Reentrancy vulnerability detection and localization: A deep learning based two-phase approach,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.707694Z

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Observation fb047f66-df99-4b57-aaaa-1ae399c5d765 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

An Empirical Study of Vulnerability Detection using Federated Learning Communication-efficient learning of deep networks from decentralized data,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.696567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8cb1076f-1d6c-46f5-a963-4e060f79d9e6 · outbound

This paper cites Is aggregation the only choice? federated learning via layer-wise model recombination,.

An Empirical Study of Vulnerability Detection using Federated Learning Is aggregation the only choice? federated learning via layer-wise model recombination,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.686362Z

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Observation e8005cef-194a-4404-b296-1b56e6da520f · outbound

This paper cites Federated optimization in heterogeneous networks,.

An Empirical Study of Vulnerability Detection using Federated Learning Federated optimization in heterogeneous networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.675285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 82024759-618d-456e-bd9f-c0772cb4ed0e · outbound

This paper cites Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark.

An Empirical Study of Vulnerability Detection using Federated Learning Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T13:37:19.102203Z

Source-reported events for the cited work

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Observation fafad45a-ade1-4839-8593-d4064d28b260 · outbound

This paper cites Gitfl: Uncertainty-aware real-time asynchronous federated learning using version control,.

An Empirical Study of Vulnerability Detection using Federated Learning Gitfl: Uncertainty-aware real-time asynchronous federated learning using version control,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.664819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b1f09d2f-69bd-400f-8c8a-e5c08f3db97c · outbound

This paper cites Vulnerability detection based on federated learning,.

An Empirical Study of Vulnerability Detection using Federated Learning Vulnerability detection based on federated learning,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.654104Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 671dcfd2-0ab5-46e5-a1c4-cd2bbf0d16cc · outbound

This paper cites SCAFFOLD: Stochastic controlled averaging for federated learning,.

An Empirical Study of Vulnerability Detection using Federated Learning SCAFFOLD: Stochastic controlled averaging for federated learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.643150Z

Source-reported events for the cited work

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Observation 3bc5f5dd-c157-47f1-b757-e8ea9ed49ce9 · outbound

This paper cites Diversevul: A new vulnerable source code dataset for deep learning based vulnerability detection,.

An Empirical Study of Vulnerability Detection using Federated Learning Diversevul: A new vulnerable source code dataset for deep learning based vulnerability detection,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.633652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 34370cfd-0a46-4b46-b44b-6081d96f1c5d · outbound

This paper cites μvuldeepecker: A deep learning-based system for multiclass vulnerability detection,.

An Empirical Study of Vulnerability Detection using Federated Learning μvuldeepecker: A deep learning-based system for multiclass vulnerability detection,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.623294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 53d66d52-bbde-46bf-9580-0792fb5615ad · outbound

This paper cites VUDENC: vulnerability detection with deep learning on a natural codebase for python,.

An Empirical Study of Vulnerability Detection using Federated Learning VUDENC: vulnerability detection with deep learning on a natural codebase for python,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.613763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e03b8303-ca39-4266-8e3b-0d237d1ceaac · outbound

This paper cites Vuldebert: A vulnerability detection system using BERT,.

An Empirical Study of Vulnerability Detection using Federated Learning Vuldebert: A vulnerability detection system using BERT,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.603755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cc34d97e-19f7-45ca-9cb3-6a9d215d255c · outbound

This paper cites Software vulnerability detection with gpt and in-context learning,.

An Empirical Study of Vulnerability Detection using Federated Learning Software vulnerability detection with gpt and in-context learning,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.593407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0647aea7-b6c4-4d02-83ca-98f5838118f1 · outbound

This paper cites Transformer-based language models for software vulnerability detection,.

An Empirical Study of Vulnerability Detection using Federated Learning Transformer-based language models for software vulnerability detection,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.583265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9cc5c1d5-09f5-475c-8449-15edd526695e · outbound

This paper cites Fedcross: Towards accurate federated learning via multi-model cross-aggregation,.

An Empirical Study of Vulnerability Detection using Federated Learning Fedcross: Towards accurate federated learning via multi-model cross-aggregation,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.573050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 792e6091-2e5b-48fa-a00e-4ac73b1e6202 · outbound

This paper cites Clustered sampling: Low-variance and improved representativity for clients selection in federated learning,.

An Empirical Study of Vulnerability Detection using Federated Learning Clustered sampling: Low-variance and improved representativity for clients selection in federated learning,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.562182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8939d94e-f5aa-4a31-8724-c12f8b7b13a6 · outbound

This paper cites Federated learning with soft clustering,.

An Empirical Study of Vulnerability Detection using Federated Learning Federated learning with soft clustering,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.550551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5b8ce3a2-76e4-42c4-8d6f-03658f3142af · outbound

This paper cites Data-free knowledge distillation for heterogeneous federated learning,.

An Empirical Study of Vulnerability Detection using Federated Learning Data-free knowledge distillation for heterogeneous federated learning,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.539062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 670b9920-2f59-4a26-bdde-dc2cd3ad0f3f · outbound

This paper cites Fine-tuning global model via data-free knowledge distillation for non-iid federated learning,.

An Empirical Study of Vulnerability Detection using Federated Learning Fine-tuning global model via data-free knowledge distillation for non-iid federated learning,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.528062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7c09e2b2-dc3d-4a57-b5c8-8ebdb733ab16 · outbound

This paper cites Is Aggregation the Only Choice? Federated Learning via Layer-wise Model Recombination.

An Empirical Study of Vulnerability Detection using Federated Learning Is Aggregation the Only Choice? Federated Learning via Layer-wise Model Recombination

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-12T13:37:19.338392Z

Source-reported events for the cited work

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Observation 50831ff5-a928-4288-a238-87bb38929dfa · outbound

This paper cites FedMut: Generalized federated learning via stochastic mutation,.

An Empirical Study of Vulnerability Detection using Federated Learning FedMut: Generalized federated learning via stochastic mutation,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.517094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d3eb1d99-0019-4cf5-a7fb-23a62901bef8 · outbound

This paper cites Flexfl: Heterogeneous federated learning via apoz-guided flexible pruning in uncertain scenarios,.

An Empirical Study of Vulnerability Detection using Federated Learning Flexfl: Heterogeneous federated learning via apoz-guided flexible pruning in uncertain scenarios,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.506490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7b7e855c-5f58-4705-8f3e-4be2d94f7899 · outbound

This paper cites Adaptivefl: Adaptive heterogeneous federated learning for resource-constrained aiot systems,.

An Empirical Study of Vulnerability Detection using Federated Learning Adaptivefl: Adaptive heterogeneous federated learning for resource-constrained aiot systems,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.495412Z

Source-reported events for the cited work

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Observation 0d43288f-c0c7-4e13-86cd-af697b3578dc · outbound

This paper cites End-to-end federated learning for autonomous driving vehicles,.

An Empirical Study of Vulnerability Detection using Federated Learning End-to-end federated learning for autonomous driving vehicles,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.484237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3ff75205-78f5-4a05-b333-db16292b2235 · outbound

This paper cites Federated learning for healthcare informatics,.

An Empirical Study of Vulnerability Detection using Federated Learning Federated learning for healthcare informatics,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.473184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 07fa9823-4789-4b30-9a65-4186838f521c · outbound

This paper cites BERT: pre-training of deep bidirectional transformers for language understanding,.

An Empirical Study of Vulnerability Detection using Federated Learning BERT: pre-training of deep bidirectional transformers for language understanding,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.462704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 835ecf21-b227-46ef-a0fa-7326ad5273a3 · outbound

This paper cites Improving language understanding by generative pre- training,.

An Empirical Study of Vulnerability Detection using Federated Learning Improving language understanding by generative pre- training,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.451808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5be44936-37c0-4914-a197-e3ecc9015f7c · outbound

This paper cites OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization.

An Empirical Study of Vulnerability Detection using Federated Learning OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization

Reference 40

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Observation 90f39a71-7a86-4277-b600-8b33b1e3b430 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

An Empirical Study of Vulnerability Detection using Federated Learning Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.438988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f05f3a7a-4797-4d57-9eb3-02f7add565da · outbound

This paper cites Codet5: Identifier-aware unified pre-trained encoder-decoder models for code understanding and generation,.

An Empirical Study of Vulnerability Detection using Federated Learning Codet5: Identifier-aware unified pre-trained encoder-decoder models for code understanding and generation,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.426482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 326ae801-97f0-4a0f-87b3-0ae0e1a68bd3 · outbound

This paper cites Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning.

An Empirical Study of Vulnerability Detection using Federated Learning Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-12T13:37:19.204433Z

Source-reported events for the cited work

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Observation f94388f6-b016-4e0d-943a-421034ef6845 · outbound

This paper cites GPT Understands, Too.

An Empirical Study of Vulnerability Detection using Federated Learning GPT Understands, Too

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T13:37:19.207883Z

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Observation d6325a51-89a6-43cc-b7c2-608341e63c45 · outbound

This paper cites P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks.

An Empirical Study of Vulnerability Detection using Federated Learning P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-12T13:37:19.211579Z

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Observation a4ce2040-06bb-47a8-976d-00e92b239b8e · outbound

This paper cites LoRA: Low-rank adaptation of large language models,.

An Empirical Study of Vulnerability Detection using Federated Learning LoRA: Low-rank adaptation of large language models,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.414305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 59e7bc6f-f6f9-4969-bc85-3dbe073c77f7 · outbound

This paper cites FedPara: Low-Rank Hadamard Product for Communication-Efficient Federated Learning.

An Empirical Study of Vulnerability Detection using Federated Learning FedPara: Low-Rank Hadamard Product for Communication-Efficient Federated Learning

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-12T13:37:19.219657Z

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Observation a582428d-b5d3-44e6-8579-1f7468c6dc1d · outbound

This paper cites Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning,.

An Empirical Study of Vulnerability Detection using Federated Learning Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.402169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 33784534-e098-46d1-b0da-2ef021a0a695 · outbound

This paper cites Model-contrastive federated learning,.

An Empirical Study of Vulnerability Detection using Federated Learning Model-contrastive federated learning,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.389081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ad8e1323-795a-4203-a5b6-71b4ee0811e3 · outbound

This paper cites Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification.

An Empirical Study of Vulnerability Detection using Federated Learning Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-12T13:37:19.230669Z

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Observation d7f7d308-4715-4b1c-95c6-a6a331e53c36 · outbound

This paper cites Language models are unsupervised multitask learners,.

An Empirical Study of Vulnerability Detection using Federated Learning Language models are unsupervised multitask learners,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:37:19.376898Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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