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Paper Citation Record · LEDGER

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification

As of 8 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2607.09936.

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

pith.paper-citation-record.v1
2607.09936 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T14:29:04.708853Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

23 of 23 outbound references displayed

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External citation measurements

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Outbound references

Observation 4c7057f2-f8fb-42c4-a497-40c483d9e104 · outbound

This paper cites Evaluating llm generated detection rules in cybersecurity.arXiv preprint arXiv:2509.16749,.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Evaluating llm generated detection rules in cybersecurity.arXiv preprint arXiv:2509.16749,

Reference 1

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:620c711b1a7eb00406d9b4a0ad5193dec94787366bc3d5c85b3284c8f276e5de

Observation 5d9b0047-2f12-4946-9cf2-55ddfcc51a1a · outbound

This paper cites Avast-CTU Public CAPE Dataset.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Avast-CTU Public CAPE Dataset

Reference 2

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:cacfa6738f520b0887a611ea802687a58aa842ebbe36efa1ca45d6d5a64c39fc

Observation 7d88b08e-98d1-420b-8e59-f7f8cb2eaf22 · outbound

This paper cites CCCS-CIC-AndMal-2020 Dataset.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification CCCS-CIC-AndMal-2020 Dataset

Reference 3

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:ab78ee2b38f663857215dac3ec645f12ae18b945a451ff66be556b82ee94b86e

Observation 40dd9727-f4bb-4e39-b000-ea55799c3f99 · outbound

This paper cites Under review.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Under review

Reference 4

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:eeedb80cb7695fbec79edede0418db17feb777812478456eb137398b64cec221

Observation ad3305c5-e4a7-4a37-a695-1f138bee2bb3 · outbound

This paper cites Zhuo Chen, Yufeng Huang, Jiaoyan Chen, Yuxia Geng, Wen Zhang, Yin Fang, Jeff Z Pan, and Huajun Chen.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Zhuo Chen, Yufeng Huang, Jiaoyan Chen, Yuxia Geng, Wen Zhang, Yin Fang, Jeff Z Pan, and Huajun Chen

Reference 5

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:5f923d8bfd539adf95c97ec85c45a8b2cef112b1f51260f0d674dc9f16f6c0ac

Observation fcab3403-9236-46a3-abd7-caced24a342d · outbound

This paper cites Clip-driven zero-shot learning with ambiguous labels.arXiv preprint arXiv:2603.05053,.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Clip-driven zero-shot learning with ambiguous labels.arXiv preprint arXiv:2603.05053,

Reference 6

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:cf66d8f4afbb993048001bbca56a0332aec03372dcc1df31f58c194dadb05eb0

Observation 940c0d66-f61d-4483-80f4-01eb0ee8a09f · outbound

This paper cites Zero-shot learning on semantic class prototype graph.IEEE transactions on pattern analysis and machine intelligence, 40(8):2009–2022,.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Zero-shot learning on semantic class prototype graph.IEEE transactions on pattern analysis and machine intelligence, 40(8):2009–2022,

Reference 7

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:d0e86fd34c97bb62b9b17e7d7ddb302de41b5ddf04eb997b485280f981a33f91

Observation f0fbfb2e-db26-45bc-9d11-313cc3a0db87 · outbound

This paper cites LLM-FS: Zero-Shot Feature Selection for Effective and Interpretable Malware Detection.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification LLM-FS: Zero-Shot Feature Selection for Effective and Interpretable Malware Detection

Reference 8

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:7737e25b5bbbee4cc7cc09ce79c4d5076dc17b22e8e20f9b842f87ea0383721d

Observation 4b9749ee-4157-4f4a-860b-f5463197dc13 · outbound

This paper cites TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second

Reference 9

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:ed97ea69c174c836949cee09f711381e57c9cbb5a4f79982cae72addabd232e3

Observation 570b43ff-b222-482c-9bde-dac799ba9f34 · outbound

This paper cites Revisiting Concept Drift in Windows Malware Detection: Adaptation to Real Drifted Malware with Minimal Samples.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Revisiting Concept Drift in Windows Malware Detection: Adaptation to Real Drifted Malware with Minimal Samples

Reference 10

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:11b1ee93016e15bee3e60413f61d3814580d64e29dc064ba735d0c1ce9d34247

Observation e74f9a2e-6064-4182-a1d1-5a0000ea2da4 · outbound

This paper cites FALCON: Transforming Cyber Threat Intelligence into Deployable IDS Rules with Self-Reflection.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification FALCON: Transforming Cyber Threat Intelligence into Deployable IDS Rules with Self-Reflection

Reference 11

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:ed72c985b050e33c6ed77b7aee3301686369b244db102609a6a067f74e7b9239

Observation 700ea50d-90df-4a87-8407-48e818ae3dfa · outbound

This paper cites Haojie Pan, Chengyu Wang, Minghui Qiu, Yichang Zhang, Yaliang Li, and Jun Huang.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Haojie Pan, Chengyu Wang, Minghui Qiu, Yichang Zhang, Yaliang Li, and Jun Huang

Reference 12

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:a3061287bc1ad7dc96b6bf2d14269769a093813c2062e92bfcc1df8afed766d8

Observation e1fdad20-4935-4200-90ef-732d78845c2d · outbound

This paper cites Generating Fake Cyber Threat Intelligence Using Transformer-Based Models.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Generating Fake Cyber Threat Intelligence Using Transformer-Based Models

Reference 13

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:1f817c5539d3c9b08b15d2258174fe34459982f189cea0eb5f4f65bd53973349

Observation 0bdfc0e1-a09c-4036-b430-3f8b175c5aa8 · outbound

This paper cites Under review.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Under review

Reference 14

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:2e711636ed1d97ab4b179b71b8059b0dad43b555eb194d6518dceae33fdf0ede

Observation 44f6c612-bd16-4eb1-90db-31e25fc072dd · outbound

This paper cites Vinay Kumar Verma, Dhanajit Brahma, and Piyush Rai.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Vinay Kumar Verma, Dhanajit Brahma, and Piyush Rai

Reference 15

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:3a44b2179f8cc6ff8c018b5925a829d3ac317eba1638014be475dca34b496740

Observation a6bf01e7-52e9-4c89-b4d4-f875ac4a5499 · outbound

This paper cites Fine-Grained Spoiler Detection from Large-Scale Review Corpora.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Fine-Grained Spoiler Detection from Large-Scale Review Corpora

Reference 16

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:38130dd3e5a763e9e9d459b33a549c2b250fd9b9c6f6e762148e6c32c5d61e1f

Observation 685c7f7c-e128-47de-b29d-6855335d7b50 · outbound

This paper cites LLM Empowered Prototype Learning for Zero and Few-Shot Tasks on Tabular Data.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification LLM Empowered Prototype Learning for Zero and Few-Shot Tasks on Tabular Data

Reference 17

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Observation ece81874-52f9-449f-85c5-932e3166466c · outbound

This paper cites Zero-shot Meta-learning for Tabular Prediction Tasks with Adversarially Pre-trained Transformer.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Zero-shot Meta-learning for Tabular Prediction Tasks with Adversarially Pre-trained Transformer

Reference 18

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Observation f6a5805b-8a98-4b29-9102-88e95ef83745 · outbound

This paper cites Under review.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Under review

Reference 19

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:774d98b731a2af8f4a27f13f71e552e9084fba6889ffa0e354ae48efe862ea8d

Observation 47c7e72f-2fdf-496c-89f7-6faa2e4f1676 · outbound

This paper cites Each method is trained and evaluated on all classes with full label access, representing the upper bound that zero-shot methods aspire to approach.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Each method is trained and evaluated on all classes with full label access, representing the upper bound that zero-shot methods aspire to approach

Reference 20

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:67a69bb11e07a414624bee765eccb138bc5dfcc560755ec26e890ef0bb851d1b

Observation 3d90fcd8-fa64-4f4b-9e9d-bbca8225f4c2 · outbound

This paper cites Under review.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Under review

Reference 21

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:01b31d7577453de7efc47937f9173d949b19121f6eb24383829ec1badae03b2a

Observation 1c95d40e-a729-442e-aa66-d8c3b6e46d47 · outbound

This paper cites Under review.

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification Under review

Reference 22

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:056eb973c1a833eede6d8259b87931a96434f3c88cb8bab5036774509108e6cb

Observation 85133d6c-292d-4ff8-83b8-5f376832a5fa · outbound

This paper cites K= 0 is the zero-shot setting; S = Seen Acc (%),U= Unseen Acc (%),H= Harmonic Mean (%).

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification K= 0 is the zero-shot setting; S = Seen Acc (%),U= Unseen Acc (%),H= Harmonic Mean (%)

Reference 23

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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:9470f3b1e750a2a87db8a2df4261e9761958eacda7afa0f2407d5858098ec4a6

Pith citing papers

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