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Paper Citation Record · LEDGER

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

As of 10 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 2026-08-09T06:31:02.800959+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:e8f2b5b87c43a3b6f2b91af4834d37406707b35535db96dda5e96278d9e887f6

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=sha256:9fc465641bd29795e191d57176ec015524f24ce25deb8a354db557a8d158a02d

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:d65f72eb13c8e2e84399bf577af7cdb0931fce3ca01a2acdb280d2ab91e4801c

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=sha256:3f3479c60fc53c56113085313d71c9133979bc522427d8ff8a4632b9d9946d60

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=sha256:26039c058326862164c9896561e8994198e892b680de441f8bbddd07765c7979

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=sha256:8ba1b4f79f96baf3201eefccf9fadd9830c6e1256505833640229929547d0a40

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:cc0d41f8383a76352b6930d302593b48cbb0ffe562c4f5a44ce4193412add1b0

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:c76d493d1bb3534dc4c6bcbaa77b4c413b4758500c8b4d5d6b39b4ffb74c778f

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:f77c6afb7d94220304e73e730fa23617f21e9b4e3d1aa0b04aa4ad7aaabc46fc

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=sha256:90dbaaff97b9a7c9ba41c666c351c227b1b0d28d75bbfbf03bab902bb3558676

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:abc85638b0db75a97bd09471503f2b2e099d9324ecec00bdc8359c8beb5c7b93

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=sha256:2d6b27f9109ae8f4ebda428b963046edab4b6d6fc2d3cffd739e9723597c8160

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:e8d6bfee98255ce3c3c5030097668cc39e1548518ba1b180f58115cebd17611f

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:a091595714b94ed14ecffbfa79d29725ad84d723b59b28948e8c8822c4f4db4b

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:c2c3d2daa761d8f91402cf9b7e8b5861d0865e68f0657fad8166b50638ff2906

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:fa93efb46509b7175b887b181e571711b595b2a3327404e1f049d10046b16a10

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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source=pdf_text observed=2026-07-14T14:29:04.708853Z digest=sha256:52bcb68cccc436d6e7d6e5fdfac29721f58b10e86af346cf3e3cb66ff9673669

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=sha256:232f5a65f88746bca31d69a00b0ab63f772155dcb241807a0376a3de10b0acec

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=sha256:0600f1b0555afa2b76a1ae1da3e2bcb199e39b96364defd351b0c39282b74701

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:ced7e888db99d8f68bee000aa5c9080e7837854685ab85bc09f2c786ddfe1ac9

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=sha256:5ac79cabf6479bb58aa1f6f5a17e9ddfc6000048409d8ddf4528a242b96a7267

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=sha256:884637a51e0b6a5204d021796eea9358f55d60adf531f6aa77309ac15766eaa9

Pith citing papers

No inbound Pith citation observations are available.