Open Source LLM Explainability: Interpreting GPT, Llama, and Mistral Decisions

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Open Source Research
Open Source Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.20214595  13stabilfr·wdophcgmx
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[x]Cited by0○Referenced by 0 other hub article(s)
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Open Source Research by Oleh Ivchenko DOI: 10.5281/zenodo.20214595 13stabilfr·wdophcgmx
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Humanitarian Aid Diversion — Modeling Leakage Channels and Mitigation Strategies

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Geopolitical Research
Geopolitical Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.20196159  62stabilfr·wdophcgmx
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[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted100%✓≥80% from verified, high-quality sources
[a]DOI50%○≥80% have a Digital Object Identifier
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[i]Indexed0%○≥80% have metadata indexed
[l]Academic100%✓≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]2,267✓Minimum 2,000 words for a full research article. Current: 2,267
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.20196159
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]100%✓≥60% of references from 2025–2026. Current: 100%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (59 × 60%) + Required (4/5 × 30%) + Optional (1/4 × 10%)

Humanitarian assistance is increasingly channelled through complex logistical networks that span unstable conflict zones, fragile state infrastructures, and volatile political landscapes. While digital innovations such as privacy‑preserving wallets [1], satellite‑based monitoring [2], and bio‑inspired optimisation algorithms [3] promise greater transparency and efficiency, they also introduce n...

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Geopolitical Research by Oleh Ivchenko DOI: 10.5281/zenodo.20196159 62stabilfr·wdophcgmx
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[a]DOI50%○≥80% have a Digital Object Identifier
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[l]Academic100%✓≥80% from journals/conferences/preprints
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[r]References2 refs○Minimum 10 references required
[w]Words [REQ]2,267✓Minimum 2,000 words for a full research article. Current: 2,267
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[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]100%✓≥60% of references from 2025–2026. Current: 100%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
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[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (59 × 60%) + Required (4/5 × 30%) + Optional (1/4 × 10%)
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Real-Time XAI Specifications: Performance Requirements for Production Explanations

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Academic Research
Academic Research by Oleh Ivchenko  76stabilfr·wdophcgmx
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[t]Trusted100%✓≥80% from verified, high-quality sources
[a]DOI97%✓≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed95%✓≥80% have metadata indexed
[l]Academic100%✓≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References65 refs✓Minimum 10 references required
[w]Words [REQ]2,290✓Minimum 2,000 words for a full research article. Current: 2,290
[d]DOI [REQ]✗✗Zenodo DOI registered for persistent citation
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]100%✓≥60% of references from 2025–2026. Current: 100%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (93 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

The rapid deployment of AI-driven decision systems in production environments has intensified the demand for explanation generation that is not only semantically meaningful but also temporally bounded and resource-constrained. This article establishes a formal specification framework for real-time explainability, defining precise performance requirements for latency, fidelity, and computational...

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Academic Research by Oleh Ivchenko 76stabilfr·wdophcgmx
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[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted100%✓≥80% from verified, high-quality sources
[a]DOI97%✓≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed95%✓≥80% have metadata indexed
[l]Academic100%✓≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References65 refs✓Minimum 10 references required
[w]Words [REQ]2,290✓Minimum 2,000 words for a full research article. Current: 2,290
[d]DOI [REQ]✗✗Zenodo DOI registered for persistent citation
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
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[h]Freshness [REQ]100%✓≥60% of references from 2025–2026. Current: 100%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
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[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (93 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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Defense Procurement Transparency — Audit Frameworks for Wartime Spending

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Economic Research
Economic Research by Oleh Ivchenko, Iryna Ivchenko & Dmytro Grybeniuk  ·  DOI: 10.5281/zenodo.20181665  13stabilfr·wdophcgmx
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[t]Trusted0%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic0%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]0✗Minimum 2,000 words for a full research article. Current: 0
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.20181665
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams0○Mermaid architecture/flow diagrams. Current: 0
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (1 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)

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Economic Research by Oleh Ivchenko, Iryna Ivchenko & Dmytro Grybeniuk DOI: 10.5281/zenodo.20181665 13stabilfr·wdophcgmx
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[t]Trusted0%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
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[l]Academic0%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]0✗Minimum 2,000 words for a full research article. Current: 0
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.20181665
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams0○Mermaid architecture/flow diagrams. Current: 0
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (1 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)
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The Legal Industry AI Transformation: From Research to Courtroom

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Technical Research
Technical Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.20168865  46stabilfr·wdophcgmx
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[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted73%○≥80% from verified, high-quality sources
[a]DOI55%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed9%○≥80% have metadata indexed
[l]Academic64%○≥80% from journals/conferences/preprints
[f]Free Access91%✓≥80% are freely accessible
[r]References11 refs✓Minimum 10 references required
[w]Words [REQ]1,401✗Minimum 2,000 words for a full research article. Current: 1,401
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.20168865
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]27%✗≥60% of references from 2025–2026. Current: 27%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams2✓Mermaid architecture/flow diagrams. Current: 2
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (52 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)

The legal services sector is undergoing a profound transformation driven by artificial intelligence technologies that reshape economics and workflows across core domains. This article systematically investigates AI’s impact on e-discovery, contract analysis, legal writing, and courtroom preparation, addressing three critical research questions: (RQ1) How has AI altered cost structures and effic...

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Technical Research by Oleh Ivchenko DOI: 10.5281/zenodo.20168865 46stabilfr·wdophcgmx
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[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted73%○≥80% from verified, high-quality sources
[a]DOI55%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed9%○≥80% have metadata indexed
[l]Academic64%○≥80% from journals/conferences/preprints
[f]Free Access91%✓≥80% are freely accessible
[r]References11 refs✓Minimum 10 references required
[w]Words [REQ]1,401✗Minimum 2,000 words for a full research article. Current: 1,401
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.20168865
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]27%✗≥60% of references from 2025–2026. Current: 27%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams2✓Mermaid architecture/flow diagrams. Current: 2
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (52 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)
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Trusted Open Source AI in Healthcare: Curated Stack for Clinical AI

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Open Source Research
Open Source Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.20151156  70stabilfr·wdophcgmx
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[s]Reviewed Sources50%○≥80% from editorially reviewed sources
[t]Trusted93%✓≥80% from verified, high-quality sources
[a]DOI79%○≥80% have a Digital Object Identifier
[b]CrossRef64%○≥80% indexed in CrossRef
[i]Indexed57%○≥80% have metadata indexed
[l]Academic86%✓≥80% from journals/conferences/preprints
[f]Free Access93%✓≥80% are freely accessible
[r]References14 refs✓Minimum 10 references required
[w]Words [REQ]1,703✗Minimum 2,000 words for a full research article. Current: 1,703
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.20151156
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]77%✓≥60% of references from 2025–2026. Current: 77%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams2✓Mermaid architecture/flow diagrams. Current: 2
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (83 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

Open-source AI technologies are rapidly transforming healthcare, especially in clinical decision support (CDS) where timely, transparent, and auditable models are essential [1]. Despite this momentum, trust in open-source solutions remains fragmented due to limited standardized evaluation frameworks and provenance tracking [2]. To address these challenges, we introduce a curated stack that aggr...

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Open Source Research by Oleh Ivchenko DOI: 10.5281/zenodo.20151156 70stabilfr·wdophcgmx
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[s]Reviewed Sources50%○≥80% from editorially reviewed sources
[t]Trusted93%✓≥80% from verified, high-quality sources
[a]DOI79%○≥80% have a Digital Object Identifier
[b]CrossRef64%○≥80% indexed in CrossRef
[i]Indexed57%○≥80% have metadata indexed
[l]Academic86%✓≥80% from journals/conferences/preprints
[f]Free Access93%✓≥80% are freely accessible
[r]References14 refs✓Minimum 10 references required
[w]Words [REQ]1,703✗Minimum 2,000 words for a full research article. Current: 1,703
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.20151156
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]77%✓≥60% of references from 2025–2026. Current: 77%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams2✓Mermaid architecture/flow diagrams. Current: 2
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (83 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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Cross-Border AI Explanation Requirements: Specifying XAI for Multi-Jurisdictional Compliance

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Academic Research
Academic Research by Oleh Ivchenko  51stabilfr·wdophcgmx
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[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted81%✓≥80% from verified, high-quality sources
[a]DOI69%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed12%○≥80% have metadata indexed
[l]Academic77%○≥80% from journals/conferences/preprints
[f]Free Access92%✓≥80% are freely accessible
[r]References26 refs✓Minimum 10 references required
[w]Words [REQ]1,947✗Minimum 2,000 words for a full research article. Current: 1,947
[d]DOI [REQ]✗✗Zenodo DOI registered for persistent citation
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]64%✓≥60% of references from 2025–2026. Current: 64%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (61 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)

Artificial intelligence systems are increasingly deployed across jurisdictions that impose distinct obligations on the transparency and interpretability of model decisions. While the European Union’s AI Act establishes a comprehensive framework for high‑risk AI, the United States relies on sector‑specific Executive Orders and guidance from the National Institute of Standards and Technology (NIS...

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Academic Research by Oleh Ivchenko 51stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted81%✓≥80% from verified, high-quality sources
[a]DOI69%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed12%○≥80% have metadata indexed
[l]Academic77%○≥80% from journals/conferences/preprints
[f]Free Access92%✓≥80% are freely accessible
[r]References26 refs✓Minimum 10 references required
[w]Words [REQ]1,947✗Minimum 2,000 words for a full research article. Current: 1,947
[d]DOI [REQ]✗✗Zenodo DOI registered for persistent citation
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]64%✓≥60% of references from 2025–2026. Current: 64%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (61 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)
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The Open Source XAI Ecosystem: Gaps, Opportunities, and Trusted Projects to Watch

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Open Source Research
Open Source Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.20115253  65stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources5%○≥80% from editorially reviewed sources
[t]Trusted84%✓≥80% from verified, high-quality sources
[a]DOI78%○≥80% have a Digital Object Identifier
[b]CrossRef3%○≥80% indexed in CrossRef
[i]Indexed8%○≥80% have metadata indexed
[l]Academic81%✓≥80% from journals/conferences/preprints
[f]Free Access89%✓≥80% are freely accessible
[r]References37 refs✓Minimum 10 references required
[w]Words [REQ]2,239✓Minimum 2,000 words for a full research article. Current: 2,239
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.20115253
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]67%✓≥60% of references from 2025–2026. Current: 67%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (64 × 60%) + Required (4/5 × 30%) + Optional (1/4 × 10%)

Explainable Artificial Intelligence (XAI) has moved from niche academic curiosity to a cornerstone of responsible AI deployment in enterprises worldwide. Recent industry surveys indicate that 68% of Fortune 500 companies now require interpretability mechanisms for any production model, yet only 24% of open-source AI libraries provide robust, production-grade explanation tools (see [1], [2], [3]...

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Open Source Research by Oleh Ivchenko DOI: 10.5281/zenodo.20115253 65stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources5%○≥80% from editorially reviewed sources
[t]Trusted84%✓≥80% from verified, high-quality sources
[a]DOI78%○≥80% have a Digital Object Identifier
[b]CrossRef3%○≥80% indexed in CrossRef
[i]Indexed8%○≥80% have metadata indexed
[l]Academic81%✓≥80% from journals/conferences/preprints
[f]Free Access89%✓≥80% are freely accessible
[r]References37 refs✓Minimum 10 references required
[w]Words [REQ]2,239✓Minimum 2,000 words for a full research article. Current: 2,239
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.20115253
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]67%✓≥60% of references from 2025–2026. Current: 67%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (64 × 60%) + Required (4/5 × 30%) + Optional (1/4 × 10%)
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Reconstruction Economics — Preventing Shadow Economy Capture of Rebuilding Funds

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Economic Research
Economic Research by Oleh Ivchenko, Iryna Ivchenko & Dmytro Grybeniuk  ·  DOI: 10.5281/zenodo.20113107  45stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted80%✓≥80% from verified, high-quality sources
[a]DOI60%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic70%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References10 refs✓Minimum 10 references required
[w]Words [REQ]1,584✗Minimum 2,000 words for a full research article. Current: 1,584
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.20113107
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
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1 Ivchenko, Oleh, Ivchenko, Iryna 3 Reconstruction Economics — Preventing Shadow Economy Capture of Rebuilding Funds. Research article: Reconstruction Economics — Preventing Shadow Economy Capture of Rebuilding Funds. Odessa National Polytechnic University, Department of Economic Cybernetics. DOI: 10.5281/zenodo.20113107  ·  View on Zenodo (CERN) 1 Ivchenko, O. & Ivchenko, I. 3 R...

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Economic Research by Oleh Ivchenko, Iryna Ivchenko & Dmytro Grybeniuk DOI: 10.5281/zenodo.20113107 45stabilfr·wdophcgmx
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Shadow Economy Dyn…Read More
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The Financial Industry AI Transformation: From Trading to Compliance

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Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.20110009  55stabilfr·wdophcgmx
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The financial services sector is undergoing a profound transformation driven by artificial intelligence, with algorithmic trading, fraud detection, credit underwriting, and regulatory compliance representing key application domains. This article examines the current state of AI adoption across these domains, analyzing both the technological innovations and the associated risks. Through a synthe...

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.20110009 55stabilfr·wdophcgmx
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Future of AIRead More
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