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factual-accuracy

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chigwell / vidconcept-sum

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vidconcept-sum generates structured, factual summaries of scientific/educational concepts from video titles or descriptions using an LLM.

topic-extraction knowledge-distillation semantic-parsing educational-tool educational-content contextual-information media-analysis content-categorization ai-powered-summarization content-indexing video-summary structured-summary quick-insights llm-based-interpretation scientific-concept-extraction concise-explanation key-terms factual-accuracy non-speculative-response video-metadata-summarization
  • Updated Dec 21, 2025
  • Python

Vladusty / russian-history-llm-benchmark-100-lv

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Dataset of 100 Russian history multiple-choice questions (translated to Latvian) adapted from the Unified State Exam. Includes model evaluation code and results for several LLMs. Designed as a small benchmark to test factual accuracy on Russian history.

natural-language-processing digital-humanities google-colab multiple-choice-questions russian-history latvian-language llm-evaluation llm-benchmark digital-humanities-dataset factual-accuracy
  • Updated Nov 22, 2025
  • Jupyter Notebook

natanaheldr / hallucination-ledger

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Catch AI hallucinations before they catch you. Extract factual claims from LLM outputs, classify them as verified/doubtful/false, and track which models lie the most. Dark & light themes, bulk ops, keyboard shortcuts, full audit trail.

python nlp dark-theme sqlite verification fact-checking ai-safety misinformation audit-trail ai-toolkit fastapi llm hallucination-detection claims-extraction factual-accuracy
  • Updated Jul 26, 2026
  • Python

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