sharvari2/Hallucination-detection-LLM
Detecting hallucinations on SQuAD using classical ML and deep learning Models
SUMMARY AI要約 by gpt-5-mini
Repository for detecting hallucinations in LLM-generated answers. It builds a 5,000-sample SQuAD v1.1 dataset, generates answers, labels them, extracts features and trains nine models to classify hallucinations. Intended for ML/NLP practitioners who need lightweight detectors or baseline comparisons. Key results: a 1‑D CNN over concatenated question+context+generated answer achieves highest test accuracy (0.976). Simple classical baselines (logistic regression, random forest) using three handcrafted features—length difference, TF‑IDF cosine similarity, and a context‑match flag—are competitive (~0.96). Includes two notebooks (data build and full pipeline), processed datasets, model comparison plot, and uses Python, PyTorch/TensorFlow, Hugging Face, scikit‑learn. Requires Python 3.10+; GPU optional.
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合計 AI関連スコア: 75 / 100
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当サイトが追跡している Jupyter Notebook 製Repoは 966件 (うちAI関連スコア40以上は 715件)。 このRepoより スター数が多いのは 92件 (上位 9.6%)、 AI関連スコアが高いのは 32件 (上位 3.4%) です。
オーナー情報
日付
| GitHub作成日 | 2026-05-13 |
| 最終Push | 2026-05-13 |
| 当サイト初検出 | 2026-05-13 |
| 最終取得 | 2026-08-18 16:19 |
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