Max-pooling Network Revisited: Analyzing the Role of Semantic Probability in Multiple Instance Learning for Hallucination Detection

arXiv:2605.08863 · cs.CL, cs.LG · Submitted 2026-05-09 · Read on arXiv

cs.CL, cs.LG

Submitted: 2026-05-09

Updated: 2026-09-26

Code: https://github.com/FUJI1229/Hallucination_Detection

Terminology

• Hallucination — 46× in this paper · explained in 3 episodes
• Hallucination Detection — 20× in this paper · explained in 2 episodes
• AUC — 17× in this paper · explained in 2 episodes
• Aggregation — 16× in this paper · explained in 1 episode
• Consistency — 14× in this paper · explained in 3 episodes
• Feature Extraction — 12× in this paper · explained in 2 episodes
• Multiple Instance Learning — 11× in this paper
• Generalization — 6× in this paper · explained in 13 episodes
• Computational overhead — 5× in this paper · explained in 2 episodes
• Multiple Instance Learning (MIL) — 5× in this paper · explained in 2 episodes
• Semantic Entropy — 5× in this paper
• Benchmark — 3× in this paper · explained in 2 episodes
• Clustering — 3× in this paper · explained in 2 episodes
• Curse of Dimensionality — 3× in this paper · explained in 6 episodes
• Large Language Models (LLMs) — 3× in this paper · explained in 6 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Attention Mechanism — 2× in this paper · explained in 2 episodes
• Natural Questions — 2× in this paper
• Semantic Similarity — 2× in this paper · explained in 2 episodes
• Ambient Dimension — 1× in this paper · explained in 1 episode
• Error Localization — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generalization Bounds — 1× in this paper · explained in 2 episodes
• Gradient Flow — 1× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Natural Language Inference (NLI) — 1× in this paper · explained in 2 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• The Llama 3 Herd of Models
• Mistral 7B

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