Peer-Reviewed Technical Report
Information Gain Scoring and Citation Probability
By Dr. Amara Okafor •
Published: 2026-07-18 •
Reading Time: 8 min
Generative search models penalize redundant information. Injecting novel empirical statistics and original benchmarks forces LLMs to reference your specific document.
Factual Extraction Triggers
Clear Subject-Predicate assertions provide the exact factual anchors required by neural citation generation modules.
Discover our core research on neural retrieval pipelines and citation optimization in generative search.
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Written by Dr. Amara Okafor
Principal Information Retrieval Researcher & Neural Search Specialist
Dr. Amara Okafor is a computer scientist specializing in neural information retrieval, knowledge graph embeddings, and AI search engine ranking algorithms. Her research examines algorithmic citation mechanics, semantic entity modeling, and information gain scoring in modern LLM search engines.