SemanticCite: Citation Verification with AI-Powered Full-Text Analysis and Evidence-Based Reasoning

TL;DR

SemanticCite is an AI system that verifies citation accuracy by analyzing full texts and providing detailed, evidence-based explanations, addressing challenges like citation errors and AI hallucinations in scientific literature.

Contribution

It introduces a novel AI-powered framework combining multiple retrieval methods and a four-class classification system for nuanced citation verification and provides an open-source dataset and models.

Findings

Lightweight models perform comparably to large systems.

The system achieves high accuracy in classifying citation support levels.

Open-source tools facilitate scalable citation verification.

Abstract

Effective scientific communication depends on accurate citations that validate sources and guide readers to supporting evidence. Yet academic literature faces mounting challenges: semantic citation errors that misrepresent sources, AI-generated hallucinated references, and traditional citation formats that point to entire papers without indicating which sections substantiate specific claims. We introduce SemanticCite, an AI-powered system that verifies citation accuracy through full-text source analysis while providing rich contextual information via detailed reasoning and relevant text snippets. Our approach combines multiple retrieval methods with a four-class classification system (Supported, Partially Supported, Unsupported, Uncertain) that captures nuanced claim-source relationships and enables appropriate remedial actions for different error types. Our experiments show that fine-tuned lightweight language models achieve performance comparable to large commercial systems with significantly lower computational requirements, making large-scale citation verification practically feasible. The system provides transparent, evidence-based explanations that support user understanding and trust. We contribute a comprehensive dataset of over 1,000 citations with detailed alignments, functional classifications, semantic annotations, and bibliometric metadata across eight disciplines, alongside fine-tuned models and the complete verification framework as open-source software. SemanticCite addresses critical challenges in research integrity through scalable citation verification, streamlined peer review, and quality control for AI-generated content, providing an open-source foundation for maintaining citation accuracy at scale.