Hallucination Detection System For Large Language Models (llms) Using Genai

• Author(s):

  Keerthi .K | Jayashree.S | Dharani.R | Archana.P | Mrs.J. jenila

• Keywords:

  Large Language Models (LLMs), Hallucination Detection, Sentence Embeddings, Evidence Retrieval, Self- Consistency, Fact Verification.

• Abstract:

  Large Language Models (LLMs) Often Generate Plausible Yet Incorrect Information, Known As Hallucinations. This Paper Proposes A Real-time Hallucination Detection System That Evaluates The Reliability Of LLM Outputs. The System Combines Evidence Retrieval From Trusted Sources, Semantic Similarity Using Sentence Embeddings, And Self-consistency Checks Across Multiple Responses. A Unified Decision Module Classifies Outputs As Factual Or Hallucinated. Implemented As A Streamlit Web Application, The System Provides An Intuitive Interface For Evaluating Responses. This Approach Enhances Transparency, Reliability, And Trust In AI-generated Content For Research And Professional Use.

---

Other Details

• Paper id:

  IJSARTV12I3104813

• Published in:

  Volume: 12 Issue: 3 March 2026

• Publication Date:

  2026-03-30

Download Article