Puwakpitiyage Sasmitha Mahesh Madhubhashana

EGV-Si: Evidence-Grounded Verification for Sinhala via Hybrid NLI and Factual Rules

This record contains the paper and related materials for EGV-Si, a hybrid system for Sinhala claim verification. EGV-Si combines a multilingual Natural Language Inference (NLI) model with eleven high-precision factual rules tailored to Sinhala. We introduce a 600-example evaluati...

EGV-Si: Evidence-Grounded Verification for Sinhala via Hybrid NLI and Factual Rules

This record contains the paper and related materials for EGV-Si, a hybrid system for Sinhala claim verification. EGV-Si combines a multilingual Natural Language Inference (NLI) model with eleven high-precision factual rules tailored to Sinhala. We introduce a 600-example evaluati...

Explainable Hallucination Detection in Large Language Models Using Evidence-Grounded Verification

This paper presents Evidence-Grounded Verification (EGV), a modular framework for explainable hallucination detection in large language models. EGV decomposes model outputs into atomic claims, retrieves independent evidence, performs fine-grained four-way verification (Supported,...

Explainable Hallucination Detection in Large Language Models Using Evidence-Grounded Verification

This paper presents Evidence-Grounded Verification (EGV), a modular framework for explainable hallucination detection in large language models. EGV decomposes model outputs into atomic claims, retrieves independent evidence, performs fine-grained four-way verification (Supported,...