Author

Chandra Sekhar Sanaboina

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Open access Sep 2026

Evaluating the Efficiency of Large Language Models in Detecting and Mitigating Hallucinations Using a Curated Domain-Oriented Dataset and Post-Hoc Retrieval

Hallucination in large language models (LLMs) refers to the generation of plausible and coherent information that is incorrect, unsupported, or inconsistent with the available evidence. Detecting such hallucinations and verifying the information in generated responses are important for improving the reliability of LLM...

Chandra Sekhar Sanaboina, Tammisetti Surekha · International Journal of Inn... · 0 citations

Open access Aug 2026

Maria-X: A Multimodal Transformer Aware of Missing Data for Reliable Diagnosis and Prognosis of Alzheimer’s Disease

An imputation approach originally validated under MCAR is extended to instead operate under the more realistic Missing At Random (MAR) mechanism, which proves robust under MAR conditions, with particularly strong performance in cases where missingness is driven by observed variables a property that points toward practi...

Lakshmiprasannakumar Vemavarapu, Chandra Sekhar Sanaboina · International Journal of Com... · 0 citations

Open access Aug 2026

Elastic net–guided NSGA-II for scalable multi-objective feature selection in high-dimensional data analytics

An Elastic Net–Guided NSGA-II framework that integrates sparsity-aware statistical regularisation and multi-objective evolutionary optimisation is proposed, supporting a wide range of real-world applications, such as bioinformatics, healthcare, and financial analytics.

S. Subhani, Gudipati Murali, Chandra Sekhar Sanaboina · Discover Computing · 0 citations