International conference Recent advances in natural language processing

Toward Quantum-Enhanced Natural Language Understanding: Sarcasm and Claim Detection with QLSTM

Pritam Pal, Dipankar Das

Published Jan 1, 2025• 2 citations

Abstract

Traditional machine learning (ML) and deep learning (DL) models have shown effectiveness in natural language processing (NLP) tasks, such as sentiment analysis.However, they often struggle with complex linguistic structures, such as sarcasm and implicit claims.This paper introduces a Quantum Long Short-Term Memory (QLSTM) framework for detecting sarcasm and identifying claims in text, aiming to enhance the analysis of complex sentences.We evaluate four approaches: (1) classical LSTM, (2) quantum framework using QLSTM, (3) voting ensemble combining classical and quantum LSTMs, and (4) hybrid framework integrating both types.The experimental results indicate that the QLSTM approach excels in sarcasm detection, while the voting framework performs best in claim identification.

DOI: 10.26615/978-954-452-098-4-097

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