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Quantum-inspired Language Model with Lindblad Master Equation and Interference Measurement for Sentiment Analysis

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3APL5MI47S" target="_blank" >RIV/00216208:11320/25:PL5MI47S - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200261674&partnerID=40&md5=a2bbde31d6e0c656639f56f2d9ffbeff" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200261674&partnerID=40&md5=a2bbde31d6e0c656639f56f2d9ffbeff</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Quantum-inspired Language Model with Lindblad Master Equation and Interference Measurement for Sentiment Analysis

  • Original language description

    Quantum-inspired models have demonstrated superior performance in many downstream language tasks, such as question answering and sentiment analysis. However, recent models primarily focus on embedding and measurement operations, overlooking the significance of the quantum evolution process. In this work, we present a novel quantum-inspired neural network, LI-QiLM, which integrates the Lindblad Master Equation (LME) to model the evolution process and the interferometry to the measurement process, providing more physical meaning to strengthen the interpretability. We conduct comprehensive experiments on six sentiment analysis datasets. Compared to the traditional neural networks, transformer-based pre-trained models and quantum-inspired models, such as CICWE-QNN and ComplexQNN, the proposed method demonstrates superior performance in accuracy and F1-score on six commonly used datasets for sentiment analysis. Additional ablation tests verify the effectiveness of LME and interferometry. © 2024 Association for Computational Linguistics.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proc. Conf. North American Chapter Assoc. Comput. Linguist.: Hum. Lang. Technol., NAACL

  • ISBN

    979-889176114-8

  • ISSN

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    2112-2121

  • Publisher name

    Association for Computational Linguistics (ACL)

  • Place of publication

  • Event location

    Mexico City

  • Event date

    Jan 1, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article