Quantum NLP

NLP: Natural Language Processing

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11 papers4 papers in the last four weeks, down 20% on the four weeks before. 0.0% of all new papers.

Wave Is All You Need: A Quantum Language Model Based on Fully Connected Quantum Boltzmann Machine
Oct 25, 2026Jun LiuLanguage Modeling Quantum NLP
EmotiQ: A Quantum Residual Specialist Framework for Text Emotion Classification
Oct 18, 2026Carlton Kigonya, Tanaka Chirara, Yunting YinQuantum NLP Emotion Recognition
Department of Computer Science, Earlham College, Richmond, IN, USA · Department of Computer Science, Eastern Michigan University, Ypsilanti, MI, USA
A Quantum Machine Learning Approach to Content-Based Media Recommendation
Oct 15, 2026Mina Abbaszadeh, Ouissal Moumou, Anna Pearson +4Quantum NLP Recommender Systems
Quantinuum United Kingdom · University College London United Kingdom · Relational Intelligence United Kingdom +1
What Does It Cost to Simulate a Quantum Sentence Classifier? An Energy and Compute Perspective on Near-Term QNLP
Oct 5, 2026Kishlay Kashyap, Sandipan GangulyQuantum NLP Quantum Machine Learning
Heritage Institute of Technology
Circuit Hypernetworks for Quantum-Augmented Diffusion Language Models
Sep 21, 2026Xiaoqiang Wang, Mengyang Xiong, Jun Dai +1LLM Fine-Tuning Quantum Machine Learning
D´epartement d´informatique et de recherche op´erationnelle, Universit´e de Montr´eal, Montr´eal, QC, Canada. · Mila, Quebec AI Institute, Montr´eal, QC, Canada. · McGill University, Montr´eal, QC, Canada.
Variational Quantum Transformer Architecture for Synthetic Language Generation
Sep 16, 2026Julian Hager, Michael Kölle, Gerhard Stenzel +3Quantum NLP Quantum Machine Learning
Institute of Informatics, LMU Munich, Oettingenstraße 67, 80538 Munich, Germany
Parameter-Efficient Quantum NLP for Paraphrase Detection: Performance, Robustness, and Entanglement
Sep 13, 2026Farha Nausheen, Khandakar Ahmed, Farina RiazQuantum NLP Quantum Machine Learning
ISILC, Victoria University, Melbourne, VIC, Australia · CSIRO, Australian International Institute of Higher Education, Sydney, NSW, Australia
Scaling Hindi Quantum Natural Language Processing through Automatic Pregroup Supertagging
Sep 12, 2026Gautami Sanjay Naik, Krishna Bhatia, Mithun Paul Saint-Germain +1Quantum NLP LLM-Assisted Annotation
Indian Institute of Information Technology Dharwad, Dharwad, India · Fractal Analytics · Arizona State University, Arizona, USA
Hybrid Quantum-Classical NLP Classification with Compact Semantic Representations: An Experimental Analysis of Representation Compression
Sep 9, 2026Ali Hassan, Zijia Zhao, Maha A. MetaweiHybrid Quantum-Classical ML Text Classification
German University in Cairo, Cairo, Egypt · University of Melbourne, Melbourne, Australia · High Performance Computing Lab, Electronics Research Institute, Cairo, Egypt
SPSA Hyperparameter Tuning for Variational Quantum Natural Language Inference
Aug 11, 2026Nayan D'Souza, Christopher J. AgostinoHyperparameter Optimization Quantum NLP
NPC Worldwide, Bloomington, IN, USA · Department of Linguistics, Indiana University, Bloomington, IN, USA
An Exploratory Evaluation of LLM-Assisted Rewriting of Moderate-Complexity Financial Sentences for DisCoCat-Based Sentiment Analysis
Aug 7, 2026Brian Llinas, Nikos ChrisochoidesFinancial Sentiment Analysis Quantum NLP
Department of Computer Science Old Dominion University Norfolk, VA, USA
Enabling Quantum Natural Language Processing for Hindi Language
Dec 2, 2023Naman Srivastava, Gaurang Belekar, Gautami Sanjay Naik +2Quantum NLP Quantum Machine Learning
IIIT Dharwad Dharwad, India

Oct 25, 2026J/K move · Enter open · S save

Wave Is All You Need: A Quantum Language Model Based on Fully Connected Quantum Boltzmann Machine

Jun Liu

Language Modeling Quantum NLP Quantum Machine Learning Text Generation

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This work proposes a self-attention mechanism based on the fully connected quantum Boltzmann machine (FC-QBM), and further constructs a fully connected quantum Boltzmann machine language model (FC-QBM-LM) using the mechanism as the core engine. By performing unitary evolution on semantic quantum states, the mechanism implicitly implements positional encoding and self-attention computation, eliminating the need to decompose continuous semantic streams into discrete matrices for explicit matrix multiplication, with the measurement results naturally satisfying the normalization condition. Specifically, this work rigorously derives the computational principle of the self-attention mechanism based on FC-QBM, and demonstrates that this mechanism is mathematically equivalent to the classical self-attention mechanism. The mathematical principles governing the training and generation of FC-QBM-LM are thoroughly derived, and the two corresponding algorithms are subsequently developed. An 8-qubit FC-QBM-LM is finally constructed and trained on the corpus of Tang poetry. Under the 8-qubit setting, the quantum layer implements the entire positional encoding and self-attention computation pipeline with only 44 parameters. In the noiseless scenario, the model exhibits favorable convergence. Furthermore, the quantum circuit proposed in this work, which terminates with Y-axis rotation gates, achieves better convergence than the counterpart terminating with X-axis rotation gates. Under the small-sample regime and across eight distinct noise intensity levels, the model demonstrates strong noise robustness, retaining over 99% of its noiseless convergence performance. Experiments on five-character quatrain generation reveal that the model preliminarily exhibits three core capabilities: associative and divergent thinking, content generation across imagery and human-aligned word ordering.