Copertina

QCSE: A Pretrained Quantum Context-Sensitive Word Embedding for Natural Language Processing

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Varmantchaonala, Charles M., Götting, Niclas, Schütte, Nils-Erik, Fendji, Jean Louis E. K., Gies, Christopher
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Expressivity Limits of Quantum Reservoir Computing
di: Schütte, Nils-Erik, et al.
Pubblicazione: (2025)

Fulfulde–French and Fulfulde–English Parallel Corpus (Adamawa Fulani) for Machine Translation
di: Varmantchaonala Moudina, Charles, et al.
Pubblicazione: (2026)

Effective long-range attraction of moiré excitons under the influence of atomic reconstructions and anisotropic screening
di: Schütte, Nils-Erik, et al.
Pubblicazione: (2026)

Memory-Nonlinearity Trade-off across Quantum Reservoir Computing Frameworks
di: Čindrak, Saud, et al.
Pubblicazione: (2026)

Connection between memory performance and optical absorption in quantum reservoir computing
di: Götting, Niclas, et al.
Pubblicazione: (2025)

Output Embedding Centering for Stable LLM Pretraining
di: Stollenwerk, Felix, et al.
Pubblicazione: (2026)

Tracing the Evolution of Word Embedding Techniques in Natural Language Processing
di: Nguyen, Minh Anh, et al.
Pubblicazione: (2026)

Multi-Relational Hyperbolic Word Embeddings from Natural Language Definitions
di: Valentino, Marco, et al.
Pubblicazione: (2023)

A Tutorial on the Pretrain-Finetune Paradigm for Natural Language Processing
di: Wang, Yu, et al.
Pubblicazione: (2024)

Extending the Context of Pretrained LLMs by Dropping Their Positional Embeddings
di: Gelberg, Yoav, et al.
Pubblicazione: (2025)

From Community Network to Community Data: Towards Combining Data Pool and Data Cooperative for Data Justice in Rural Areas
di: Ebongue, Jean Louis Fendji Kedieng
Pubblicazione: (2025)

Statistical Uncertainty in Word Embeddings: GloVe-V
di: Vallebueno, Andrea, et al.
Pubblicazione: (2024)

Automated Detection and Analysis of Power Words in Persuasive Text Using Natural Language Processing
di: Garje, Sahil
Pubblicazione: (2024)

Learning Complex Word Embeddings in Classical and Quantum Spaces
di: Harvey, Carys, et al.
Pubblicazione: (2024)

Diffusion-Pretrained Dense and Contextual Embeddings
di: Eslami, Sedigheh, et al.
Pubblicazione: (2026)

Quantum Natural Language Processing
di: Widdows, Dominic, et al.
Pubblicazione: (2024)

Word Embeddings Are Steers for Language Models
di: Han, Chi, et al.
Pubblicazione: (2023)

Guided Perturbation Sensitivity (GPS): Detecting Adversarial Text via Embedding Stability and Word Importance
di: Tuck, Bryan E., et al.
Pubblicazione: (2025)

Efficient Domain-adaptive Continual Pretraining for the Process Industry in the German Language
di: Zhukova, Anastasia, et al.
Pubblicazione: (2025)

Fairness Certification for Natural Language Processing and Large Language Models
di: Freiberger, Vincent, et al.
Pubblicazione: (2024)

One Word Is Not Enough: Simple Prompts Improve Word Embeddings
di: Ranjan, Rajeev
Pubblicazione: (2025)

Near-Term Advances in Quantum Natural Language Processing
di: Widdows, Dominic, et al.
Pubblicazione: (2022)

The BIAS Detection Framework: Bias Detection in Word Embeddings and Language Models for European Languages
di: Puttick, Alexandre, et al.
Pubblicazione: (2024)

Explainable Natural Language Processing for Corporate Sustainability Analysis
di: Ong, Keane, et al.
Pubblicazione: (2024)

From Word Vectors to Multimodal Embeddings: Techniques, Applications, and Future Directions For Large Language Models
di: Zhang, Charles, et al.
Pubblicazione: (2024)

ViConBERT: Context-Gloss Aligned Vietnamese Word Embedding for Polysemous and Sense-Aware Representations
di: Huynh, Khang T., et al.
Pubblicazione: (2025)

On The Role of Pretrained Language Models in General-Purpose Text Embeddings: A Survey
di: Zhang, Meishan, et al.
Pubblicazione: (2025)

A Critical Reflection and Forward Perspective on Empathy and Natural Language Processing
di: Lahnala, Allison, et al.
Pubblicazione: (2022)

MuCPT: Music-related Natural Language Model Continued Pretraining
di: Tian, Kai, et al.
Pubblicazione: (2025)

Revisiting Word Embeddings in the LLM Era
di: Mahajan, Yash, et al.
Pubblicazione: (2025)

Evaluating Metrics for Bias in Word Embeddings
di: Schröder, Sarah, et al.
Pubblicazione: (2021)

Enhancing Cross-lingual Sentence Embedding for Low-resource Languages with Word Alignment
di: Miao, Zhongtao, et al.
Pubblicazione: (2024)

Processing Natural Language on Embedded Devices: How Well Do Transformer Models Perform?
di: Sarkar, Souvika, et al.
Pubblicazione: (2023)

Resolving Word Vagueness with Scenario-guided Adapter for Natural Language Inference
di: Liu, Yonghao, et al.
Pubblicazione: (2024)

Exploring Interpretability of Independent Components of Word Embeddings with Automated Word Intruder Test
di: Musil, Tomáš, et al.
Pubblicazione: (2022)

Is Less More? Quality, Quantity and Context in Idiom Processing with Natural Language Models
di: Knietaite, Agne, et al.
Pubblicazione: (2024)

Register Always Matters: Analysis of LLM Pretraining Data Through the Lens of Language Variation
di: Myntti, Amanda, et al.
Pubblicazione: (2025)

Natural Language Processing Methods for the Study of Protein-Ligand Interactions
di: Michels, James, et al.
Pubblicazione: (2024)

Using Context to Improve Word Segmentation
di: Hu, Stephanie, et al.
Pubblicazione: (2025)

Context-level Language Modeling by Learning Predictive Context Embeddings
di: Dai, Beiya, et al.
Pubblicazione: (2025)