{"total":23,"rows":[{"id":"2105.09114","title":"Explainable Tsetlin Machine framework for fake news detection with credibility score assessment","created":"2021-05-19","cited_by_count":23,"area":null},{"id":"2108.07594","title":"Coalesced Multi-Output Tsetlin Machines with Clause Sharing","created":"2021-08-17","cited_by_count":22,"area":null},{"id":"2101.02547","title":"On the Convergence of Tsetlin Machines for the XOR Operator","created":"2021-01-07","cited_by_count":16,"area":null},{"id":"2104.06901","title":"Enhancing Interpretable Clauses Semantically using Pretrained Word Representation","created":"2021-04-14","cited_by_count":10,"area":null},{"id":"2105.04708","title":"Word-level Human Interpretable Scoring Mechanism for Novel Text Detection Using Tsetlin Machines","created":"2021-05-10","cited_by_count":10,"area":null},{"id":"2102.10952","title":"A Relational Tsetlin Machine with Applications to Natural Language Understanding","created":"2021-02-22","cited_by_count":8,"area":null},{"id":"2105.14506","title":"Drop Clause: Enhancing Performance, Interpretability and Robustness of the Tsetlin Machine","created":"2021-05-30","cited_by_count":7,"area":null},{"id":"2406.00704","title":"An Optimized Toolbox for Advanced Image Processing with Tsetlin Machine Composites","created":"2024-06-02","cited_by_count":7,"area":null},{"id":"2406.02648","title":"Exploring Effects of Hyperdimensional Vectors for Tsetlin Machines","created":"2024-06-04","cited_by_count":5,"area":null},{"id":"2501.18998","title":"Adversarial Attacks on AI-Generated Text Detection Models: A Token Probability-Based Approach Using Embeddings","created":"2025-01-31","cited_by_count":5,"area":null},{"id":"2407.09162","title":"Exploring State Space and Reasoning by Elimination in Tsetlin Machines","created":"2024-07-12","cited_by_count":4,"area":null},{"id":"2405.14505","title":"Explainable automatic industrial carbon footprint estimation from bank transaction classification using natural language processing","created":"2024-05-23","cited_by_count":3,"area":null},{"id":"2109.00846","title":"Self-timed Reinforcement Learning using Tsetlin Machine","created":"2021-09-02","cited_by_count":2,"area":null},{"id":"2501.19018","title":"Scalable Multi-phase Word Embedding Using Conjunctive Propositional Clauses","created":"2025-01-31","cited_by_count":2,"area":null},{"id":"2212.13634","title":"On the Equivalence of the Weighted Tsetlin Machine and the Perceptron","created":"2022-12-27","cited_by_count":1,"area":null},{"id":"2405.02375","title":"The Sparse Tsetlin Machine: Sparse Representation with Active Literals","created":"2024-05-03","cited_by_count":1,"area":null},{"id":"2303.14464","title":"Verifying Properties of Tsetlin Machines","created":"2023-03-25","cited_by_count":0,"area":null},{"id":"2305.10219","title":"Separability and Scatteredness (S&S) Ratio-Based Efficient SVM Regularization Parameter, Kernel, and Kernel Parameter Selection","created":"2023-05-17","cited_by_count":0,"area":null},{"id":"2310.17207","title":"Efficient Data Fusion using the Tsetlin Machine","created":"2023-10-26","cited_by_count":0,"area":null},{"id":"2507.19803","title":"AI-Based Clinical Rule Discovery for NMIBC Recurrence through Tsetlin Machines","created":"2025-07-26","cited_by_count":0,"area":null},{"id":"2508.06991","title":"A Comparative Study of Feature Selection in Tsetlin Machines","created":"2025-08-09","cited_by_count":0,"area":null},{"id":"2510.01906","title":"A Methodology for Transparent Logic-Based Classification Using a Multi-Task Convolutional Tsetlin Machine","created":"2025-10-02","cited_by_count":0,"area":null},{"id":"2606.19815","title":"Clusters are All You Need: Pre-Training the Tsetlin Machine with Semantic Clusters from Language Models for Interpretability","created":"2026-06-18","cited_by_count":0,"area":null}],"next_cursor":null}