WO2025099541 - INTEGRATION OF MACHINE LEARNING MODELS WITH DIALECTICAL LOGIC FRAMEWORKS
National phase entry is expected:
Publication Number
WO/2025/099541
Publication Date
15.05.2025
International Application No.
PCT/IB2024/060738
International Filing Date
31.10.2024
Title **
[English]
INTEGRATION OF MACHINE LEARNING MODELS WITH DIALECTICAL LOGIC FRAMEWORKS
[French]
INTÉGRATION DE MODÈLES D'APPRENTISSAGE AUTOMATIQUE AVEC DES STRUCTURES LOGIQUES DIALECTIQUES
Applicants **
PETRAUSKAS, Alanas
Inventors
PETRAUSKAS, Alanas
Priority Data
63/598,074
11.11.2023
US
18/631,009
09.04.2024
US
18/677,875
30.05.2024
US
18/929,555
28.10.2024
US
Application details
| Total Number of Claims/PCT | * |
| Number of Independent Claims | * |
| Number of Priorities | * |
| Number of Multi-Dependent Claims | * |
| Number of Drawings | * |
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| Pages of Specification | * |
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International Searching Authority |
EPO
* |
| Recordal of a Change of the Applicant's Name/Address |
Change of Applicant's Name and Address
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| Type of Assignment |
The Standard Agent's Assignment
* |
| Applicant's Legal Status |
Natural Person
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| * | |
| * | |
| * | |
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| Entry into National Phase under |
Chapter I
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| Patent Delivery |
Send the Letters Patent by Courier
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| Translation |
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Quotation for National Phase entry
| Country | Stages | Total | |
|---|---|---|---|
| China | Filing, Examination, Granting | 4633 | |
| EPO | Filing, Examination, Granting | 33898 | |
| Japan | Filing, Examination, Granting | 3663 | |
| South Korea | Filing, Examination, Granting | 5248 | |
| USA | Filing, Examination, Granting | 22240 |
Total:
69,682
The term for entry into the National Phase has expired. This quotation is for informational purposes only
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Abstract[English]
This disclosure relates to techniques for executing dialectical analyses using large language models and/or other types of deep learning models. In certain embodiments, the dialectic logic engine executes programmatic processes to derive various types of parameters through communication exchanges with generative language models. In certain embodiments, these parameters can be organized in mapping schemas with defined relationships and circular structures, and the schemas can be leveraged to generate various types of outputs, such as dialectic wheels, tables, and natural language explanations. The dialectic logic engine also can enforce constraint conditions and/or eliminate bias while handling both ambiguous and unambiguous causal relationships. A dialectic training system also is disclosed that can train and/or fine-tune language models to extend their capabilities in dialectic domains.[French]
La présente divulgation concerne des techniques de mise en œuvre d'analyses dialectiques à l'aide de grands modèles de langage et/ou d'autres types de modèles d'apprentissage profond. Dans certains modes de réalisation, le moteur logique dialectique exécute des processus programmatiques pour obtenir divers types de paramètres par l'intermédiaire d'échanges de communication avec des modèles de langage génératif. Dans certains modes de réalisation, ces paramètres peuvent être organisés en schémas de mappage avec des relations définies et des structures circulaires, et les schémas peuvent être exploités pour générer divers types de sorties, telles que des roues dialectiques, des tables et des explications en langage naturel. Le moteur logique dialectique peut également appliquer des conditions de contrainte et/ou éliminer un biais tout en prenant à la fois en charge des relations causales ambiguës et non ambiguës. Est également divulgué un système d'entraînement dialectique qui peut entraîner et/ou affiner des modèles de langage pour étendre leurs capacités dans des domaines dialectiques.