Language Generation for Broad-Coverage, Explainable Cognitive Systems
This paper describes recent progress on natural language generation (NLG) for language-endowed intelligent agents (LEIAs) developed within the OntoAgent cognitive architecture. The approach draws heavily from past work on natural language understanding in this paradigm: it uses the same knowledge bases, theory of computational linguistics, agent architecture, and methodology of developing broad-coverage capabilities over time while still supporting near-term applications.
Code (0)
등록된 구현이 없습니다.
Tasks
Natural Language UnderstandingText GenerationSimilar Papers 제목 키워드 기반
DEE: Dual-stage Explainable Evaluation Method for Text Generation
Automatic methods for evaluating machine-generated texts hold significant importance due to the expanding applications of generative systems. Conventional methods tend to grapple with a lack of explainability, issuing a …
DiagnosticHallucinationText GenerationOPTIMUS: Predicting Multivariate Outcomes in Alzheimer's Disease Using Multi-modal Data amidst Missing Values
Alzheimer's disease, a neurodegenerative disorder, is associated with neural, genetic, and proteomic factors while affecting multiple cognitive and behavioral faculties. Traditional AD prediction largely focuses on univa…
Disease PredictionImputationMissing ValuesPredictionMade for Each Other: Broad-coverage Semantic Structures Meet Preposition Supersenses
Universal Conceptual Cognitive Annotation (UCCA; Abend and Rappoport, 2013) is a typologically-informed, broad-coverage semantic annotation scheme that describes coarse-grained predicate-argument structure but currently …
Cognition Chain for Explainable Psychological Stress Detection on Social Media
Stress is a pervasive global health issue that can lead to severe mental health problems. Early detection offers timely intervention and prevention of stress-related disorders. The current early detection models perform …
Dataset GenerationTokensome: Towards a Genetic Vision-Language GPT for Explainable and Cognitive Karyotyping
Automatic karyotype analysis is often defined as a visual perception task focused solely on chromosomal object-level modeling. This definition has led most existing methods to overlook componential and holistic informati…
Anomaly DetectionDecision MakingKnowledge GraphsLanguage Modeling+1