Towards Interpretative Language Models: A Complex Adaptive System Framework with Six Interaction Variables to Capture Implicit, Intrinsic, and Artistic Meaning
AbstrakÂ
We propose a novel theoretical framework---CAS-6 (Complex Adaptive System with Six Variables)---designed to enhance Large Language Models (LLMs) by enabling them to capture not only probabilistic and denotative meanings, but also implicit, intrinsic, and artistic dimensions of language. The framework introduces six variables: interaction level, interaction pattern, interaction probability, interaction weight, interaction stability, and interaction output. We demonstrate the framework using triadic word sets such as "air", "mata", and "buaya", showing how permutations across interaction levels generate diverse semantic outputs---from literal to metaphorical. Unlike current LLMs that rely predominantly on statistical co-occurrence, CAS-6 models meaning as an emergent property of multi-layered semantic interplay. This work lays the groundwork for a new generation of interpretative, culturally-sensitive, and creatively adaptive AI language systems.
1. Introduction
1.1. Limitations of Probabilistic Approaches in Contemporary Language Models
Large Language Models (LLMs) such as GPT, PaLM, and LLaMA have demonstrated remarkable capabilities in generating coherent and contextually appropriate natural language texts. These models are primarily driven by probabilistic mechanisms---namely, the estimation of the most likely next token in a sequence based on massive corpora of linguistic data. While this architecture excels at capturing syntactic regularities and frequent co-occurrences, it remains limited in its ability to understand or generate nuanced language that conveys implicit, connotative, or artistic meaning.
This limitation is not merely aesthetic; it reflects a deeper issue in the representation of meaning itself. Language is not reducible to statistical regularities alone. Poetic constructs, idiomatic expressions, irony, metaphor, cultural subtext, and emotional resonance often operate through rare or unexpected combinations of words---precisely those which fall outside the bounds of high-probability patterns. For instance, while the phrase "crocodile tears" is a well-known idiom denoting false sympathy, its interpretation cannot be inferred solely from the individual meanings of "crocodile" and "tears", nor from the frequency with which these terms co-occur.
In other words, the dominant statistical paradigm in current LLMs lacks an inherent mechanism to capture inter-word dynamics that generate emergent meaning beyond local token prediction. As a consequence, such models often default to superficial fluency without genuine semantic depth or creativity, especially when tasked with interpreting figurative, emotional, or symbolic language.
This paper proposes an alternative framework---CAS-6V (Complex Adaptive System with 6 Variables)---designed to model multi-word meaning as an emergent property of structured interaction between linguistic elements. By introducing six interconnected variables (Interaction Level, Interaction Pattern, Interaction Probability, Interaction Weight, Interaction Stability, and Interaction Output), the CAS-6V framework aims to capture not only the probabilistic relationships among words but also their potential to form nonlinear, context-sensitive, and aesthetically meaningful structures. Our approach treats language understanding as a dynamic and adaptive system, not merely a sequential optimization problem.
1.2. The Importance of Implicit Meaning, Cultural Nuance, and Aesthetic Dimensions in Language Understanding
Natural language is not merely a medium for information transmission; it is a complex, culturally-situated system for encoding thought, emotion, identity, and aesthetic experience. In human communication, a significant proportion of meaning is conveyed not through explicit statements, but through implicature, connotation, metaphor, symbolism, and cultural reference. These phenomena are not noise or ornament---they are central to how language functions as a tool for nuanced human cognition and intersubjectivity.
