From Tokens to States: LLMs as a Special Case of World Models and the Continuous Path Beyond
arXiv:2606.28127v1 Announce Type: cross Abstract: The AI community has framed the relationship between large language models (LLMs) and world models as a dichotomy: LLMs predict tokens; world models simulate reality. Yann LeCun argues in 2022 that reaching general intelligence requires abandoning autoregressive token prediction in favour of latent-space architectures. This framing is unnecessarily binary. Two claims will be defended. First, LLMs are a degenerate special case of world models: the state space is the set of all token sequences, the only action is appending one token, and world mo
The paper directly addresses a prominent debate within the AI community regarding the nature of LLMs versus world models, proposing a unifying perspective.
This recharacterization could significantly influence future AI research directions, shifting focus from pure token prediction to more state-based reasoning, blurring the lines between current LLMs and more general AI architectures.
The perceived fundamental limitations of LLMs as mere 'token predictors' are challenged, opening avenues for developing them into more sophisticated 'world model' like systems via architectural evolution.
- · AI researchers in generative models
- · Developers of foundational AI models
- · Companies investing in multimodal AI
- · Long-term AI development
- · Strict proponents of a dichotomy between LLMs and world models
- · Companies solely focused on incremental token prediction improvements
This theoretical shift could encourage the development of new architectures that explicitly incorporate notions of state and action within LLM frameworks.
Advanced LLMs might become more capable of complex reasoning, planning, and interaction with dynamic environments, accelerating the development of more general AI systems.
The acceleration of AI capabilities could further intensify the AI agents race, leading to more autonomous and sophisticated systems faster than anticipated under the previous dichotomy.
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Read at arXiv cs.LG