World models in AI: predictive models of environment dynamics for planning and reasoning, including JEPA, latent-space architectures, and the spectrum from token prediction to state-based simulation
| Name | Categories | Topics | References | Credibility | CreateDate | UpdateDate | Title | RelatedNotes | NavigationOrder | Eleventy | TemplateEngineOverride | Created |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 20260630_from_tokens_to_states_llms_world_models | paper_analysis | llm, reasoning, world_model, memory_mechanism, agent_architecture | jepa, othello_gpt | 100 | From Tokens to States: LLMs as a Special Case of World Models and the Continuous Path Beyond | memory_os_of_ai_agent, rl_long_horizon_reasoning_llm_expressiveness | [object Object] | [object Object] | md | |||
| 20260703_self_evolving_world_models_llm_agent_planning | paper_analysis | world_model, self_evolving_agents, memory_mechanism, embodied_ai, reasoning | nus, alfworld, deepmind | 100 | Self-Evolving World Models for LLM Agent Planning | from_tokens_to_states_llms_world_models, world_models_in_pieces_structural_certification, memory_r1_enhancing_llm_agents_manage_utilize_memories_rl, stop_comparing_llm_agents_without_disclosing_harness | [object Object] | [object Object] | md |