Research

• Structural decision-making in LLMs1 paper raises it · 3 address it

  Current LLMs lack native support for decision problems with structural requirements like null-awareness, permutation invariance, and scalability.

  • Jeva: System One Models from First Principlesraises · addresses
  • LEV: Thinking Fast and Deep with Looped Decision Modelsaddresses
  • SearchJev: A Fast and Calibrated System-1 Model for Search Agentsaddresses
• Adaptive computation for decision models1 paper raises it · 1 addresses it

  Fixed-depth decision models waste computation on easy questions and cannot scale depth dynamically.

  • LEV: Thinking Fast and Deep with Looped Decision Modelsraises · addresses
• Reliable no-thinking behavior in LLMs1 paper raises it · 1 addresses it

  LLMs often ignore or misinterpret no-thinking instructions, leading to unwanted reasoning traces.

  • Thinking Inertia: LLMs Keep Thinking When Told Not Toraises · addresses
• Memory consolidation in context-augmented LLMs1 paper raises it · 1 addresses it

  Gains from context are lost after its removal, and models struggle to retain learned knowledge without forgetting.

  • Cortex: Consolidating Context into Parametric Memoryraises · addresses
• Sustaining self-evolution in reasoning models1 paper raises it · 1 addresses it

  Self-generated training data degrades over rounds due to invalid or repetitive questions, causing performance collapse.

  • Questioning the Questions: Sustaining Self-Evolution in Reasoning Modelsraises · addresses

Named by an AI from these papers' abstracts.