EnigmaForge: The Question Is Hidden in the Story
Daniel Eisner
Abstract
Most benchmarks hand the model a question. EnigmaForge hands it a stack of old documents and no question at all. Buried in the letters, receipts, and logbook margins is a small logic puzzle whose solution is unique - proved by a SAT solver at generation time, with an ablation certificate showing every clue is load-bearing. Because instances are generated rather than collected, the corpus renews forever. The headline measure is intuition: task success when handed only the story, with world reconstruction as the secondary axis. Twenty-five frontier models ran over 600 instances (17,400 scored records) under three matched conditions. Intuition reshuffles the leaderboard: a 22x spread where fact recovery spans 1.6x, the second-best fact-recoverer ranks fourteenth, one model is indifferent to being told the question, and another is significantly better without it. Several models were blocked by their own content filters before reaching the puzzle - any benchmark scoring refusals as failure is quietly measuring filter behavior.
Create a lesson
Related papers
GRASP: Generating, Revising, and Assessing for Strategic Planning with Agentic AI
Arunabh Srivastava, Mohammad A., Khojastepour et al.
Screen Before You Serve: Simulation for Production Customer Experience AI Agents at 140M Scale
Edesio Alcoba, Kevin Rossell, Aman Gupta et al.
HEXIS: Compiling Skills into Extended Finite State Machines
Minghao LI
PrivDrift: Auditing User-Secret Leakage Under Topic Drift in Active LLM Conversations
Luciano Maldonado
Self-Play Pretraining with Zero Data
Aditya Cowsik, Kfir Dolev, Michael Y. Li et al.
SciWalker: Synthesizing Scientific Coding Problems with Operator Graphs and Execution Feedback
Chenxi Li, Wenxuan Zeng, Yun Luo et al.