OptiMind: Teaching LLMs to Think Like Optimization Experts
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2509.22979
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Published
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[papers] Gameplay Optimization
Research papers that may contribute to a broader approach to teaching machines how to play complex strategy games beyond just Chess.
Note Could be very important for understanding how to get the most value out of every line of play.
LFM2 Technical Report
Paper • 2511.23404 • Published • 50Note Tiny models that make on-device at the edge possible. Key bases for distillation.
Zero-Overhead Introspection for Adaptive Test-Time Compute
Paper • 2512.01457 • Published • 1Note Promising for reducing the amount of needless future-looking simulations.
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Confidence Estimation for LLMs in Multi-turn Interactions
Paper • 2601.02179 • Published • 16 -
Can LLMs Predict Their Own Failures? Self-Awareness via Internal Circuits
Paper • 2512.20578 • Published • 83 -
The Poisoned Apple Effect: Strategic Manipulation of Mediated Markets via Technology Expansion of AI Agents
Paper • 2601.11496 • Published • 45 -
GLEE: A Unified Framework and Benchmark for Language-based Economic Environments
Paper • 2410.05254 • Published • 85 -
EpiCaR: Knowing What You Don't Know Matters for Better Reasoning in LLMs
Paper • 2601.06786 • Published • 6 -
ArenaRL: Scaling RL for Open-Ended Agents via Tournament-based Relative Ranking
Paper • 2601.06487 • Published • 50 -
AT^2PO: Agentic Turn-based Policy Optimization via Tree Search
Paper • 2601.04767 • Published • 28 -
Entropy-Adaptive Fine-Tuning: Resolving Confident Conflicts to Mitigate Forgetting
Paper • 2601.02151 • Published • 102