ARIADNE combines blackboard architecture with MCTS to coordinate strategy, code, test, evaluation, and repair stages, yielding higher Pass@1 scores than prior LLM baselines on APPS, CodeContests, and related benchmarks.
In The Twelfth International Conference on Learning Representations
3 Pith papers cite this work. Polarity classification is still indexing.
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NLCO benchmark shows LLMs achieve reasonable feasibility on small natural-language CO tasks but degrade on larger instances, with set-based problems easier than graph-structured or bottleneck-objective ones.
GrandCode is the first AI system to consistently beat all human participants and place first in live Codeforces competitive programming contests.
citing papers explorer
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ARIADNE: Agentic Reward-Informed Adaptive Decision Exploration via Blackboard-Driven MCTS for Competitive Program Generation
ARIADNE combines blackboard architecture with MCTS to coordinate strategy, code, test, evaluation, and repair stages, yielding higher Pass@1 scores than prior LLM baselines on APPS, CodeContests, and related benchmarks.
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Reasoning in a Combinatorial and Constrained World: Benchmarking LLMs on Natural-Language Combinatorial Optimization
NLCO benchmark shows LLMs achieve reasonable feasibility on small natural-language CO tasks but degrade on larger instances, with set-based problems easier than graph-structured or bottleneck-objective ones.
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GrandCode: Achieving Grandmaster Level in Competitive Programming via Agentic Reinforcement Learning
GrandCode is the first AI system to consistently beat all human participants and place first in live Codeforces competitive programming contests.