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.
arXiv preprint arXiv:2206.06888 , year=
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RealBench is a new repo-level code generation benchmark that adds UML diagrams to natural language specs, showing LLMs struggle more at full repositories, create modules with errors, and perform best with whole-repo generation on small projects versus module-by-module on complex ones.
DPOP is a new loss function that prevents DPO from lowering preferred response likelihoods and outperforms standard DPO on diverse datasets, MT-Bench, and enables Smaug-72B to exceed 80% on the Open LLM Leaderboard.
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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RealBench: A Repo-Level Code Generation Benchmark Aligned with Real-World Software Development Practices
RealBench is a new repo-level code generation benchmark that adds UML diagrams to natural language specs, showing LLMs struggle more at full repositories, create modules with errors, and perform best with whole-repo generation on small projects versus module-by-module on complex ones.
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Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive
DPOP is a new loss function that prevents DPO from lowering preferred response likelihoods and outperforms standard DPO on diverse datasets, MT-Bench, and enables Smaug-72B to exceed 80% on the Open LLM Leaderboard.