TraceFix repairs LLM-generated multi-agent protocols via TLA+ counterexamples to achieve full verification on all tested tasks and higher completion rates than prompt-only baselines.
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RubberDuckBench shows top AI models score around 68% on real GitHub coding questions, rarely answer completely correctly, and hallucinate in 58% of responses on average.
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TraceFix: Repairing Agent Coordination Protocols with TLA+ Counterexamples
TraceFix repairs LLM-generated multi-agent protocols via TLA+ counterexamples to achieve full verification on all tested tasks and higher completion rates than prompt-only baselines.
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RubberDuckBench: A Benchmark for AI Coding Assistants
RubberDuckBench shows top AI models score around 68% on real GitHub coding questions, rarely answer completely correctly, and hallucinate in 58% of responses on average.