CAPRA is a multi-agent LLM system with evidence anchoring and consistency checking that analyzes software architecture deliverables and meets 88.8% of an eight-criterion evaluation on 10 student reports.
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3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
Survey of RLM adoption in 28 disciplines reveals maturity disparities via a new assessment framework, with focus on development, evaluation, and public resources.
LectūraAgents proposes a hierarchical multi-agent system with adaptive embodied teaching and the TASA algorithm for personalized AI-assisted learning, reporting gains in content quality, teaching actions, and personalization over baselines via expert educator validation on sample courses.
citing papers explorer
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CAPRA: Scaling Feedback on Software Architecture Deliverables with a Multi-Agent LLM System
CAPRA is a multi-agent LLM system with evidence anchoring and consistency checking that analyzes software architecture deliverables and meets 88.8% of an eight-criterion evaluation on 10 student reports.
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Reasoning4Sciences: Bridging Reasoning Language Models to All Scientific Branches
Survey of RLM adoption in 28 disciplines reveals maturity disparities via a new assessment framework, with focus on development, evaluation, and public resources.
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Lect\=uraAgents: A Multi-Agent Framework for Adaptive Personalized AI-Assisted Learning and Embodied Teaching
LectūraAgents proposes a hierarchical multi-agent system with adaptive embodied teaching and the TASA algorithm for personalized AI-assisted learning, reporting gains in content quality, teaching actions, and personalization over baselines via expert educator validation on sample courses.