SR4CS is a new open collection of 1,212 CS systematic reviews with expert Boolean queries and references to support reproducible automation research.
System for systematic literature review using multiple ai agents: Concept and an empirical evaluation
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The Novelty-Aware Research Agent layers query analysis, ReAct retrieval, ranking, schema-guided extraction, three-pass comparison, and answer generation on RAG to produce structured comparison artifacts that standard RAG cannot.
A two-layer certification framework decouples knowledge validity from human authorship to accommodate AI-enabled research in existing publication systems.
CodePori is a multi-agent LLM system for code generation whose participant evaluation identifies practical challenges like memory limits and hallucinations missed by binary benchmarks.
citing papers explorer
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A Collection of Systematic Reviews in Computer Science
SR4CS is a new open collection of 1,212 CS systematic reviews with expert Boolean queries and references to support reproducible automation research.
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Novelty-Aware Agentic Retrieval: Comparing Research Contributions Through Structured Multi-Step Reasoning
The Novelty-Aware Research Agent layers query analysis, ReAct retrieval, ranking, schema-guided extraction, three-pass comparison, and answer generation on RAG to produce structured comparison artifacts that standard RAG cannot.
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Rethinking Publication: A Certification Framework for AI-Enabled Research
A two-layer certification framework decouples knowledge validity from human authorship to accommodate AI-enabled research in existing publication systems.
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CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technology
CodePori is a multi-agent LLM system for code generation whose participant evaluation identifies practical challenges like memory limits and hallucinations missed by binary benchmarks.