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Author

Ramesh Venkatachalapathy

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Conference Aug 2026

Retrieval-Augmented Reasoning for Knowledge-Intensive AI Systems Using Dynamic Evidence Acquisition

Retrieval-Augmented Generation (RAG) improves factual grounding by adding external evidence to large language model prompts, but conventional pipelines usually retrieve evidence only once before generation. This static design is limited for knowledge-intensive tasks in which intermediate reasoning steps expose new evid...

Ramesh Venkatachalapathy · 0 citations
Conference Jul 2026

Designing Reliable LLM Systems for AI-Assisted Engineering Education

Large Language Models (LLMs) are increasingly used in AI-assisted engineering education, enterprise learning, technical knowledge support, and software-development workflows. However, static retrieval-augmented generation (RAG) pipelines retrieve external context for every query, which can increase latency, token cost,...

Ramesh Venkatachalapathy · 0 citations

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