Papers with decompose tasks

1 papers
Data-Centric Perspectives on Agentic Retrieval-Augmented Generation: A Survey (2026.findings-acl)

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Challenge: Large Language Models (LLMs) excel at natural language understanding and generation, yet rely on static pre-training data.
Approach: They propose to augment Large Language Models with external retrieval to ground model outputs . traditional RAG is constrained by a fixed retrieve-then-generate routine . authors aim to guide creation of high-quality datasets for next generation of adaptive LLM agents .
Outcome: The proposed model can decompose tasks, issue exploratory queries, and refine evidence through iterative retrieval.

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