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RAG

Multi-task retriever fine-tuning for domain-specific and efficient RAG
Retrieval-Augmented Generation (RAG) has become ubiquitous when deploying Large Language Models (LLMs), as it can address typical …
Generating a Low-code Complete Workflow via Task Decomposition and RAG
AI technologies are moving rapidly from research to production. With the popularity of Foundation Models (FMs) that generate text, …
XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference
In-context learning (ICL) approaches typically leverage prompting to condition decoder-only language model generation on reference …
Reducing hallucination in structured outputs via Retrieval-Augmented Generation
A common and fundamental limitation of Generative AI (GenAI) is its propensity to hallucinate. While large language models (LLM) have …