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Large Language Models (LLMs) have demonstrated their strong ability to assist people and show "sparks of intelligence". However, several open challenges hinder their wider application: such as concerns over privacy, tendencies to produce hallucinations, and difficulties in handling long contexts. In this work, we address those challenges by introducing the Retrieval-Augmented Thought Process (RATP). Given access to external knowledge, RATP formulates the thought generation of LLMs as a multiple-step decision process. To optimize such a thought process, RATP leverages Monte-Carlo Tree Search, and learns a Q-value estimator that permits cost-efficient inference. In addressing the task of question-answering with private data, where ethical and security concerns limit LLM training methods, RATP achieves a 50% improvement over existing in-context retrieval-augmented language models.🗓️ Mark your calendar from March 30, 2024 to February 28, 2024 at Terminal West. Thought Process is a celebration of passion, innovation, and community. Embrace the opportunity to explore the world of Other Concerts in a dynamic setting in , . Reserve your spot now for tickets starting at just 30.00 🎟️.
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Terminal West, 887 West Marietta, Atlanta, GA 30318, United States
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