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Interpreting and learning voice commands with a Large Language Model for a robot system

2024-07-31 · Stanislau Stankevich, Wojciech Dudek

Robots are increasingly common in industry and daily life, such as in nursing homes where they can assist staff. A key challenge is developing intuitive interfaces for easy communication. The use of Large Language Models (LLMs) like GPT-4 has enhanced robot capabilities, allowing for real-time interaction and decision-making. This integration improves robots' adaptability and functionality. This project focuses on merging LLMs with databases to improve decision-making and enable knowledge acquisition for request interpretation problems.

📄 PDF Abstract BibTeX arXiv:2407.21512

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Decision MakingLanguage ModelingLanguage ModellingLarge Language Model

Methods 이 논문이 사용한 방법론

Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.
Layer Normalization Unlike batch normalization, Layer Normalization directly estimates the normalization statistics from the summed inputs…
Multi-Head Attention 설명 없음
Attention 설명 없음
Position-Wise Feed-Forward Layer 설명 없음
Adam 설명 없음
BPE Byte Pair Encoding, or BPE, is a subword segmentation algorithm that encodes rare and unknown words as sequences of subword units. The intuition is that various word…
Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…

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