LLM-based Task

An LLM-based Task is an AI-based task that makes use of an LLM model.

• Context:
  • input: LLM Prompt.
  • It can (typically) involve tasks such as LLM-based Text generation, summarization, translation, and question answering.
  • It can (often) require substantial computational resources due to the complexity of the LL model.
  • It can be used in various applications, including content creation, customer support, and data analysis.
  • It can involve training, fine-tuning, or using a pre-trained LLM to achieve the desired outcomes.
  • It can be implemented through various frameworks and platforms that support LLMs, such as OpenAI, Hugging Face, and others.
  • ...
• Example(s):
  • LLM-based Text Generation Task using an LLM to create marketing copy for a new product.
  • LLM-based Summarization Task where an LLM condenses a lengthy article into key points.
  • LLM-based Translation Task leveraging an LLM to translate a document from English to Spanish.
  • LLM-based Question Answering Task using an LLM to provide detailed responses to user queries in a knowledge base.
  • LLM-based Content Creation Task where an LLM generates blog posts based on given topics.
  • LLM-based Chatbot Interaction Task using an LLM to engage in natural language conversations with users.
  • ...
• Counter-Example(s):
  • Rule-Based Task which relies on predefined rules rather than a large language model.
  • Statistical Machine Translation (SMT) Task which uses statistical models instead of neural networks.
  • Simple Text Parsing Task which involves basic text processing without the complexity of an LLM.
  • Traditional Machine Learning Task that employs algorithms like decision trees or SVMs instead of LLMs.
  • Hand-Crafted Dialogue System which does not use an LLM for generating responses but relies on manually written scripts.
• See: LLM-based System, ML-based Task, Natural Language Processing (NLP), Transformer Models

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• See: LLM-based System, ML-based Task.

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