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Similar to other text generation tasks, language models can produce entire conversations by utilizing the preceding conversational context. This capability allows for the creation of dialogues that are coherent and contextually appropriate.

Conversation Generation from Context

A prompt for a conversation completion task can be structured by first setting the context and then providing a clear instruction. For example, a model can be told, 'You are provided with a conversation between a tourist and a taxi driver,' to establish the scenario, followed by the direct command, 'Please complete the conversation.'

Example Prompt for Conversation Completion

Review the conversation transcript below. Identify the specific point where the chatbot fails to use the conversational context effectively and explain why this response is inappropriate.

Analyzing a Chatbot's Conversational Failure

A user provides the following prompt to a language model: 'I'm looking for a good book to read on my vacation. I really enjoy historical fiction, but nothing too heavy.' The model responds with: 'The Theory of Relativity by Albert Einstein is a seminal work in physics.' In 2-3 sentences, explain why the model's response fails to utilize the conversational context effectively. Then, provide one example of a more appropriate response.

Evaluating Contextual Coherence in a Language Model's Response

A language model is given the following two lines of a conversation and is tasked with generating the next line for Speaker A.

Speaker A: "I finally finished assembling that new bookshelf, but I have a dozen screws left over."
Speaker B: "That happens to me all the time. I just toss them in a drawer and hope for the best."

Which of the following responses for Speaker A best demonstrates an effective use of the preceding conversational context to generate a coherent continuation?

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