Papers with gpt-4-turbo

1 papers
CantTalkAboutThis: Aligning Language Models to Stay on Topic in Dialogues (2024.findings-emnlp)

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Challenge: Recent advances in instruction-tuning datasets focus on specific tasks like mathematical or logical reasoning.
Approach: They propose to use synthetic dialogues to help language models remain focused on the subject at hand during task-oriented interactions.
Outcome: The proposed dataset improves language models' ability to maintain topical coherence compared to general-purpose instruction-tuned LLMs like gpt-4-turbo and Mixtral-Instruct.

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