Papers with Claude 2

2 papers
Enhancing Perception: Refining Explanations of News Claims with LLM Conversations (2024.findings-naacl)

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Challenge: a new framework for Large Language Models (LLMs) streamlines the task of crafting explanations for fake news . a study compared refinement conversations between human and LLMs to enhance the effectiveness of LLM explanations .
Approach: They propose a framework for Large Language Models to streamline the task of crafting fake news explanations.
Outcome: The proposed framework enhances the process of crafting explanations for fake news claims through conversational refinement.
Teaching Language Models to Self-Improve by Learning from Language Feedback (2024.findings-acl)

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Challenge: Recent advances in Large Language Models (LLMs) generate content that can be untruthful or harmful.
Approach: They propose a method that leverages model feedback for alignment . they use a base language model to generate initial responses, critiqued and refined .
Outcome: The proposed method outperforms strong baselines across diverse tasks and model sizes.

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