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    Dissecting In-Context Learning in Large Language Models: Distinguishing Task Recognition from Task Learning

    AI Papers
    New study illuminates the dual mechanisms of in-context learning, suggesting a differentiation between task recognition and task learning capabilities in large language models. The mechanisms...

    Unlocking the Potential of Large Language Models for Formal Theorem Proving

    AI Papers
    Exploring Failure Cases to Enhance Performance and Accessibility of AI-driven Proof Automation Large language models, such as GPT-3.5 Turbo and GPT-4, have the potential to...

    The Unfaithful Nature of Chain-of-Thought Explanations in Large Language Models

    AI Papers
    A Study Reveals How Misleading Explanations Can Increase Trust in AI Systems Without Ensuring Their Safety Chain-of-thought (CoT) explanations produced by large language models (LLMs)...

    Vcc: A Breakthrough in Scaling Transformers to Handle Ultra-Long Sequences

    AI Papers
    Prioritizing Important Tokens to Achieve Over 3x Efficiency Improvement for 4K to 128K Token Lengths Vcc (VIP-token centric compression) tackles the challenge of efficiently processing...