Tag: In-Context Learning
All the articles with the tag "In-Context Learning".
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COSMOS: Predictable and Cost-Effective Adaptation of LLMs
COSMOS introduces a cost-effective framework to predict performance and cost of LLM adaptation strategies like QLoRA fine-tuning and retrieval-augmented ICL, achieving high accuracy (1.09% MAE) and reducing computational costs by 92.72% across eight diverse benchmarks.
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Racing Thoughts: Explaining Contextualization Errors in Large Language Models
本文提出‘LLM Race Conditions Hypothesis’解释大型语言模型的上下文化错误,通过机械可解释性技术验证了关键窗口和上下文化顺序对模型性能的影响,并探索了推理时干预措施来缓解问题。
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Does Knowledge Distillation Matter for Large Language Model based Bundle Generation?
本文首次系统探索知识蒸馏技术在基于大语言模型的捆绑生成任务中的应用,通过提出一个全面的 KD 框架和实验验证,证明了在减少计算需求的同时能保持甚至提升性能。
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The dynamic interplay between in-context and in-weight learning in humans and neural networks
本文通过神经网络中上下文学习(ICL)与权重学习(IWL)的动态交互,统一解释了人类学习中的组合性泛化、课程效应及灵活性与保留性权衡,为认知科学双过程理论提供了新视角。
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Prompt-Based Cost-Effective Evaluation and Operation of ChatGPT as a Computer Programming Teaching Assistant
本文通过设计基于ICL和CoT的提示模板,实现了ChatGPT在编程教育中的成本效益评估和操作,显著降低了手动评估需求并提升了反馈的结构化分析。