Tag: In-Context Learning
All the articles with the tag "In-Context Learning".
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Beyond the Last Answer: Your Reasoning Trace Uncovers More than You Think
Published: at 12:12 AM
76.38 🤔本文提出了一种通过分割大型语言模型推理轨迹为子思维并从中间状态生成多条推理路径、最终以众数聚合答案的方法，显著提高了数学推理任务的准确性（最高提升13%），并揭示了答案一致性与正确性的相关性。
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COSMOS: Predictable and Cost-Effective Adaptation of LLMs
Published: at 11:05 AM 75.99 🤔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
Published: at 12:18 AM 74.82 🤔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?
Published: at 04:30 PM 72.97 🤔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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Rethinking Invariance in In-context Learning
Published: at 11:15 AM 71.91 🤔This paper introduces Invariant In-Context Learning (InvICL), a novel ICL method that achieves permutation invariance, information non-leakage, and context interdependence using leave-one-out encoding and parallel implementation, outperforming both invariant and non-invariant baselines in generalization and performance across synthetic and real-world tasks.