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Using in-context learning technology, researchers can provide a description of dodo characteristics in the prompt as a reference to guide the model in making comparisons, without needing to fine-tune the model's weights.
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10/2/2026
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VerifiedThe effectiveness of prompt engineering is rooted in the large language model's In-Context Learning capability, which enables task switching without modifying model weights.77% similarUnverifiedProviding in-context learning examples at inference time can substantially mitigate context confusion.75% similarVerifiedIn-Context Learning (ICL) refers to the ability of large language models to perform new tasks without updating weights, solely by providing examples or instructions in the input prompt; this ability was first systematically described in the GPT-3 paper.71% similarUnverified可解释性论文的贡献往往不在于提升benchmark指标，而在于增进对模型行为的理解，这本质上是认识论层面的贡献70% similarUnverifiedThe researchers propose a simple, training-free framework that enables reasoning-capable vision-language models to perform iterative search, dynamic reasoning, and evidence accumulation.70% similar
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