ICL-Analysis-NLP-685
PublicThis evaluation explores the In-context learning (ICL) capabilities of pre-trained language models on arithmetic tasks and sentiment analysis using synthetic datasets. The goal is to use different prompting strategies—zero-shot, few-shot, and chain-of-thought—to assess the performance of these models on the given tasks.
arithemtic-tasksbtlmscerebrashuggingfacein-context-learningllama2llms-benchmarkingmamba-state-space-modelsmistral-7bsentiment-analysis
作成時間：2024-05-17T16:08:49
更新時間：2025-01-28T03:57:39
https://amit-sarker.github.io/projects/4_project/
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