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  task_categories:
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  - question-answering
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  ---
 
 
 
 
 
 
 
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  # WikiContradict
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  <!-- Provide a quick summary of the dataset. -->
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- <!-- https://github.com/[username]/[reponame]/blob/[branch]/image.jpg?raw=true -->
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- <!-- ![alt text](https://https://huggingface.co/datasets/ibm/Wikipedia_Contradict_Benchmark/tree/main/figs/Example.pdf?raw=true) -->
 
 
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- <img src="https://https://huggingface.co/datasets/ibm/Wikipedia_Contradict_Benchmark/blob/main/figs/Example.png">
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  WikiContradict is a dataset consisting of 253 high-quality, human-annotated instances designed to assess LLM performance when augmented with retrieved passages containing real-world knowledge conflicts. The dataset was created intentionally with that task in mind, focusing on a benchmark consisting of high-quality, human-annotated instances.
 
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  task_categories:
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  - question-answering
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  ---
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+ H1{color:Blue !important;}
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+ H2{color:DarkOrange !important;}
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+ </style>
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  # WikiContradict
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  <!-- Provide a quick summary of the dataset. -->
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+ <p align="center">
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+ <img src="./figs/Example.png" width=70%/>
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+ </p>
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  WikiContradict is a dataset consisting of 253 high-quality, human-annotated instances designed to assess LLM performance when augmented with retrieved passages containing real-world knowledge conflicts. The dataset was created intentionally with that task in mind, focusing on a benchmark consisting of high-quality, human-annotated instances.