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--- |
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license: mit |
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configs: |
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- config_name: static |
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data_files: |
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- split: test |
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path: "static.csv" |
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- config_name: temporal |
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data_files: |
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- split: test |
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path: "temporal.csv" |
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- config_name: disputable |
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data_files: |
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- split: test |
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path: "disputable.csv" |
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--- |
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# DYMANICQA |
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This is a repository for the paper [DYNAMICQA: Tracing Internal Knowledge Conflicts in Language Models](https://arxiv.org/abs/2407.17023) accepted at Findings of EMNLP 2024. |
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<p align="center"> |
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<img src="main_figure.png" width="650" alt="main_figure"> |
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</p> |
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Our paper investigates the Language Model's behaviour when the conflicting knowledge exist within the LM's parameters. We present a novel dataset containing inherently conflicting data, DYNAMICQA. Our dataset consists of three partitions, **Static**, **Disputable** 🤷♀️, and **Temporal** 🕰️. |
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We also evaluate several measures on their ability to reflect the presence of intra-memory conflict: **Semantic Entropy** and a novel **Coherent Persuasion Score**. You can find our findings from our paper! |
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The implementation of the measures is available on our github [repo](https://github.com/copenlu/dynamicqa)! |
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## Dataset |
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Our dataset consists of three different partitions. |
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| Partition | Number of Questions | |
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| --------- | ------------------- | |
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| Static | 2500 | |
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| Temporal | 2495 | |
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| Disputable | 694 | |
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