Datasets:
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---
license: mit
configs:
- config_name: static
data_files:
- split: test
path: static.csv
- config_name: temporal
data_files:
- split: test
path: temporal.csv
- config_name: disputable
data_files:
- split: test
path: disputable.csv
task_categories:
- question-answering
language:
- en
pretty_name: DynamicQA
size_categories:
- 10K<n<100K
---
# DYNAMICQA
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.
<p align="center">
<img src="main_figure.png" width="800" alt="main_figure">
</p>
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** 🕰️.
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!
The implementation of the measures is available on our github [repo](https://github.com/copenlu/dynamicqa)!
## Dataset
Our dataset consists of three different partitions.
| Partition | Number of Questions |
| --------- | ------------------- |
| Static | 2500 |
| Temporal | 2495 |
| Disputable | 694 |
### Details
1. Question : "question" column
2. Answers : Two different answers are available: one in the "obj" column and the other in the "replace_name" column.
3. Context : Context ("context" column) is masked with \[ENTITY\]. Before providing the context to the LM, you should replace \[ENTITY\] with either "obj" or "replace_name".
4. Number of edits : "num_edits" column. This denotes Temporality for temporal partition, and Disputability for disputable partition. |