---
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"
---


# DYMANICQA

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="650" 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 |