metadata

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 accepted at Findings of EMNLP 2024.

main_figure

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!

Dataset

Our dataset consists of three different partitions.

Partition	Number of Questions
Static	2500
Temporal	2495
Disputable	694