Papers by Derek Thomas
TAXI: Evaluating Categorical Knowledge Editing for Language Models (2024.findings-acl)
Copied to clipboard
| Challenge: | Knowledge editing aims to inject new facts into language models to improve factuality, but current benchmarks fail to evaluate consistency, which is critical to ensure efficient, accurate, and generalizable edits. |
| Approach: | They manually create a new benchmark dataset specifically created to evaluate consistency in categorical knowledge edits. |
| Outcome: | The results show that the editors achieve marginal, yet non-random consistency, and their consistency far underperforms human baselines. |
Autoencoding Keyword Correlation Graph for Document Clustering (2020.acl-main)
Copied to clipboard
| Challenge: | Existing representation learning models do not capture the intra-sentential and inter-sententential features of long-text. |
| Approach: | They propose a graph-based representation for document clustering that builds a Graph Autoencoder on a Keyword Correlation Graph. |
| Outcome: | The proposed graph autoencoder can achieve better clustering performance than existing features. |