commit 34b1a5751496c1bceb8cb2f04883333f396dd0e9 parent e7bc5213da3ac177ea408cd085104ac38bffcf0c Author: Sondre Wold <sondrewold1@gmail.com> Date: Thu, 30 May 2024 15:08:10 +0200 Fixes to README Diffstat:
| M | README.md | | | 20 | ++------------------ |
1 file changed, 2 insertions(+), 18 deletions(-)
diff --git a/README.md b/README.md @@ -7,29 +7,13 @@ <p align="center"> <i> - <sup>*</sup>University of Oslo<br> + University of Oslo<br> </i> <br> </p> <br> -Grounded language models use external sources of information, such as -knowledge graphs, to meet some of the general challenges associated with -pre-training. By extending previous work on compositional generalization in -semantic parsing, we allow for a controlled evaluation of the degree to -which grounded language models can learn and generalize from patterns in -knowledge graphs. We develop a procedure for generating natural language -questions paired with knowledge graphs that targets different aspects of -compositionality and further avoids grounding the language models in -information already encoded implicitly in their weights. We evaluate -existing methods for combining language models with knowledge graphs and -find that all of them struggle with generalization to sequences of unseen -lengths and to novel combinations of seen base components. While our -experimental results provide some insight into the expressive power of -these models, we hope our work and released datasets motivate future -research on how to better combine language models with structured knowledge -representations. <p align="center"> - <a href="https://arxiv.org/abs/2404.01196"><b>Paper</b></a><br> + <a href=""><b>Paper</b></a><br> </p> _______