4 papers
Identifying Scientists on X
Philipp Meier, Katarina Boland, Laura Kallmeyer +1
With the growing importance of science-related discourse on the Web and the erosion of the classical knowledge order, it is important to identify different user groups, such as sci…
Understanding Syntactic Generalization in Structure-inducing Language Models
David Arps, Hassan Sajjad, Laura Kallmeyer
Structure-inducing Language Models (SiLM) are trained on a self-supervised language modeling task, and induce a hierarchical sentence representation as a byproduct when processing…
Seeing Syntax: Uncovering Syntactic Learning Limitations in Vision-Language Models
Sri Harsha Dumpala, David Arps, Sageev Oore +2
Vision-language models (VLMs), serve as foundation models for multi-modal applications such as image captioning and text-to-image generation. Recent studies have highlighted limita…
Dissecting Paraphrases: The Impact of Prompt Syntax and supplementary Information on Knowledge Retrieval from Pretrained Language Models
Stephan Linzbach, Dimitar Dimitrov, Laura Kallmeyer +3
Pre-trained Language Models (PLMs) are known to contain various kinds of knowledge. One method to infer relational knowledge is through the use of cloze-style prompts, where a mode…