25 citations · 72 across the 23 of their papers we have counts for
6 papers · 1 filter
TxT: Crossmodal End-to-End Learning with Transformers
Jan-Martin O. Steitz, Jonas Pfeiffer, Iryna Gurevych +1
Reasoning over multiple modalities, e.g. in Visual Question Answering (VQA), requires an alignment of semantic concepts across domains. Despite the widespread success of end-to-end…
Smelting Gold and Silver for Improved Multilingual AMR-to-Text Generation
Leonardo F. R. Ribeiro, Jonas Pfeiffer, Yue Zhang +1
Recent work on multilingual AMR-to-text generation has exclusively focused on data augmentation strategies that utilize silver AMR. However, this assumes a high quality of generate…
xGQA: Cross-Lingual Visual Question Answering
Jonas Pfeiffer, Gregor Geigle, Aishwarya Kamath +4
Recent advances in multimodal vision and language modeling have predominantly focused on the English language, mostly due to the lack of multilingual multimodal datasets to steer m…
AdapterHub Playground: Simple and Flexible Few-Shot Learning with Adapters
Tilman Beck, Bela Bohlender, Christina Viehmann +6
The open-access dissemination of pretrained language models through online repositories has led to a democratization of state-of-the-art natural language processing (NLP) research.…
What to Pre-Train on? Efficient Intermediate Task Selection
Clifton Poth, Jonas Pfeiffer, Andreas Rücklé +1
Intermediate task fine-tuning has been shown to culminate in large transfer gains across many NLP tasks. With an abundance of candidate datasets as well as pre-trained language mod…
Retrieve Fast, Rerank Smart: Cooperative and Joint Approaches for Improved Cross-Modal Retrieval
Gregor Geigle, Jonas Pfeiffer, Nils Reimers +2
Current state-of-the-art approaches to cross-modal retrieval process text and visual input jointly, relying on Transformer-based architectures with cross-attention mechanisms that…