1 code implementation • 31 Mar 2023 • Haritz Puerto, Tim Baumgärtner, Rachneet Sachdeva, Haishuo Fang, Hao Zhang, Sewin Tariverdian, Kexin Wang, Iryna Gurevych
To ease research in multi-agent models, we extend UKP-SQuARE, an online platform for QA research, to support three families of multi-agent systems: i) agent selection, ii) early-fusion of agents, and iii) late-fusion of agents.
1 code implementation • 19 Oct 2022 • Tim Baumgärtner, Leonardo F. R. Ribeiro, Nils Reimers, Iryna Gurevych
Pairing a lexical retriever with a neural re-ranking model has set state-of-the-art performance on large-scale information retrieval datasets.
1 code implementation • 19 Aug 2022 • Rachneet Sachdeva, Haritz Puerto, Tim Baumgärtner, Sewin Tariverdian, Hao Zhang, Kexin Wang, Hossain Shaikh Saadi, Leonardo F. R. Ribeiro, Iryna Gurevych
In this paper, we introduce SQuARE v2, the new version of SQuARE, to provide an explainability infrastructure for comparing models based on methods such as saliency maps and graph-based explanations.
1 code implementation • ACL 2022 • Tim Baumgärtner, Kexin Wang, Rachneet Sachdeva, Max Eichler, Gregor Geigle, Clifton Poth, Hannah Sterz, Haritz Puerto, Leonardo F. R. Ribeiro, Jonas Pfeiffer, Nils Reimers, Gözde Gül Şahin, Iryna Gurevych
Recent advances in NLP and information retrieval have given rise to a diverse set of question answering tasks that are of different formats (e. g., extractive, abstractive), require different model architectures (e. g., generative, discriminative), and setups (e. g., with or without retrieval).
no code implementations • ACL 2019 • Janosch Haber, Tim Baumgärtner, Ece Takmaz, Lieke Gelderloos, Elia Bruni, Raquel Fernández
This paper introduces the PhotoBook dataset, a large-scale collection of visually-grounded, task-oriented dialogues in English designed to investigate shared dialogue history accumulating during conversation.
no code implementations • WS 2019 • Joris Baan, Jana Leible, Mitja Nikolaus, David Rau, Dennis Ulmer, Tim Baumgärtner, Dieuwke Hupkes, Elia Bruni
We present a detailed comparison of two types of sequence to sequence models trained to conduct a compositional task.
3 code implementations • NAACL 2019 • Ravi Shekhar, Aashish Venkatesh, Tim Baumgärtner, Elia Bruni, Barbara Plank, Raffaella Bernardi, Raquel Fernández
We compare our approach to an alternative system which extends the baseline with reinforcement learning.