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cs.CL2022

UKP-SQUARE: An Online Platform for Question Answering Research

Tim Baumgärtner, Kexin Wang, Rachneet Sachdeva +10

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…

cs.CL2019

The PhotoBook Dataset: Building Common Ground through Visually-Grounded Dialogue

Janosch Haber, Tim Baumgärtner, Ece Takmaz +3

This paper introduces the PhotoBook dataset, a large-scale collection of visually-grounded, task-oriented dialogues in English designed to investigate shared dialogue history accum…

cs.CL2019

On the Realization of Compositionality in Neural Networks

Joris Baan, Jana Leible, Mitja Nikolaus +5

We present a detailed comparison of two types of sequence to sequence models trained to conduct a compositional task. The models are architecturally identical at inference time, bu…

cs.CL2018

Beyond task success: A closer look at jointly learning to see, ask, and GuessWhat

Ravi Shekhar, Aashish Venkatesh, Tim Baumgärtner +4

We propose a grounded dialogue state encoder which addresses a foundational issue on how to integrate visual grounding with dialogue system components. As a test-bed, we focus on t…

cs.CL2018

Ask No More: Deciding when to guess in referential visual dialogue

Ravi Shekhar, Tim Baumgartner, Aashish Venkatesh +3

Our goal is to explore how the abilities brought in by a dialogue manager can be included in end-to-end visually grounded conversational agents. We make initial steps towards this…