no code implementations • INLG (ACL) 2020 • Robin Rojowiec, Jana Götze, Philipp Sadler, Henrik Voigt, Sina Zarrieß, David Schlangen
We find that it is, and investigate several simple baselines, taking these from the related task of image captioning.
no code implementations • 31 May 2024 • Anne Beyer, Kranti Chalamalasetti, Sherzod Hakimov, Brielen Madureira, Philipp Sadler, David Schlangen
In this paper, we take one of the proposed frameworks for setting up such game-play environments, and further test its usefulness as an evaluation instrument, along a number of dimensions: We show that it can easily keep up with new developments while avoiding data contamination, we show that the tests implemented within it are not yet saturated (human performance is substantially higher than that of even the best models), and we show that it lends itself to investigating additional questions, such as the impact of the prompting language on performance.
1 code implementation • 26 Mar 2024 • Philipp Sadler, Sherzod Hakimov, David Schlangen
In collaborative goal-oriented settings, the participants are not only interested in achieving a successful outcome, but do also implicitly negotiate the effort they put into the interaction (by adapting to each other).
no code implementations • 7 Feb 2024 • Philipp Sadler, Sherzod Hakimov, David Schlangen
Albrecht and Stone (2018) state that modeling of changing behaviors remains an open problem "due to the essentially unconstrained nature of what other agents may do".
1 code implementation • 24 May 2023 • Philipp Sadler, David Schlangen
NLP tasks are typically defined extensionally through datasets containing example instantiations (e. g., pairs of image i and text t), but motivated intensionally through capabilities invoked in verbal descriptions of the task (e. g., "t is a description of i, for which the content of i needs to be recognised and understood").
1 code implementation • 22 May 2023 • Kranti Chalamalasetti, Jana Götze, Sherzod Hakimov, Brielen Madureira, Philipp Sadler, David Schlangen
Recent work has proposed a methodology for the systematic evaluation of "Situated Language Understanding Agents"-agents that operate in rich linguistic and non-linguistic contexts-through testing them in carefully constructed interactive settings.
1 code implementation • 22 May 2023 • Philipp Sadler, Sherzod Hakimov, David Schlangen
The ability to pick up on language signals in an ongoing interaction is crucial for future machine learning models to collaborate and interact with humans naturally.
no code implementations • 29 Sep 2020 • Philipp Sadler
The internal workings of modern deep learning models stay often unclear to an external observer, although spatial attention mechanisms are involved.
no code implementations • WS 2019 • Philipp Sadler, Tatjana Scheffler, David Schlangen
Learned dynamic weighting of the conditioning signal (attention) has been shown to improve neural language generation in a variety of settings.
no code implementations • 19 Oct 2018 • Philipp Sadler
First a principal component analysis in conjunction with a Fourier transform is trained on a single reference augmentation training dataset using the city images.