25 citations · 73 across the 24 of their papers we have counts for
11 papers · 1 filter
Neural Conversation Models and How to Rein Them in: A Survey of Failures and Fixes
Fabian Galetzka, Anne Beyer, David Schlangen
Recent conditional language models are able to continue any kind of text source in an often seemingly fluent way. This fact encouraged research in the area of open-domain conversat…
The Road to Quality is Paved with Good Revisions: A Detailed Evaluation Methodology for Revision Policies in Incremental Sequence Labelling
Brielen Madureira, Patrick Kahardipraja, David Schlangen
Incremental dialogue model components produce a sequence of output prefixes based on incoming input. Mistakes can occur due to local ambiguities or to wrong hypotheses, making the…
"Are you telling me to put glasses on the dog?'' Content-Grounded Annotation of Instruction Clarification Requests in the CoDraw Dataset
Brielen Madureira, David Schlangen
Instruction Clarification Requests are a mechanism to solve communication problems, which is very functional in instruction-following interactions. Recent work has argued that the…
Pento-DIARef: A Diagnostic Dataset for Learning the Incremental Algorithm for Referring Expression Generation from Examples
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 capabiliti…
Images in Language Space: Exploring the Suitability of Large Language Models for Vision & Language Tasks
Sherzod Hakimov, David Schlangen
Large language models have demonstrated robust performance on various language tasks using zero-shot or few-shot learning paradigms. While being actively researched, multimodal mod…
Yes, this Way! Learning to Ground Referring Expressions into Actions with Intra-episodic Feedback from Supportive Teachers
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. In this paper,…