25 citations · 32 across the 5 of their papers we have counts for
11 papers · 1 filter
The slurk Interaction Server Framework: Better Data for Better Dialog Models
Jana Götze, Maike Paetzel-Prüsmann, Wencke Liermann +2
This paper presents the slurk software, a lightweight interaction server for setting up dialog data collections and running experiments. Slurk enables a multitude of settings inclu…
Is Incoherence Surprising? Targeted Evaluation of Coherence Prediction from Language Models
Anne Beyer, Sharid Loáiciga, David Schlangen
Coherent discourse is distinguished from a mere collection of utterances by the satisfaction of a diverse set of constraints, for example choice of expression, logical relation bet…
An Overview of Natural Language State Representation for Reinforcement Learning
Brielen Madureira, David Schlangen
A suitable state representation is a fundamental part of the learning process in Reinforcement Learning. In various tasks, the state can either be described by natural language or…
Targeting the Benchmark: On Methodology in Current Natural Language Processing Research
David Schlangen
It has become a common pattern in our field: One group introduces a language task, exemplified by a dataset, which they argue is challenging enough to serve as a benchmark. They al…
A Corpus of Controlled Opinionated and Knowledgeable Movie Discussions for Training Neural Conversation Models
Fabian Galetzka, Chukwuemeka U. Eneh, David Schlangen
Fully data driven Chatbots for non-goal oriented dialogues are known to suffer from inconsistent behaviour across their turns, stemming from a general difficulty in controlling par…
Can Neural Image Captioning be Controlled via Forced Attention?
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. The weights applied when generating…