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Found 7 papers, 6 papers with code
UGent-T2K at the 2nd DialDoc Shared Task: A Retrieval-Focused Dialog System Grounded in Multiple Documents
Further, error analysis reveals two major failure cases, to be addressed in future work: (i) in case of topic shift within the dialog, retrieval often fails to select the correct grounding document(s), and (ii) generation sometimes fails to use the correctly retrieved grounding passage.
An Emotional Journey: Detecting Emotion Trajectories in Dutch Customer Service Dialogues
The ability to track fine-grained emotions in customer service dialogues has many real-world applications, but has not been studied extensively.
Learning to Reuse Distractors to support Multiple Choice Question Generation in Education
This paper studies how a large existing set of manually created answers and distractors for questions over a variety of domains, subjects, and languages can be leveraged to help teachers in creating new MCQs, by the smart reuse of existing distractors.
EduQG: A Multi-format Multiple Choice Dataset for the Educational Domain
Thus, our versatile dataset can be used for both question and distractor generation, as well as to explore new challenges such as question format conversion.
A Million Tweets Are Worth a Few Points: Tuning Transformers for Customer Service Tasks
In online domain-specific customer service applications, many companies struggle to deploy advanced NLP models successfully, due to the limited availability of and noise in their datasets.
Block-wise Dynamic Sparseness
In this paper, we present a new method for \emph{dynamic sparseness}, whereby part of the computations are omitted dynamically, based on the input.
A Self-Training Approach for Short Text Clustering
Short text clustering is a challenging problem when adopting traditional bag-of-words or TF-IDF representations, since these lead to sparse vector representations of the short texts.
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Short Text Clustering
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