5 papers · 1 filter
Are Current Decoding Strategies Capable of Facing the Challenges of Visual Dialogue?
Amit Kumar Chaudhary, Alex J. Lucassen, Ioanna Tsani +1
Decoding strategies play a crucial role in natural language generation systems. They are usually designed and evaluated in open-ended text-only tasks, and it is not clear how diffe…
Looking for Confirmations: An Effective and Human-Like Visual Dialogue Strategy
Alberto Testoni, Raffaella Bernardi
Generating goal-oriented questions in Visual Dialogue tasks is a challenging and long-standing problem. State-Of-The-Art systems are shown to generate questions that, although gram…
Overprotective Training Environments Fall Short at Testing Time: Let Models Contribute to Their Own Training
Alberto Testoni, Raffaella Bernardi
Despite important progress, conversational systems often generate dialogues that sound unnatural to humans. We conjecture that the reason lies in their different training and testi…
The Interplay of Task Success and Dialogue Quality: An in-depth Evaluation in Task-Oriented Visual Dialogues
Alberto Testoni, Raffaella Bernardi
When training a model on referential dialogue guessing games, the best model is usually chosen based on its task success. We show that in the popular end-to-end approach, this choi…
Grounded Textual Entailment
Hoa Trong Vu, Claudio Greco, Aliia Erofeeva +6
Capturing semantic relations between sentences, such as entailment, is a long-standing challenge for computational semantics. Logic-based models analyse entailment in terms of poss…