Are Current Decoding Strategies Capable of Facing the Challenges of Visual Dialogue?
Amit Chaudhary, Alex J. Lucassen, Ioanna Tsani, Alberto Testoni · 2022
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 different strategies handle the numerous challenges that goal-oriented multimodal systems face (such as grounding and informativeness).To answer this question, we compare a wide variety of different decoding strategies and hyper-parameter configurations in a Visual Dialogue referential game.Although none of them successfully balance lexical richness, accuracy in the task, and visual grounding, our in-depth analysis allows us to highlight the strengths and weaknesses of each decoding strategy.We believe our findings and suggestions may serve as a starting point for designing more effective decoding algorithms that handle the challenges of Visual Dialogue tasks.