57 citations · 79 across the 14 of their papers we have counts for
5 papers · 1 filter
Beyond task success: A closer look at jointly learning to see, ask, and GuessWhat
Ravi Shekhar, Aashish Venkatesh, Tim Baumgärtner +4
We propose a grounded dialogue state encoder which addresses a foundational issue on how to integrate visual grounding with dialogue system components. As a test-bed, we focus on t…
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…
Ask No More: Deciding when to guess in referential visual dialogue
Ravi Shekhar, Tim Baumgartner, Aashish Venkatesh +3
Our goal is to explore how the abilities brought in by a dialogue manager can be included in end-to-end visually grounded conversational agents. We make initial steps towards this…
Some of Them Can be Guessed! Exploring the Effect of Linguistic Context in Predicting Quantifiers
Sandro Pezzelle, Shane Steinert-Threlkeld, Raffaela Bernardi +1
We study the role of linguistic context in predicting quantifiers (`few', `all'). We collect crowdsourced data from human participants and test various models in a local (single-se…
Comparatives, Quantifiers, Proportions: A Multi-Task Model for the Learning of Quantities from Vision
Sandro Pezzelle, Ionut-Teodor Sorodoc, Raffaella Bernardi
The present work investigates whether different quantification mechanisms (set comparison, vague quantification, and proportional estimation) can be jointly learned from visual sce…