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1804.05018
Cited By

Comparatives, Quantifiers, Proportions: A Multi-Task Model for the
Learning of Quantities from Vision

Comparatives, Quantifiers, Proportions: A Multi-Task Model for the Learning of Quantities from Vision

13 April 2018

Sandro Pezzelle

Ionut-Teodor Sorodoc

Raffaella Bernardi

ArXiv (abs)PDF HTML

Papers citing "Comparatives, Quantifiers, Proportions: A Multi-Task Model for the Learning of Quantities from Vision"

4 / 4 papers shown

Pragmatic Reasoning Unlocks Quantifier Semantics for Foundation Models

Pragmatic Reasoning Unlocks Quantifier Semantics for Foundation Models

Shashank Srivastava

178

2

0

08 Nov 2023

Is the Red Square Big? MALeViC: Modeling Adjectives Leveraging Visual
Contexts

Is the Red Square Big? MALeViC: Modeling Adjectives Leveraging Visual ContextsConference on Empirical Methods in Natural Language Processing (EMNLP), 2019

Sandro Pezzelle

Raquel Fernández

118

18

0

27 Aug 2019

Multimodal Logical Inference System for Visual-Textual Entailment

Multimodal Logical Inference System for Visual-Textual EntailmentAnnual Meeting of the Association for Computational Linguistics (ACL), 2019

Masashi Yoshikawa

165

21

0

10 Jun 2019

The meaning of "most" for visual question answering models

The meaning of "most" for visual question answering models

Ann A. Copestake

134

4

0

31 Dec 2018