211 citations · 378 across the 15 of their papers we have counts for
13 papers · 1 filter
Communication breakdown: On the low mutual intelligibility between human and neural captioning
Roberto Dessì, Eleonora Gualdoni, Francesca Franzon +2
We compare the 0-shot performance of a neural caption-based image retriever when given as input either human-produced captions or captions generated by a neural captioner. We condu…
Does referent predictability affect the choice of referential form? A computational approach using masked coreference resolution
Laura Aina, Xixian Liao, Gemma Boleda +1
It is often posited that more predictable parts of a speaker's meaning tend to be made less explicit, for instance using shorter, less informative words. Studying these dynamics in…
Deep daxes: Mutual exclusivity arises through both learning biases and pragmatic strategies in neural networks
Kristina Gulordava, Thomas Brochhagen, Gemma Boleda
Children's tendency to associate novel words with novel referents has been taken to reflect a bias toward mutual exclusivity. This tendency may be advantageous both as (1) an ad-ho…
Putting words in context: LSTM language models and lexical ambiguity
Laura Aina, Kristina Gulordava, Gemma Boleda
In neural network models of language, words are commonly represented using context-invariant representations (word embeddings) which are then put in context in the hidden layers. S…
Don't Blame Distributional Semantics if it can't do Entailment
Matthijs Westera, Gemma Boleda
Distributional semantics has had enormous empirical success in Computational Linguistics and Cognitive Science in modeling various semantic phenomena, such as semantic similarity,…
What do Entity-Centric Models Learn? Insights from Entity Linking in Multi-Party Dialogue
Laura Aina, Carina Silberer, Matthijs Westera +2
Humans use language to refer to entities in the external world. Motivated by this, in recent years several models that incorporate a bias towards learning entity representations ha…
Distributional Semantics and Linguistic Theory
Gemma Boleda
Distributional semantics provides multi-dimensional, graded, empirically induced word representations that successfully capture many aspects of meaning in natural languages, as sho…
Short-Term Meaning Shift: A Distributional Exploration
Marco Del Tredici, Raquel Fernández, Gemma Boleda
We present the first exploration of meaning shift over short periods of time in online communities using distributional representations. We create a small annotated dataset and use…
Instantiation
Abhijeet Gupta, Gemma Boleda, Sebastian Pado
In computational linguistics, a large body of work exists on distributed modeling of lexical relations, focussing largely on lexical relations such as hypernymy (scientist -- perso…
AMORE-UPF at SemEval-2018 Task 4: BiLSTM with Entity Library
Laura Aina, Carina Silberer, Ionut-Teodor Sorodoc +2
This paper describes our winning contribution to SemEval 2018 Task 4: Character Identification on Multiparty Dialogues. It is a simple, standard model with one key innovation, an e…
Living a discrete life in a continuous world: Reference with distributed representations
Gemma Boleda, Sebastian Padó, Nghia The Pham +1
Reference is a crucial property of language that allows us to connect linguistic expressions to the world. Modeling it requires handling both continuous and discrete aspects of mea…
"Show me the cup": Reference with Continuous Representations
Gemma Boleda, Sebastian Padó, Marco Baroni
One of the most basic functions of language is to refer to objects in a shared scene. Modeling reference with continuous representations is challenging because it requires individu…
The LAMBADA dataset: Word prediction requiring a broad discourse context
Denis Paperno, Germán Kruszewski, Angeliki Lazaridou +6
We introduce LAMBADA, a dataset to evaluate the capabilities of computational models for text understanding by means of a word prediction task. LAMBADA is a collection of narrative…