12 citations · 25 across the 5 of their papers we have counts for
6 papers
DynE: Dynamic Ensemble Decoding for Multi-Document Summarization
Chris Hokamp, Demian Gholipour Ghalandari, Nghia The Pham +1
Sequence-to-sequence (s2s) models are the basis for extensive work in natural language processing. However, some applications, such as multi-document summarization, multi-modal mac…
A Large-Scale Multi-Document Summarization Dataset from the Wikipedia Current Events Portal
Demian Gholipour Ghalandari, Chris Hokamp, Nghia The Pham +2
Multi-document summarization (MDS) aims to compress the content in large document collections into short summaries and has important applications in story clustering for newsfeeds,…
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…
Towards Multi-Agent Communication-Based Language Learning
Angeliki Lazaridou, Nghia The Pham, Marco Baroni
We propose an interactive multimodal framework for language learning. Instead of being passively exposed to large amounts of natural text, our learners (implemented as feed-forward…
The red one!: On learning to refer to things based on their discriminative properties
Angeliki Lazaridou, Nghia The Pham, Marco Baroni
As a first step towards agents learning to communicate about their visual environment, we propose a system that, given visual representations of a referent (cat) and a context (sof…
Combining Language and Vision with a Multimodal Skip-gram Model
Angeliki Lazaridou, Nghia The Pham, Marco Baroni
We extend the SKIP-GRAM model of Mikolov et al. (2013a) by taking visual information into account. Like SKIP-GRAM, our multimodal models (MMSKIP-GRAM) build vector-based word repre…