10 citations · 10 across the 2 of their papers we have counts for
4 papers · 1 filter
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,…
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…