activity
20182020
most citedAn Information Extraction and Knowledge Graph Platform for Accelerating Biochemical Discoveries

8 citations · 23 across the 6 of their papers we have counts for

collaborators

13 papers

cs.CL2020

Understood in Translation, Transformers for Domain Understanding

Dimitrios Christofidellis, Matteo Manica, Leonidas Georgopoulos +1

Knowledge acquisition is the essential first step of any Knowledge Graph (KG) application. This knowledge can be extracted from a given corpus (KG generation process) or specified…

q-bio.BM20202 cited

Pre-training Protein Language Models with Label-Agnostic Binding Pairs Enhances Performance in Downstream Tasks

Modestas Filipavicius, Matteo Manica, Joris Cadow +1

Less than 1% of protein sequences are structurally and functionally annotated. Natural Language Processing (NLP) community has recently embraced self-supervised learning as a power…

cs.CL2020

Hierarchical Pre-training for Sequence Labelling in Spoken Dialog

Emile Chapuis, Pierre Colombo, Matteo Manica +2

Sequence labelling tasks like Dialog Act and Emotion/Sentiment identification are a key component of spoken dialog systems. In this work, we propose a new approach to learn generic…

q-bio.QM2020

PaccMann on SARS-CoV-2: Designing antiviral candidates with conditional generative models

Jannis Born, Matteo Manica, Joris Cadow +4

With the fast development of COVID-19 into a global pandemic, scientists around the globe are desperately searching for effective antiviral therapeutic agents. Bridging systems bio…

cs.CL2020

Guider l'attention dans les modeles de sequence a sequence pour la prediction des actes de dialogue

Pierre Colombo, Emile Chapuis, Matteo Manica +3

The task of predicting dialog acts (DA) based on conversational dialog is a key component in the development of conversational agents. Accurately predicting DAs requires a precise…

cs.CL20207 cited

Guiding attention in Sequence-to-sequence models for Dialogue Act prediction

Pierre Colombo, Emile Chapuis, Matteo Manica +3

The task of predicting dialog acts (DA) based on conversational dialog is a key component in the development of conversational agents. Accurately predicting DAs requires a precise…