269 citations · 2.2k across the 32 of their papers we have counts for
33 papers
Non-contrastive sentence representations via self-supervision
Marco Farina, Duccio Pappadopulo
Sample contrastive methods, typically referred to simply as contrastive are the foundation of most unsupervised methods to learn text and sentence embeddings. On the other hand, a…
Distillation of encoder-decoder transformers for sequence labelling
Marco Farina, Duccio Pappadopulo, Anant Gupta +3
Driven by encouraging results on a wide range of tasks, the field of NLP is experiencing an accelerated race to develop bigger language models. This race for bigger models has also…
Disentangling Online Chats with DAG-Structured LSTMs
Duccio Pappadopulo, Lisa Bauer, Marco Farina +2
Many modern messaging systems allow fast and synchronous textual communication among many users. The resulting sequence of messages hides a more complicated structure in which inde…
Searching for long-lived particles beyond the Standard Model at the Large Hadron Collider
Juliette Alimena, James Beacham, Martino Borsato +198
Particles beyond the Standard Model (SM) can generically have lifetimes that are long compared to SM particles at the weak scale. When produced at experiments such as the Large Had…
New Physics from High Energy Tops
Marco Farina, Cristina Mondino, Duccio Pappadopulo +1
Precision measurements of high energy top quarks at the LHC constitute a powerful probe of new physics. We study the effect of four fermion operators involving two tops and two lig…
Searching for New Physics with Deep Autoencoders
Marco Farina, Yuichiro Nakai, David Shih
We introduce a potentially powerful new method of searching for new physics at the LHC, using autoencoders and unsupervised deep learning. The key idea of the autoencoder is that i…