274 citations · 2.9k across the 39 of their papers we have counts for
40 papers
Improving Instruct Models for Free: A Study on Partial Adaptation
Ozan İrsoy, Pengxiang Cheng, Jennifer L. Chen +3
Instruct models, obtained from various instruction tuning or post-training steps, are commonly deemed superior and more usable than their base counterpart. While the model gains in…
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…
Reframing Jet Physics with New Computational Methods
Kyle Cranmer, Matthew Drnevich, Sebastian Macaluso +1
We reframe common tasks in jet physics in probabilistic terms, including jet reconstruction, Monte Carlo tuning, matrix element - parton shower matching for large jet multiplicity,…
Hierarchical clustering in particle physics through reinforcement learning
Johann Brehmer, Sebastian Macaluso, Duccio Pappadopulo +1
Particle physics experiments often require the reconstruction of decay patterns through a hierarchical clustering of the observed final-state particles. We show that this task can…