36 citations · 57 across the 22 of their papers we have counts for
5 papers · 1 filter
How should the advent of large language models affect the practice of science?
Marcel Binz, Stephan Alaniz, Adina Roskies +15
Large language models (LLMs) are being increasingly incorporated into scientific workflows. However, we have yet to fully grasp the implications of this integration. How should the…
PDiscoNet: Semantically consistent part discovery for fine-grained recognition
Robert van der Klis, Stephan Alaniz, Massimiliano Mancini +4
Fine-grained classification often requires recognizing specific object parts, such as beak shape and wing patterns for birds. Encouraging a fine-grained classification model to fir…
Iterative Superquadric Recomposition of 3D Objects from Multiple Views
Stephan Alaniz, Massimiliano Mancini, Zeynep Akata
Humans are good at recomposing novel objects, i.e. they can identify commonalities between unknown objects from general structure to finer detail, an ability difficult to replicate…
DeViL: Decoding Vision features into Language
Meghal Dani, Isabel Rio-Torto, Stephan Alaniz +1
Post-hoc explanation methods have often been criticised for abstracting away the decision-making process of deep neural networks. In this work, we would like to provide natural lan…
In-Context Impersonation Reveals Large Language Models' Strengths and Biases
Leonard Salewski, Stephan Alaniz, Isabel Rio-Torto +2
In everyday conversations, humans can take on different roles and adapt their vocabulary to their chosen roles. We explore whether LLMs can take on, that is impersonate, different…