8 papers
Large Language Models Miss the Multi-Agent Mark
Emanuele La Malfa, Gabriele La Malfa, Samuele Marro +5
Recent interest in Multi-Agent Systems of Large Language Models (MAS LLMs) has led to an increase in frameworks leveraging multiple LLMs to tackle complex tasks. However, much of t…
Fixed Point Explainability
Emanuele La Malfa, Jon Vadillo, Marco Molinari +1
This paper introduces a formal notion of fixed point explanations, inspired by the "why regress" principle, to assess, through recursive applications, the stability of the interpla…
Language Models Are Implicitly Continuous
Samuele Marro, Davide Evangelista, X. Angelo Huang +3
Language is typically modelled with discrete sequences. However, the most successful approaches to language modelling, namely neural networks, are continuous and smooth function ap…
Out-of-Context Reasoning in Large Language Models
Jonathan Shaki, Emanuele La Malfa, Michael Wooldridge +1
We study how large language models (LLMs) reason about memorized knowledge through simple binary relations such as equality (), inequality (), and inclusion (). Unli…
Code Simulation as a Proxy for High-order Tasks in Large Language Models
Emanuele La Malfa, Christoph Weinhuber, Orazio Torre +6
Many reasoning, planning, and problem-solving tasks share an intrinsic algorithmic nature: correctly simulating each step is a sufficient condition to solve them correctly. We coll…
Jailbreaking Large Language Models in Infinitely Many Ways
Oliver Goldstein, Emanuele La Malfa, Felix Drinkall +2
We discuss the ``Infinitely Many Paraphrases'' attacks (IMP), a category of jailbreaks that leverages the increasing capabilities of a model to handle paraphrases and encoded commu…