29 citations · 53 across the 26 of their papers we have counts for
6 papers · 1 filter
A Scalable Communication Protocol for Networks of Large Language Models
Samuele Marro, Emanuele La Malfa, Jesse Wright +4
Communication is a prerequisite for collaboration. When scaling networks of AI-powered agents, communication must be versatile, efficient, and portable. These requisites, which we…
Assessing Dialect Fairness and Robustness of Large Language Models in Reasoning Tasks
Fangru Lin, Shaoguang Mao, Emanuele La Malfa +7
Language is not monolithic. While benchmarks, including those designed for multiple languages, are often used as proxies to evaluate the performance of Large Language Models (LLMs)…
A Notion of Complexity for Theory of Mind via Discrete World Models
X. Angelo Huang, Emanuele La Malfa, Samuele Marro +3
Theory of Mind (ToM) can be used to assess the capabilities of Large Language Models (LLMs) in complex scenarios where social reasoning is required. While the research community ha…
Deep Neural Networks via Complex Network Theory: a Perspective
Emanuele La Malfa, Gabriele La Malfa, Giuseppe Nicosia +1
Deep Neural Networks (DNNs) can be represented as graphs whose links and vertices iteratively process data and solve tasks sub-optimally. Complex Network Theory (CNT), merging stat…
Graph-enhanced Large Language Models in Asynchronous Plan Reasoning
Fangru Lin, Emanuele La Malfa, Valentin Hofmann +3
Planning is a fundamental property of human intelligence. Reasoning about asynchronous plans is challenging since it requires sequential and parallel planning to optimize time cost…
Code Simulation Challenges for Large Language Models
Emanuele La Malfa, Christoph Weinhuber, Orazio Torre +5
Many reasoning, planning, and problem-solving tasks share an intrinsic algorithmic nature: correctly simulating each step is a sufficient condition to solve them correctly. This wo…