71 citations · 229 across the 21 of their papers we have counts for
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cs.AI2026
Sequential Enumeration in Large Language Models
Kuinan Hou, Marco Zorzi, Alberto Testolin
Reliably counting and generating sequences of items remain a significant challenge for neural networks, including Large Language Models (LLMs). Indeed, although this capability is…
cs.AI2025
Learning neuro-symbolic convergent term rewriting systems
Flavio Petruzzellis, Alberto Testolin, Alessandro Sperduti
Building neural systems that can learn to execute symbolic algorithms is a challenging open problem in artificial intelligence, especially when aiming for strong generalization and…
cs.AI2023★ 27 cited
Can neural networks do arithmetic? A survey on the elementary numerical skills of state-of-the-art deep learning models
Alberto Testolin
Creating learning models that can exhibit sophisticated reasoning skills is one of the greatest challenges in deep learning research, and mathematics is rapidly becoming one of the…