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pro vyhledávání: '"A. Testolin"'
Humans share with many animal species the ability to perceive and approximately represent the number of objects in visual scenes. This ability improves throughout childhood, suggesting that learning and development play a key role in shaping our numb
Externí odkaz:
http://arxiv.org/abs/2409.11028
Large Language Models (LLMs) achieve impressive performance in a wide range of tasks, even if they are often trained with the only objective of chatting fluently with users. Among other skills, LLMs show emergent abilities in mathematical reasoning b
Externí odkaz:
http://arxiv.org/abs/2406.06588
Modern neural network architectures still struggle to learn algorithmic procedures that require to systematically apply compositional rules to solve out-of-distribution problem instances. In this work, we focus on formula simplification problems, a c
Externí odkaz:
http://arxiv.org/abs/2402.17407
Large Language Models (LLMs) have revolutionized the field of Natural Language Processing thanks to their ability to reuse knowledge acquired on massive text corpora on a wide variety of downstream tasks, with minimal (if any) tuning steps. At the sa
Externí odkaz:
http://arxiv.org/abs/2402.17396
Humans can readily judge the number of objects in a visual scene, even without counting, and such a skill has been documented in many animal species and babies prior to language development and formal schooling. Numerical judgments are error-free for
Externí odkaz:
http://arxiv.org/abs/2402.03328
Solving symbolic reasoning problems that require compositionality and systematicity is considered one of the key ingredients of human intelligence. However, symbolic reasoning is still a great challenge for deep learning models, which often cannot ge
Externí odkaz:
http://arxiv.org/abs/2306.17249
Generative neural networks can produce data samples according to the statistical properties of their training distribution. This feature can be used to test modern computational neuroscience hypotheses suggesting that spontaneous brain activity is pa
Externí odkaz:
http://arxiv.org/abs/2305.06745
Autor:
Testolin, Alberto
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 target domains for assessing scientific progress in this direction. I
Externí odkaz:
http://arxiv.org/abs/2303.07735
Acquiring mathematical skills is considered a key challenge for modern Artificial Intelligence systems. Inspired by the way humans discover numerical knowledge, here we introduce a deep reinforcement learning framework that allows to simulate how cog
Externí odkaz:
http://arxiv.org/abs/2301.06870
Publikováno v:
Frontiers in Artificial Intelligence, 2023
Effective conservation of maritime environments and wildlife management of endangered species require the implementation of efficient, accurate and scalable solutions for environmental monitoring. Ecoacoustics offers the advantages of non-invasive, l
Externí odkaz:
http://arxiv.org/abs/2211.15406