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pro vyhledávání: '"Campbell, Murray"'
Relational reasoning refers to the ability to infer and understand the relations between multiple entities. In humans, this ability underpins many higher cognitive functions, such as problem solving and decision-making, and has been reliably linked t
Externí odkaz:
http://arxiv.org/abs/2406.08272
Autor:
Basu, Kinjal, Murugesan, Keerthiram, Chaudhury, Subhajit, Campbell, Murray, Talamadupula, Kartik, Klinger, Tim
Text-based games (TBGs) have emerged as an important collection of NLP tasks, requiring reinforcement learning (RL) agents to combine natural language understanding with reasoning. A key challenge for agents attempting to solve such tasks is to gener
Externí odkaz:
http://arxiv.org/abs/2403.10692
The advent of the Transformer has led to the development of large language models (LLM), which appear to demonstrate human-like capabilities. To assess the generality of this class of models and a variety of other base neural network architectures to
Externí odkaz:
http://arxiv.org/abs/2401.15030
Autor:
Yu, Mo, Gu, Yi, Guo, Xiaoxiao, Feng, Yufei, Zhu, Xiaodan, Greenspan, Michael, Campbell, Murray, Gan, Chuang
Commonsense reasoning simulates the human ability to make presumptions about our physical world, and it is an essential cornerstone in building general AI systems. We propose a new commonsense reasoning dataset based on human's Interactive Fiction (I
Externí odkaz:
http://arxiv.org/abs/2210.15456
Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environments
Autor:
Ganapini, Marianna B., Campbell, Murray, Fabiano, Francesco, Horesh, Lior, Lenchner, Jon, Loreggia, Andrea, Mattei, Nicholas, Rahgooy, Taher, Rossi, Francesca, Srivastava, Biplav, Venable, Brent
Current AI systems lack several important human capabilities, such as adaptability, generalizability, self-control, consistency, common sense, and causal reasoning. We believe that existing cognitive theories of human decision making, such as the thi
Externí odkaz:
http://arxiv.org/abs/2201.07050
Autor:
Ganapini, Marianna Bergamaschi, Campbell, Murray, Fabiano, Francesco, Horesh, Lior, Lenchner, Jon, Loreggia, Andrea, Mattei, Nicholas, Rossi, Francesca, Srivastava, Biplav, Venable, Kristen Brent
AI systems have seen dramatic advancement in recent years, bringing many applications that pervade our everyday life. However, we are still mostly seeing instances of narrow AI: many of these recent developments are typically focused on a very limite
Externí odkaz:
http://arxiv.org/abs/2110.01834
Autor:
Zachary A. Siders, Campbell Murray, Charity Puloka, Shelton Harley, Clinton Duffy, Christopher A. Long, Robert N. M. Ahrens, T. Todd Jones
Publikováno v:
Frontiers in Marine Science, Vol 11 (2024)
Western Pacific leatherback sea turtles (Dermochelys coriacea) are a priority bycatch mitigation concern due to the projected extinction of the population before the end of the 21st century. The species regularly occurs as bycatch in gillnet and surf
Externí odkaz:
https://doaj.org/article/5b93c3be097e4f889c217c1d6b72d321
Human judgments of word similarity have been a popular method of evaluating the quality of word embedding. But it fails to measure the geometry properties such as asymmetry. For example, it is more natural to say "Ellipses are like Circles" than "Cir
Externí odkaz:
http://arxiv.org/abs/2012.01631
This paper studies a new design of the optimization algorithm for training deep learning models with a fixed architecture of the classification network in a continual learning framework. The training data is non-stationary and the non-stationarity is
Externí odkaz:
http://arxiv.org/abs/2011.12581