Zobrazeno 1 - 10
of 24 269
pro vyhledávání: '"† A Lampinen"'
The ability of language models to learn a task from a few examples in context has generated substantial interest. Here, we provide a perspective that situates this type of supervised few-shot learning within a much broader spectrum of meta-learned in
Externí odkaz:
http://arxiv.org/abs/2412.03782
Autor:
Muttenthaler, Lukas, Greff, Klaus, Born, Frieda, Spitzer, Bernhard, Kornblith, Simon, Mozer, Michael C., Müller, Klaus-Robert, Unterthiner, Thomas, Lampinen, Andrew K.
Deep neural networks have achieved success across a wide range of applications, including as models of human behavior in vision tasks. However, neural network training and human learning differ in fundamental ways, and neural networks often fail to g
Externí odkaz:
http://arxiv.org/abs/2409.06509
Publikováno v:
Conference on Neural Information Processing Systems (NeurIPS), Dec 2024
Recent studies suggest that deep learning models inductive bias towards favoring simpler features may be one of the sources of shortcut learning. Yet, there has been limited focus on understanding the complexity of the myriad features that models lea
Externí odkaz:
http://arxiv.org/abs/2407.06076
Representation learning, and interpreting learned representations, are key areas of focus in machine learning and neuroscience. Both fields generally use representations as a means to understand or improve a system's computations. In this work, howev
Externí odkaz:
http://arxiv.org/abs/2405.05847
Autor:
SIMA Team, Raad, Maria Abi, Ahuja, Arun, Barros, Catarina, Besse, Frederic, Bolt, Andrew, Bolton, Adrian, Brownfield, Bethanie, Buttimore, Gavin, Cant, Max, Chakera, Sarah, Chan, Stephanie C. Y., Clune, Jeff, Collister, Adrian, Copeman, Vikki, Cullum, Alex, Dasgupta, Ishita, de Cesare, Dario, Di Trapani, Julia, Donchev, Yani, Dunleavy, Emma, Engelcke, Martin, Faulkner, Ryan, Garcia, Frankie, Gbadamosi, Charles, Gong, Zhitao, Gonzales, Lucy, Gupta, Kshitij, Gregor, Karol, Hallingstad, Arne Olav, Harley, Tim, Haves, Sam, Hill, Felix, Hirst, Ed, Hudson, Drew A., Hudson, Jony, Hughes-Fitt, Steph, Rezende, Danilo J., Jasarevic, Mimi, Kampis, Laura, Ke, Rosemary, Keck, Thomas, Kim, Junkyung, Knagg, Oscar, Kopparapu, Kavya, Lawton, Rory, Lampinen, Andrew, Legg, Shane, Lerchner, Alexander, Limont, Marjorie, Liu, Yulan, Loks-Thompson, Maria, Marino, Joseph, Cussons, Kathryn Martin, Matthey, Loic, Mcloughlin, Siobhan, Mendolicchio, Piermaria, Merzic, Hamza, Mitenkova, Anna, Moufarek, Alexandre, Oliveira, Valeria, Oliveira, Yanko, Openshaw, Hannah, Pan, Renke, Pappu, Aneesh, Platonov, Alex, Purkiss, Ollie, Reichert, David, Reid, John, Richemond, Pierre Harvey, Roberts, Tyson, Ruscoe, Giles, Elias, Jaume Sanchez, Sandars, Tasha, Sawyer, Daniel P., Scholtes, Tim, Simmons, Guy, Slater, Daniel, Soyer, Hubert, Strathmann, Heiko, Stys, Peter, Tam, Allison C., Teplyashin, Denis, Terzi, Tayfun, Vercelli, Davide, Vujatovic, Bojan, Wainwright, Marcus, Wang, Jane X., Wang, Zhengdong, Wierstra, Daan, Williams, Duncan, Wong, Nathaniel, York, Sarah, Young, Nick
Building embodied AI systems that can follow arbitrary language instructions in any 3D environment is a key challenge for creating general AI. Accomplishing this goal requires learning to ground language in perception and embodied actions, in order t
Externí odkaz:
http://arxiv.org/abs/2404.10179
Autor:
Janet Wade
Publikováno v:
The Classical Review. :1-3
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e4833663ac04103f2876a417bef1b431
https://doi.org/10.1017/s0009840x23000550
https://doi.org/10.1017/s0009840x23000550
Autor:
Sondoqah, Mousa, Abdesslem, Fehmi Ben, Popova, Kristina, McGregor, Moira, La Delfa, Joseph, Garrett, Rachael, Lampinen, Airi, Mottola, Luca, Höök, Kristina
We report on a three-day challenge during which five teams each programmed a nanodrone to be piloted through an obstacle course using bodily movement, in a 3D transposition of the '80s video-game Pacman. Using a bricolage approach to analyse intervie
Externí odkaz:
http://arxiv.org/abs/2312.09688
A common method to study deep learning systems is to use simplified model representations--for example, using singular value decomposition to visualize the model's hidden states in a lower dimensional space. This approach assumes that the results of
Externí odkaz:
http://arxiv.org/abs/2312.03656
Autor:
Carvalho, Wilka, Saraiva, Andre, Filos, Angelos, Lampinen, Andrew Kyle, Matthey, Loic, Lewis, Richard L., Lee, Honglak, Singh, Satinder, Rezende, Danilo J., Zoran, Daniel
The Option Keyboard (OK) was recently proposed as a method for transferring behavioral knowledge across tasks. OK transfers knowledge by adaptively combining subsets of known behaviors using Successor Features (SFs) and Generalized Policy Improvement
Externí odkaz:
http://arxiv.org/abs/2310.15940
Large language models (LLMs) show remarkable capabilities across a variety of tasks. Despite the models only seeing text in training, several recent studies suggest that LLM representations implicitly capture aspects of the underlying grounded concep
Externí odkaz:
http://arxiv.org/abs/2310.14540