Zobrazeno 1 - 10
of 2 825
pro vyhledávání: '"Kornblith A"'
Autor:
Ciernik, Laure, Linhardt, Lorenz, Morik, Marco, Dippel, Jonas, Kornblith, Simon, Muttenthaler, Lukas
The Platonic Representation Hypothesis claims that recent foundation models are converging to a shared representation space as a function of their downstream task performance, irrespective of the objectives and data modalities used to train these mod
Externí odkaz:
http://arxiv.org/abs/2411.05561
Autor:
Sundaram, Shobhita, Fu, Stephanie, Muttenthaler, Lukas, Tamir, Netanel Y., Chai, Lucy, Kornblith, Simon, Darrell, Trevor, Isola, Phillip
Humans judge perceptual similarity according to diverse visual attributes, including scene layout, subject location, and camera pose. Existing vision models understand a wide range of semantic abstractions but improperly weigh these attributes and th
Externí odkaz:
http://arxiv.org/abs/2410.10817
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
Autor:
Hron, Jiri, Culp, Laura, Elsayed, Gamaleldin, Liu, Rosanne, Adlam, Ben, Bileschi, Maxwell, Bohnet, Bernd, Co-Reyes, JD, Fiedel, Noah, Freeman, C. Daniel, Gur, Izzeddin, Kenealy, Kathleen, Lee, Jaehoon, Liu, Peter J., Mishra, Gaurav, Mordatch, Igor, Nova, Azade, Novak, Roman, Parisi, Aaron, Pennington, Jeffrey, Rizkowsky, Alex, Simpson, Isabelle, Sedghi, Hanie, Sohl-dickstein, Jascha, Swersky, Kevin, Vikram, Sharad, Warkentin, Tris, Xiao, Lechao, Xu, Kelvin, Snoek, Jasper, Kornblith, Simon
While many capabilities of language models (LMs) improve with increased training budget, the influence of scale on hallucinations is not yet fully understood. Hallucinations come in many forms, and there is no universally accepted definition. We thus
Externí odkaz:
http://arxiv.org/abs/2408.07852
In the emergency department (ED), patients undergo triage and multiple laboratory tests before diagnosis. This time-consuming process causes ED crowding which impacts patient mortality, medical errors, staff burnout, etc. This work proposes (time) co
Externí odkaz:
http://arxiv.org/abs/2402.13448
Neither the hype exemplified in some exaggerated claims about deep neural networks (DNNs), nor the gloom expressed by Bowers et al. do DNNs as models in vision science justice: DNNs rapidly evolve, and today's limitations are often tomorrow's success
Externí odkaz:
http://arxiv.org/abs/2312.05355
Autor:
Nguyen, Thao, Kornblith, Simon
Neural network representations contain structure beyond what was present in the training labels. For instance, representations of images that are visually or semantically similar tend to lie closer to each other than to dissimilar images, regardless
Externí odkaz:
http://arxiv.org/abs/2311.07864
Autor:
Freeman, C. Daniel, Culp, Laura, Parisi, Aaron, Bileschi, Maxwell L, Elsayed, Gamaleldin F, Rizkowsky, Alex, Simpson, Isabelle, Alemi, Alex, Nova, Azade, Adlam, Ben, Bohnet, Bernd, Mishra, Gaurav, Sedghi, Hanie, Mordatch, Igor, Gur, Izzeddin, Lee, Jaehoon, Co-Reyes, JD, Pennington, Jeffrey, Xu, Kelvin, Swersky, Kevin, Mahajan, Kshiteej, Xiao, Lechao, Liu, Rosanne, Kornblith, Simon, Constant, Noah, Liu, Peter J., Novak, Roman, Qian, Yundi, Fiedel, Noah, Sohl-Dickstein, Jascha
We introduce and study the problem of adversarial arithmetic, which provides a simple yet challenging testbed for language model alignment. This problem is comprised of arithmetic questions posed in natural language, with an arbitrary adversarial str
Externí odkaz:
http://arxiv.org/abs/2311.07587
Autor:
Sucholutsky, Ilia, Muttenthaler, Lukas, Weller, Adrian, Peng, Andi, Bobu, Andreea, Kim, Been, Love, Bradley C., Cueva, Christopher J., Grant, Erin, Groen, Iris, Achterberg, Jascha, Tenenbaum, Joshua B., Collins, Katherine M., Hermann, Katherine L., Oktar, Kerem, Greff, Klaus, Hebart, Martin N., Cloos, Nathan, Kriegeskorte, Nikolaus, Jacoby, Nori, Zhang, Qiuyi, Marjieh, Raja, Geirhos, Robert, Chen, Sherol, Kornblith, Simon, Rane, Sunayana, Konkle, Talia, O'Connell, Thomas P., Unterthiner, Thomas, Lampinen, Andrew K., Müller, Klaus-Robert, Toneva, Mariya, Griffiths, Thomas L.
Biological and artificial information processing systems form representations of the world that they can use to categorize, reason, plan, navigate, and make decisions. How can we measure the similarity between the representations formed by these dive
Externí odkaz:
http://arxiv.org/abs/2310.13018
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-10 (2024)
Abstract The release of GPT-4 and other large language models (LLMs) has the potential to transform healthcare. However, existing research evaluating LLM performance on real-world clinical notes is limited. Here, we conduct a highly-powered study to
Externí odkaz:
https://doaj.org/article/518fbdf717084364b1ea33afc1f98785
