Zobrazeno 1 - 10
of 4 428
pro vyhledávání: '"CLARK, KEVIN"'
We present Direct Reward Fine-Tuning (DRaFT), a simple and effective method for fine-tuning diffusion models to maximize differentiable reward functions, such as scores from human preference models. We first show that it is possible to backpropagate
Externí odkaz:
http://arxiv.org/abs/2309.17400
What is the best paradigm to recognize objects -- discriminative inference (fast but potentially prone to shortcut learning) or using a generative model (slow but potentially more robust)? We build on recent advances in generative modeling that turn
Externí odkaz:
http://arxiv.org/abs/2309.16779
Autor:
Singhal, Karan, Tu, Tao, Gottweis, Juraj, Sayres, Rory, Wulczyn, Ellery, Hou, Le, Clark, Kevin, Pfohl, Stephen, Cole-Lewis, Heather, Neal, Darlene, Schaekermann, Mike, Wang, Amy, Amin, Mohamed, Lachgar, Sami, Mansfield, Philip, Prakash, Sushant, Green, Bradley, Dominowska, Ewa, Arcas, Blaise Aguera y, Tomasev, Nenad, Liu, Yun, Wong, Renee, Semturs, Christopher, Mahdavi, S. Sara, Barral, Joelle, Webster, Dale, Corrado, Greg S., Matias, Yossi, Azizi, Shekoofeh, Karthikesalingam, Alan, Natarajan, Vivek
Recent artificial intelligence (AI) systems have reached milestones in "grand challenges" ranging from Go to protein-folding. The capability to retrieve medical knowledge, reason over it, and answer medical questions comparably to physicians has long
Externí odkaz:
http://arxiv.org/abs/2305.09617
Autor:
Clark, Kevin, Jaini, Priyank
The excellent generative capabilities of text-to-image diffusion models suggest they learn informative representations of image-text data. However, what knowledge their representations capture is not fully understood, and they have not been thoroughl
Externí odkaz:
http://arxiv.org/abs/2303.15233
Autor:
Clark, Kevin, Guu, Kelvin, Chang, Ming-Wei, Pasupat, Panupong, Hinton, Geoffrey, Norouzi, Mohammad
Dynamic evaluation of language models (LMs) adapts model parameters at test time using gradient information from previous tokens and substantially improves LM performance. However, it requires over 3x more compute than standard inference. We present
Externí odkaz:
http://arxiv.org/abs/2212.02475
Autor:
Schmitt, Paul, Britten, Nicholas, Jeong, JiHyun, Coffey, Amelia, Clark, Kevin, Kothawade, Shweta Sunil, Grigore, Elena Corina, Khaw, Adam, Konopka, Christopher, Pham, Linh, Ryan, Kim, Schmitt, Christopher, Pandya, Aryaman, Frazzoli, Emilio
We present nuReality, a virtual reality 'VR' environment designed to test the efficacy of vehicular behaviors to communicate intent during interactions between autonomous vehicles 'AVs' and pedestrians at urban intersections. In this project we focus
Externí odkaz:
http://arxiv.org/abs/2201.04742
Autor:
Clark, Kevin M.1 kevclark@iuk.edu
Publikováno v:
Review of General Psychology. Jun2024, Vol. 28 Issue 2, p166-183. 18p.
Autor:
Larkin, Colin
Publikováno v:
Encyclopedia of Popular Music, 4 ed., 2009.
Externí odkaz:
http://www.oxfordreference.com/view/10.1093/acref/9780195313734.001.0001/acref-9780195313734-e-5024