Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Guan, Melody"'
Autor:
OpenAI, Jaech, Aaron, Kalai, Adam, Lerer, Adam, Richardson, Adam, El-Kishky, Ahmed, Low, Aiden, Helyar, Alec, Madry, Aleksander, Beutel, Alex, Carney, Alex, Iftimie, Alex, Karpenko, Alex, Passos, Alex Tachard, Neitz, Alexander, Prokofiev, Alexander, Wei, Alexander, Tam, Allison, Bennett, Ally, Kumar, Ananya, Saraiva, Andre, Vallone, Andrea, Duberstein, Andrew, Kondrich, Andrew, Mishchenko, Andrey, Applebaum, Andy, Jiang, Angela, Nair, Ashvin, Zoph, Barret, Ghorbani, Behrooz, Rossen, Ben, Sokolowsky, Benjamin, Barak, Boaz, McGrew, Bob, Minaiev, Borys, Hao, Botao, Baker, Bowen, Houghton, Brandon, McKinzie, Brandon, Eastman, Brydon, Lugaresi, Camillo, Bassin, Cary, Hudson, Cary, Li, Chak Ming, de Bourcy, Charles, Voss, Chelsea, Shen, Chen, Zhang, Chong, Koch, Chris, Orsinger, Chris, Hesse, Christopher, Fischer, Claudia, Chan, Clive, Roberts, Dan, Kappler, Daniel, Levy, Daniel, Selsam, Daniel, Dohan, David, Farhi, David, Mely, David, Robinson, David, Tsipras, Dimitris, Li, Doug, Oprica, Dragos, Freeman, Eben, Zhang, Eddie, Wong, Edmund, Proehl, Elizabeth, Cheung, Enoch, Mitchell, Eric, Wallace, Eric, Ritter, Erik, Mays, Evan, Wang, Fan, Such, Felipe Petroski, Raso, Filippo, Leoni, Florencia, Tsimpourlas, Foivos, Song, Francis, von Lohmann, Fred, Sulit, Freddie, Salmon, Geoff, Parascandolo, Giambattista, Chabot, Gildas, Zhao, Grace, Brockman, Greg, Leclerc, Guillaume, Salman, Hadi, Bao, Haiming, Sheng, Hao, Andrin, Hart, Bagherinezhad, Hessam, Ren, Hongyu, Lightman, Hunter, Chung, Hyung Won, Kivlichan, Ian, O'Connell, Ian, Osband, Ian, Gilaberte, Ignasi Clavera, Akkaya, Ilge, Kostrikov, Ilya, Sutskever, Ilya, Kofman, Irina, Pachocki, Jakub, Lennon, James, Wei, Jason, Harb, Jean, Twore, Jerry, Feng, Jiacheng, Yu, Jiahui, Weng, Jiayi, Tang, Jie, Yu, Jieqi, Candela, Joaquin Quiñonero, Palermo, Joe, Parish, Joel, Heidecke, Johannes, Hallman, John, Rizzo, John, Gordon, Jonathan, Uesato, Jonathan, Ward, Jonathan, Huizinga, Joost, Wang, Julie, Chen, Kai, Xiao, Kai, Singhal, Karan, Nguyen, Karina, Cobbe, Karl, Shi, Katy, Wood, Kayla, Rimbach, Kendra, Gu-Lemberg, Keren, GuLemberg, Keren, Liu, Kevin, Lu, Kevin, Stone, Kevin, Yu, Kevin, Ahmad, Lama, Yang, Lauren, Liu, Leo, Maksin, Leon, Ho, Leyton, Fedus, Liam, Weng, Lilian, Li, Linden, McCallum, Lindsay, Held, Lindsey, Kuhn, Lorenz, Kondraciuk, Lukas, Kaiser, Lukasz, Metz, Luke, Boyd, Madelaine, Trebacz, Maja, Joglekar, Manas, Chen, Mark, Tintor, Marko, Meyer, Mason, Jones, Matt, Kaufer, Matt, Schwarzer, Max, Shah, Meghan, Yatbaz, Mehmet, Guan, Melody, Xu, Mengyuan, Yan, Mengyuan, Glaese, Mia, Chen, Mianna, Lampe, Michael, Malek, Michael, Wang, Michele, Fradin, Michelle, McClay, Mike, Pavlov, Mikhail, Wang, Miles, Wang, Mingxuan, Murati, Mira, Bavarian, Mo, Rohaninejad, Mostafa, McAleese, Nat, Chowdhury, Neil, Ryder, Nick, Tezak, Nikolas, Brown, Noam, Nachum, Ofir, Boiko, Oleg, Murk, Oleg, Watkins, Olivia, Chao, Patrick, Ashbourne, Paul, Izmailov, Pavel, Zhokhov, Peter, Dias, Rachel, Arora, Rahul, Lin, Randall, Lopes, Rapha Gontijo, Gaon, Raz, Miyara, Reah, Leike, Reimar, Hwang, Renny, Garg, Rhythm, Brown, Robin, James, Roshan, Shu, Rui, Cheu, Ryan, Greene, Ryan, Jain, Saachi, Altman, Sam, Toizer, Sam, Toyer, Sam, Miserendino, Samuel, Agarwal, Sandhini, Hernandez, Santiago, Baker, Sasha, McKinney, Scott, Yan, Scottie, Zhao, Shengjia, Hu, Shengli, Santurkar, Shibani, Chaudhuri, Shraman Ray, Zhang, Shuyuan, Fu, Siyuan, Papay, Spencer, Lin, Steph, Balaji, Suchir, Sanjeev, Suvansh, Sidor, Szymon, Broda, Tal, Clark, Aidan, Wang, Tao, Gordon, Taylor, Sanders, Ted, Patwardhan, Tejal, Sottiaux, Thibault, Degry, Thomas, Dimson, Thomas, Zheng, Tianhao, Garipov, Timur, Stasi, Tom, Bansal, Trapit, Creech, Trevor, Peterson, Troy, Eloundou, Tyna, Qi, Valerie, Kosaraju, Vineet, Monaco, Vinnie, Pong, Vitchyr, Fomenko, Vlad, Zheng, Weiyi, Zhou, Wenda, McCabe, Wes, Zaremba, Wojciech, Dubois, Yann, Lu, Yinghai, Chen, Yining, Cha, Young, Bai, Yu, He, Yuchen, Zhang, Yuchen, Wang, Yunyun, Shao, Zheng, Li, Zhuohan
The o1 model series is trained with large-scale reinforcement learning to reason using chain of thought. These advanced reasoning capabilities provide new avenues for improving the safety and robustness of our models. In particular, our models can re
Externí odkaz:
http://arxiv.org/abs/2412.16720
Autor:
Guan, Melody Y., Joglekar, Manas, Wallace, Eric, Jain, Saachi, Barak, Boaz, Heylar, Alec, Dias, Rachel, Vallone, Andrea, Ren, Hongyu, Wei, Jason, Chung, Hyung Won, Toyer, Sam, Heidecke, Johannes, Beutel, Alex, Glaese, Amelia
As large-scale language models increasingly impact safety-critical domains, ensuring their reliable adherence to well-defined principles remains a fundamental challenge. We introduce Deliberative Alignment, a new paradigm that directly teaches the mo
Externí odkaz:
http://arxiv.org/abs/2412.16339
Autor:
Goodman, Emmett D., Patel, Krishna K., Zhang, Yilun, Locke, William, Kennedy, Chris J., Mehrotra, Rohan, Ren, Stephen, Guan, Melody Y., Downing, Maren, Chen, Hao Wei, Clark, Jevin Z., Brat, Gabriel A., Yeung, Serena
Open procedures represent the dominant form of surgery worldwide. Artificial intelligence (AI) has the potential to optimize surgical practice and improve patient outcomes, but efforts have focused primarily on minimally invasive techniques. Our work
Externí odkaz:
http://arxiv.org/abs/2112.07219
Autor:
Zhang, Michael, Cheng, Xiaotian, Copeland, Daniel, Desai, Arjun, Guan, Melody Y., Brat, Gabriel A., Yeung, Serena
Open, or non-laparoscopic surgery, represents the vast majority of all operating room procedures, but few tools exist to objectively evaluate these techniques at scale. Current efforts involve human expert-based visual assessment. We leverage advance
Externí odkaz:
http://arxiv.org/abs/2012.06948
Intense recent discussions have focused on how to provide individuals with control over when their data can and cannot be used --- the EU's Right To Be Forgotten regulation is an example of this effort. In this paper we initiate a framework studying
Externí odkaz:
http://arxiv.org/abs/1907.05012
Autor:
Guan, Melody Y., Valiant, Gregory
Recent work on adversarial examples has demonstrated that most natural inputs can be perturbed to fool even state-of-the-art machine learning systems. But does this happen for humans as well? In this work, we investigate: what fraction of natural ins
Externí odkaz:
http://arxiv.org/abs/1906.01040
Knowing when a classifier's prediction can be trusted is useful in many applications and critical for safely using AI. While the bulk of the effort in machine learning research has been towards improving classifier performance, understanding when a c
Externí odkaz:
http://arxiv.org/abs/1805.11783
We propose Efficient Neural Architecture Search (ENAS), a fast and inexpensive approach for automatic model design. In ENAS, a controller learns to discover neural network architectures by searching for an optimal subgraph within a large computationa
Externí odkaz:
http://arxiv.org/abs/1802.03268
Autor:
Guan, Melody Y., Jiang, Heinrich
We analyze the $K$-armed bandit problem where the reward for each arm is a noisy realization based on an observed context under mild nonparametric assumptions. We attain tight results for top-arm identification and a sublinear regret of $\widetilde{O
Externí odkaz:
http://arxiv.org/abs/1801.01750
The standard content-based attention mechanism typically used in sequence-to-sequence models is computationally expensive as it requires the comparison of large encoder and decoder states at each time step. In this work, we propose an alternative att
Externí odkaz:
http://arxiv.org/abs/1707.00110