Zobrazeno 1 - 10
of 18 262
pro vyhledávání: '"P Schäffer"'
Autor:
Hung, Nguyen N., Fry, A. A. Schaeffer
We propose and present evidence for a conjectural global-local phenomenon concerning the $p$-rationality of $p$-height-zero characters. Specifically, if $\chi$ is a height-zero character of a finite group $G$ and $D$ is a defect group of the $p$-bloc
Externí odkaz:
http://arxiv.org/abs/2412.05703
Autor:
Hughes, John, Price, Sara, Lynch, Aengus, Schaeffer, Rylan, Barez, Fazl, Koyejo, Sanmi, Sleight, Henry, Jones, Erik, Perez, Ethan, Sharma, Mrinank
We introduce Best-of-N (BoN) Jailbreaking, a simple black-box algorithm that jailbreaks frontier AI systems across modalities. BoN Jailbreaking works by repeatedly sampling variations of a prompt with a combination of augmentations - such as random s
Externí odkaz:
http://arxiv.org/abs/2412.03556
Autor:
Wang, Tony T., Hughes, John, Sleight, Henry, Schaeffer, Rylan, Agrawal, Rajashree, Barez, Fazl, Sharma, Mrinank, Mu, Jesse, Shavit, Nir, Perez, Ethan
Defending large language models against jailbreaks so that they never engage in a broadly-defined set of forbidden behaviors is an open problem. In this paper, we investigate the difficulty of jailbreak-defense when we only want to forbid a narrowly-
Externí odkaz:
http://arxiv.org/abs/2412.02159
In-Context Operator Networks (ICONs) are models that learn operators across different types of PDEs using a few-shot, in-context approach. Although they show successful generalization to various PDEs, existing methods treat each data point as a singl
Externí odkaz:
http://arxiv.org/abs/2411.16063
Linear regression is often deemed inherently interpretable; however, challenges arise for high-dimensional data. We focus on further understanding how linear regression approximates nonlinear responses from high-dimensional functional data, motivated
Externí odkaz:
http://arxiv.org/abs/2411.12060
Retrograde analysis is used in game-playing programs to solve states at the end of a game, working backwards toward the start of the game. The algorithm iterates through and computes the perfect-play value for as many states as resources allow. We in
Externí odkaz:
http://arxiv.org/abs/2411.09089
We propose a novel fine-tuning method to achieve multi-operator learning through training a distributed neural operator with diverse function data and then zero-shot fine-tuning the neural network using physics-informed losses for downstream tasks. O
Externí odkaz:
http://arxiv.org/abs/2411.07239
Autor:
Nateghi, Ramin, Zhou, Ruoji, Saft, Madeline, Schnauss, Marina, Neill, Clayton, Alam, Ridwan, Handa, Nicole, Huang, Mitchell, Li, Eric V, Goldstein, Jeffery A, Schaeffer, Edward M, Nadim, Menatalla, Pourakpour, Fattaneh, Isaila, Bogdan, Felicelli, Christopher, Mehta, Vikas, Nezami, Behtash G, Ross, Ashley, Yang, Ximing, Cooper, Lee AD
Artificial intelligence may assist healthcare systems in meeting increasing demand for pathology services while maintaining diagnostic quality and reducing turnaround time and costs. We aimed to investigate the performance of an institutionally devel
Externí odkaz:
http://arxiv.org/abs/2410.23642
Autor:
Malle, Gunter, Fry, A. A. Schaeffer
The Eaton--Moret\'o conjecture extends the recently-proven Brauer height zero conjecture to blocks with non-abelian defect group, positing equality between the minimal positive heights of a block of a finite group and its defect group. Here we provid
Externí odkaz:
http://arxiv.org/abs/2410.22745
We present an innovative optical imaging system for measuring parameters of a small particle such as a macromolecule or nanoparticle at the quantum limit of sensitivity. In comparison to the conventional confocal interferometric scattering (iSCAT) ap
Externí odkaz:
http://arxiv.org/abs/2410.19417