Zobrazeno 1 - 10
of 2 602
pro vyhledávání: '"Adlam, A."'
Autor:
Adlam, Emily
Recent developments in foundations of physics have given rise to a class of views suggesting that physically meaningful descriptions must always be relativized to a physical perspective. In this article I distinguish between strong physical perspecti
Externí odkaz:
http://arxiv.org/abs/2410.13819
Autor:
Adlam, Emily
In theories with a diffeomorphism symmetry, such as general relativity and canonical quantum gravity, it is often proposed that the empirical content is encoded in relational observables. But how do relational observables actually make contact with e
Externí odkaz:
http://arxiv.org/abs/2410.05508
Autor:
Adlam, Emily
I distinguish between pure self-locating credences and superficially self-locating credences, and argue that there is never any rationally compelling way to assign pure self-locating credences. I first argue that from a practical point of view, pure
Externí odkaz:
http://arxiv.org/abs/2409.05259
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
Autor:
Adlam, Emily
Publikováno v:
Philosophy of Physics 2(1): 9, 1-23, 2024
In this paper we seek to understand what current knowledge of entanglement entropies suggests about the appropriate way to interpret the covariant entropy bound. We first begin by arguing that just as in the classical case, a universal bound on the v
Externí odkaz:
http://arxiv.org/abs/2407.20458
Autor:
Adlam, Emily
I suggest that the current situation in quantum field theory (QFT) provides some reason to question the universal validity of ontological reductionism. I argue that the renormalization group flow is reversible except at fixed points, which makes the
Externí odkaz:
http://arxiv.org/abs/2407.20457
In the transfer learning paradigm models learn useful representations (or features) during a data-rich pretraining stage, and then use the pretrained representation to improve model performance on data-scarce downstream tasks. In this work, we explor
Externí odkaz:
http://arxiv.org/abs/2404.12481
Autor:
Adlam, Emily
This article uses the existing literature on the panpsychist combination problem as a starting point to think about how to address a structurally similar combination problem in relational quantum mechanics. I note some similarities and differences be
Externí odkaz:
http://arxiv.org/abs/2401.15790
Autor:
Ridley, Michael, Adlam, Emily
We investigate two types of temporal symmetry in quantum mechanics. The first type, time symmetry, refers to the inclusion of opposite time orientations on an equivalent physical footing. The second, event symmetry, refers to the inclusion of all tim
Externí odkaz:
http://arxiv.org/abs/2312.13524
Autor:
Singh, Avi, Co-Reyes, John D., Agarwal, Rishabh, Anand, Ankesh, Patil, Piyush, Garcia, Xavier, Liu, Peter J., Harrison, James, Lee, Jaehoon, Xu, Kelvin, Parisi, Aaron, Kumar, Abhishek, Alemi, Alex, Rizkowsky, Alex, Nova, Azade, Adlam, Ben, Bohnet, Bernd, Elsayed, Gamaleldin, Sedghi, Hanie, Mordatch, Igor, Simpson, Isabelle, Gur, Izzeddin, Snoek, Jasper, Pennington, Jeffrey, Hron, Jiri, Kenealy, Kathleen, Swersky, Kevin, Mahajan, Kshiteej, Culp, Laura, Xiao, Lechao, Bileschi, Maxwell L., Constant, Noah, Novak, Roman, Liu, Rosanne, Warkentin, Tris, Qian, Yundi, Bansal, Yamini, Dyer, Ethan, Neyshabur, Behnam, Sohl-Dickstein, Jascha, Fiedel, Noah
Fine-tuning language models~(LMs) on human-generated data remains a prevalent practice. However, the performance of such models is often limited by the quantity and diversity of high-quality human data. In this paper, we explore whether we can go bey
Externí odkaz:
http://arxiv.org/abs/2312.06585