Zobrazeno 1 - 10
of 23 709
pro vyhledávání: '"A, Gur"'
We study the complexity of testing properties of quantum channels. First, we show that testing identity to any channel $\mathcal N: \mathbb C^{d_{\mathrm{in}} \times d_{\mathrm{in}}} \to \mathbb C^{d_{\mathrm{out}} \times d_{\mathrm{out}}}$ in diamon
Externí odkaz:
http://arxiv.org/abs/2409.12566
Autor:
Furuta, Hiroki, Lee, Kuang-Huei, Gu, Shixiang Shane, Matsuo, Yutaka, Faust, Aleksandra, Zen, Heiga, Gur, Izzeddin
Many algorithms for aligning LLMs with human preferences assume that human preferences are binary and deterministic. However, it is reasonable to think that they can vary with different individuals, and thus should be distributional to reflect the fi
Externí odkaz:
http://arxiv.org/abs/2409.06691
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:
Limonad, Lior, Fournier, Fabiana, Díaz, Juan Manuel Vera, Skarbovsky, Inna, Gur, Shlomit, Lazcano, Raquel
Publikováno v:
AIFin workshop at ECAI 2024
Large language models (LLMs) play a vital role in almost every domain in today's organizations. In the context of this work, we highlight the use of LLMs for sentiment analysis (SA) and explainability. Specifically, we contribute a novel technique to
Externí odkaz:
http://arxiv.org/abs/2407.19922
Autor:
Everett, Katie, Xiao, Lechao, Wortsman, Mitchell, Alemi, Alexander A., Novak, Roman, Liu, Peter J., Gur, Izzeddin, Sohl-Dickstein, Jascha, Kaelbling, Leslie Pack, Lee, Jaehoon, Pennington, Jeffrey
Robust and effective scaling of models from small to large width typically requires the precise adjustment of many algorithmic and architectural details, such as parameterization and optimizer choices. In this work, we propose a new perspective on pa
Externí odkaz:
http://arxiv.org/abs/2407.05872
Estimating the eigenstate properties of quantum many-body systems is a long-standing, challenging problem for both classical and quantum computing. For the task of eigenstate preparation, quantum signal processing (QSP) has established near-optimal q
Externí odkaz:
http://arxiv.org/abs/2406.04307
Autor:
Feld, Leon G., Boehme, Simon C., Sabisch, Sebastian, Frenkel, Nadav, Yazdani, Nuri, Morad, Viktoriia, Zhu, Chenglian, Svyrydenko, Mariia, Tao, Rui, Bodnarchuk, Maryna, Lubin, Gur, Kazes, Miri, Wood, Vanessa, Oron, Dan, Rainò, Gabriele, Kovalenko, Maksym V.
In lead halide perovskites (APbX3), the effect of the A-site cation on optical and electronic properties has initially been thought to be marginal. Yet, evidence of beneficial effects on solar cell performance and light emission is accumulating. Here
Externí odkaz:
http://arxiv.org/abs/2404.15920
Autor:
Gur, Tom, Jahanara, Mohammad Mahdi, Khodabandeh, Mohammad Mahdi, Rajgopal, Ninad, Salamatian, Bahar, Shinkar, Igor
We continue the study of doubly-efficient proof systems for verifying agnostic PAC learning, for which we obtain the following results. - We construct an interactive protocol for learning the $t$ largest Fourier characters of a given function $f \col
Externí odkaz:
http://arxiv.org/abs/2404.08158
We construct perfect zero-knowledge probabilistically checkable proofs (PZK-PCPs) for every language in #P. This is the first construction of a PZK-PCP for any language outside BPP. Furthermore, unlike previous constructions of (statistical) zero-kno
Externí odkaz:
http://arxiv.org/abs/2403.11941
We study "incentivized exploration" (IE) in social learning problems where the principal (a recommendation algorithm) can leverage information asymmetry to incentivize sequentially-arriving agents to take exploratory actions. We identify posterior sa
Externí odkaz:
http://arxiv.org/abs/2402.13338