Zobrazeno 1 - 10
of 20 711
pro vyhledávání: '"A. R. Thomas"'
Autor:
Seiler, Anna M., Statz, Martin, Eckel, Christian, Weimer, Isabell, Pöhls, Jonas, Watanabe, Kenji, Taniguchi, Takashi, Zhang, Fan, Weitz, R. Thomas
AB-stacked bilayer graphene has emerged as a fascinating yet simple platform for exploring macroscopic quantum phenomena of correlated electrons. Unexpectedly, an insulating phase has recently been observed when a large electric displacement field is
Externí odkaz:
http://arxiv.org/abs/2408.16628
Autor:
Falorsi, Francesca, Zhao, Shuangjie, Liu, Kejun, Eckel, Christian, Pöhls, Jonas F., Bennecke, Wiebke, Reutzel, Marcel, Mathias, Stefan, Watanabe, Kenji, Taniguchi, Takashi, Wang, Zhiyong, Polozij, Miroslav, Feng, Xinliang, Heine, Thomas, Weitz, R. Thomas
The vertical integration of multiple two-dimensional (2D) materials in heterostructures, held together by van der Waals forces, has opened unprecedented possibilities for modifying the (opto-)electronic properties of nanodevices. Graphene, with its r
Externí odkaz:
http://arxiv.org/abs/2407.11559
Chain-of-Thought (CoT) prompting has been shown to enhance the multi-step reasoning capabilities of Large Language Models (LLMs). However, debates persist about whether LLMs exhibit abstract generalization or rely on shallow heuristics when given CoT
Externí odkaz:
http://arxiv.org/abs/2407.01687
Large language models (LLMs) have shown the emergent capability of in-context learning (ICL). One line of research has explained ICL as functionally performing gradient descent. In this paper, we introduce a new way of diagnosing whether ICL is funct
Externí odkaz:
http://arxiv.org/abs/2406.18501
Autor:
Chi, Nathan A., Malchev, Teodor, Kong, Riley, Chi, Ryan A., Huang, Lucas, Chi, Ethan A., McCoy, R. Thomas, Radev, Dragomir
We introduce modeLing, a novel benchmark of Linguistics Olympiad-style puzzles which tests few-shot reasoning in AI systems. Solving these puzzles necessitates inferring aspects of a language's grammatical structure from a small number of examples. S
Externí odkaz:
http://arxiv.org/abs/2406.17038
Autor:
Seiler, Anna M., Zhumagulov, Yaroslav, Zollner, Klaus, Yoon, Chiho, Urbaniak, David, Geisenhof, Fabian R., Watanabe, Kenji, Taniguchi, Takashi, Fabian, Jaroslav, Zhang, Fan, Weitz, R. Thomas
Spin-orbit coupling (SOC) and electron-electron interaction can mutually influence each other and give rise to a plethora of intriguing phenomena in condensed matter systems. In pristine bilayer graphene, which has weak SOC, intrinsic Lifshitz transi
Externí odkaz:
http://arxiv.org/abs/2403.17140
Humans can learn new concepts from a small number of examples by drawing on their inductive biases. These inductive biases have previously been captured by using Bayesian models defined over symbolic hypothesis spaces. Is it possible to create a neur
Externí odkaz:
http://arxiv.org/abs/2402.07035
Large language models (LLMs) can produce long, coherent passages of text, suggesting that LLMs, although trained on next-word prediction, must represent the latent structure that characterizes a document. Prior work has found that internal representa
Externí odkaz:
http://arxiv.org/abs/2312.14226
Autor:
Seiler, Anna M., Jacobsen, Nils, Statz, Martin, Fernandez, Noelia, Falorsi, Francesca, Watanabe, Kenji, Taniguchi, Takashi, Dong, Zhiyu, Levitov, Leonid S., Weitz, R. Thomas
Controlling the bandstructure of Dirac materials is of wide interest in current research but has remained an outstanding challenge for systems such as monolayer graphene. In contrast, Bernal bilayer graphene (BLG) offers a highly flexible platform fo
Externí odkaz:
http://arxiv.org/abs/2311.10816
The success of methods based on artificial neural networks in creating intelligent machines seems like it might pose a challenge to explanations of human cognition in terms of Bayesian inference. We argue that this is not the case, and that in fact t
Externí odkaz:
http://arxiv.org/abs/2311.10206