Zobrazeno 1 - 10
of 3 909
pro vyhledávání: '"Cohen, Daniel A."'
Autor:
Nünnerich, Markus, Cohen, Daniel, Barthel, Patrick, Huber, Patrick H., Niroomand, Dorna, Retzker, Alex, Wunderlich, Christof
A novel two-qubit entangling gate for RF-controlled trapped-ion quantum processors is proposed theoretically and demonstrated experimentally. The speed of this gate is an order of magnitude higher than that of previously demonstrated two-qubit entang
Externí odkaz:
http://arxiv.org/abs/2403.04730
Explain then Rank: Scale Calibration of Neural Rankers Using Natural Language Explanations from LLMs
In search settings, calibrating the scores during the ranking process to quantities such as click-through rates or relevance levels enhances a system's usefulness and trustworthiness for downstream users. While previous research has improved this not
Externí odkaz:
http://arxiv.org/abs/2402.12276
By allowing models to predict without task-specific training, in-context learning (ICL) with pretrained LLMs has enormous potential in NLP. However, a number of problems persist in ICL. In particular, its performance is sensitive to the choice and or
Externí odkaz:
http://arxiv.org/abs/2402.11447
Epithelial monolayers are some of the best-studied models for collective cell migration due to their abundance in multicellular systems and their tractability. Experimentally, the collective migration of epithelial monolayers can be robustly steered
Externí odkaz:
http://arxiv.org/abs/2402.08700
The spatiotemporal coordination and regulation of cell proliferation is fundamental in many aspects of development and tissue maintenance. Cells have the ability to adapt their division rates in response to mechanical constraints, yet we do not fully
Externí odkaz:
http://arxiv.org/abs/2401.08805
Publikováno v:
CIKM 2023: 32nd ACM International Conference on Information and Knowledge Management
Societal biases that are contained in retrieved documents have received increased interest. Such biases, which are often prevalent in the training data and learned by the model, can cause societal harms, by misrepresenting certain groups, and by enfo
Externí odkaz:
http://arxiv.org/abs/2309.09833
Autor:
Ummel, Kevin, Poblete-Cazenave, Miguel, Akkiraju, Karthik, Graetz, Nick, Ashman, Hero, Kingdon, Cora, Tenorio, Steven Herrera, Singhal, Aaryaman "Sunny", Cohen, Daniel Aldana, Rao, Narasimha D.
Social science often relies on surveys of households and individuals. Dozens of such surveys are regularly administered by the U.S. government. However, they field independent, unconnected samples with specialized questions, limiting research questio
Externí odkaz:
http://arxiv.org/abs/2309.11512
When employing mechanistic models to study biological phenomena, practical parameter identifiability is important for making accurate predictions across wide range of unseen scenarios, as well as for understanding the underlying mechanisms. In this w
Externí odkaz:
http://arxiv.org/abs/2309.01476
Publikováno v:
Phys. Rev. Res. 6, 013217 (2024)
Dynamical decoupling is effective in reducing gate errors in most quantum computation platforms and is therefore projected to play an essential role in future fault-tolerant constructions. In superconducting circuits, however, it has proven difficult
Externí odkaz:
http://arxiv.org/abs/2306.09149
Autor:
Staudenmaier, Nicolas, Vijayakumar-Sreeja, Anjusha, Genov, Genko, Cohen, Daniel, Findler, Christoph, Lang, Johannes, Retzker, Alex, Jelezko, Fedor, Oviedo-Casado, Santiago
Publikováno v:
Phys. Rev. Lett. 131, 150801 (2023)
Diffusion noise represents a major constraint to successful liquid state nano-NMR spectroscopy. Using the Fisher information as a faithful measure, we theoretically calculate and experimentally show that phase sensitive protocols are superior in most
Externí odkaz:
http://arxiv.org/abs/2305.14881