A Neural Network Solves, Explains, and Generates University Math Problems by Program Synthesis and Few-Shot Learning at Human Level

Posted by kmcclain MIT

Kavli Affiliate: Avi Shporer | First 5 Authors: Iddo Drori, Sarah Zhang, Reece Shuttleworth, Leonard Tang, Albert Lu | Summary: We demonstrate that a neural network pre-trained on text and fine-tuned on code solves mathematics course problems, explains solutions, and generates new questions at a human level. We automatically synthesize programs using few-shot learning and […]


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A Neural Network Solves and Generates Mathematics Problems by Program Synthesis: Calculus, Differential Equations, Linear Algebra, and More

Posted by klaurent MIT

Kavli Affiliate: Avi Shporer | First 5 Authors: Iddo Drori, Sunny Tran, Roman Wang, Newman Cheng, Kevin Liu | Summary: We demonstrate that a neural network pre-trained on text and fine-tuned on code solves Mathematics problems by program synthesis. We turn questions into programming tasks, automatically generate programs, and then execute them, perfectly solving university-level […]


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QEMind: Alibaba’s Submission to the WMT21 Quality Estimation Shared Task

Posted by klaurent Peking

Kavli Affiliate: Ke Wang | First 5 Authors: Jiayi Wang, Ke Wang, Boxing Chen, Yu Zhao, Weihua Luo | Summary: Quality Estimation, as a crucial step of quality control for machine translation, has been explored for years. The goal is to investigate automatic methods for estimating the quality of machine translation results without reference translations. […]


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Chaos by Magic

Posted by klaurent UCAS

Kavli Affiliate: Masahiro Nozaki | First 5 Authors: [#item_custom_name[1]], [#item_custom_name[2]], [#item_custom_name[3]], [#item_custom_name[4]], [#item_custom_name[5]] | Summary: There is a property of a quantum state called magic. It measures how difficult for a classical computer to simulate the state. In this paper, we study magic of states in the integrable and chaotic regimes of the higher-spin generalization […]


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Non-Equilibrating a Black Hole with Inhomogeneous Quantum Quench

Posted by klaurent UCAS

Kavli Affiliate: Masahiro Nozaki | First 5 Authors: [#item_custom_name[1]], [#item_custom_name[2]], [#item_custom_name[3]], [#item_custom_name[4]], [#item_custom_name[5]] | Summary: We study non-equilibrium processes in (1+1)-dimensional conformal field theory (CFT) after quantum quenches starting from the thermal equilibrium (Gibbs) state. Our quench protocol uses spatially inhomogeneous Hamiltonians, the Mobius and sine-square-deformed (SSD) Hamiltonians. After a quench by the Mobius Hamiltonian, […]


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DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification

Posted by Chicago

Kavli Affiliate: Brian Nord | First 5 Authors: Aleksandra Ćiprijanović, Diana Kafkes, Gregory Snyder, F. Javier Sánchez, Gabriel Nathan Perdue | Summary: With increased adoption of supervised deep learning methods for processing and analysis of cosmological survey data, the assessment of data perturbation effects (that can naturally occur in the data processing and analysis pipelines) […]


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DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification

Posted by Chicago

Kavli Affiliate: Brian Nord | First 5 Authors: Aleksandra Ćiprijanović, Diana Kafkes, Gregory Snyder, F. Javier Sánchez, Gabriel Nathan Perdue | Summary: Data processing and analysis pipelines in cosmological survey experiments introduce data perturbations that can significantly degrade the performance of deep learning-based models. Given the increased adoption of supervised deep learning methods for processing […]


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DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification

Posted by klaurent Chicago

Kavli Affiliate: Brian Nord | First 5 Authors: Aleksandra Ćiprijanović, Diana Kafkes, Gregory Snyder, F. Javier Sánchez, Gabriel Nathan Perdue | Summary: Data processing and analysis pipelines in cosmological survey experiments introduce data perturbations that can significantly degrade the performance of deep learning-based models. Given the increased adoption of supervised deep learning methods for processing […]


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Deployed MDI-QKD and Bell-State Measurements Coexisting with Standard Internet Data and Networking Equipment

Posted by klaurent Delft

Kavli Affiliate: Wolfgang Tittel | First 5 Authors: Remon C. Berrevoets, Thomas Middelburg, Raymond F. L. Vermeulen, Luca Della Chiesa, Federico Broggi | Summary: The forthcoming quantum Internet is poised to allow new applications not possible with the conventional Internet. The ability for both quantum and conventional networking equipment to coexist on the same fiber […]


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Neutrino Observations of LHAASO Sources: Present Constraints and Future Prospects

Posted by klaurent Peking

Kavli Affiliate: Zhuo Li | First 5 Authors: Tian-Qi Huang, Zhuo Li, , , | Summary: The Large High Altitude Air Shower Observatory (LHAASO) observed a dozen of gamma-ray sources with significant emission above 100 TeV, which may be strong candidates of PeVatrons. Neutrino observations are crucial to diagnose whether the gamma-ray radiative process is […]


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