Zobrazeno 1 - 10
of 3 435
pro vyhledávání: '"A. Shandilya"'
Autor:
Shandilya, Anurag, Bhat, Swapnil, Gautam, Akshat, Yadav, Subhash, Bhatt, Siddharth, Mehta, Deval, Jadhav, Kshitij
Generative models have proven to be very effective in generating synthetic medical images and find applications in downstream tasks such as enhancing rare disease datasets, long-tailed dataset augmentation, and scaling machine learning algorithms. Fo
Externí odkaz:
http://arxiv.org/abs/2411.17535
Autor:
Flågan, Sigurd, Itoi, Joe, Shandilya, Prasoon K., Kavatamane, Vinaya K., Mitchell, Matthew, Lake, David P., Barclay, Paul E.
Photoinduced modification of second-harmonic generation mediated by nitrogen vacancy (NV) centres in a diamond cavity is observed. Excitation of NV centres quenches the device's second-harmonic emission, and is attributed to modification of $\chi^{(2
Externí odkaz:
http://arxiv.org/abs/2412.06792
Autor:
Shandilya, Prasoon K., Kavatamane, Vinaya K., Flågan, Sigurd, Lake, David P., Sukachev, Denis, Barclay, Paul E.
The photodynamics of diamond nitrogen-vacancy (NV) centers limits their performance in many quantum technologies. Quenching of photoluminescence, which degrades NV readout, is commonly ascribed to a dark state that is not fully understood. Using a na
Externí odkaz:
http://arxiv.org/abs/2411.10638
Autor:
Soni, Aditya, Das, Mayukh, Parayil, Anjaly, Ghosh, Supriyo, Shandilya, Shivam, Cheng, Ching-An, Gopal, Vishak, Khairy, Sami, Mittag, Gabriel, Hosseinkashi, Yasaman, Bansal, Chetan
The difficulty of exploring and training online on real production systems limits the scope of real-time online data/feedback-driven decision making. The most feasible approach is to adopt offline reinforcement learning from limited trajectory sample
Externí odkaz:
http://arxiv.org/abs/2411.06815
The spin-valley or Kramers qubit promises significantly enhanced spin-valley lifetimes due to strong coupling of the electrons' spin to their momentum (valley) degrees of freedom. In transition metal dichalcogenides (TMDCs) such spin-valley locking i
Externí odkaz:
http://arxiv.org/abs/2410.21814
Autor:
Gupta, Taneesh, Shandilya, Shivam, Zhang, Xuchao, Ghosh, Supriyo, Bansal, Chetan, Yao, Huaxiu, Rajmohan, Saravan
The use of large language models (LLMs) as evaluators has garnered significant attention due to their potential to rival human-level evaluations in long-form response assessments. However, current LLM evaluators rely heavily on static, human-defined
Externí odkaz:
http://arxiv.org/abs/2410.21545
Autor:
Shandilya, Bhargav, Palmer, Alexis
The data and compute requirements of current language modeling technology pose challenges for the processing and analysis of low-resource languages. Declarative linguistic knowledge has the potential to partially bridge this data scarcity gap by prov
Externí odkaz:
http://arxiv.org/abs/2410.00387
The rapid increase in unstructured data across various fields has made multi-document comprehension and summarization a critical task. Traditional approaches often fail to capture relevant context, maintain logical consistency, and extract essential
Externí odkaz:
http://arxiv.org/abs/2409.18454
Autor:
Shandilya, Shivam, Xia, Menglin, Ghosh, Supriyo, Jiang, Huiqiang, Zhang, Jue, Wu, Qianhui, Rühle, Victor
The increasing prevalence of large language models (LLMs) such as GPT-4 in various applications has led to a surge in the size of prompts required for optimal performance, leading to challenges in computational efficiency. Prompt compression aims to
Externí odkaz:
http://arxiv.org/abs/2409.13035
Synchronization of oscillators is ubiquitous in nature. Often, the synchronized oscillators couple directly, yet in some cases synchronization can arise from their parametric interactions. Here, we theoretically predict and experimentally demonstrate
Externí odkaz:
http://arxiv.org/abs/2409.05388