Zobrazeno 1 - 10
of 28 003
pro vyhledávání: '"A, Nigam"'
Autor:
Katz-Samuels, Julian, Li, Zheng, Yun, Hyokun, Nigam, Priyanka, Xu, Yi, Petricek, Vaclav, Yin, Bing, Chilimbi, Trishul
The ability of large language models (LLMs) to execute complex instructions is essential for their real-world applications. However, several recent studies indicate that LLMs struggle with challenging instructions. In this paper, we propose Evolution
Externí odkaz:
http://arxiv.org/abs/2410.07513
Autor:
Steinberg, Ethan, Wornow, Michael, Bedi, Suhana, Fries, Jason Alan, McDermott, Matthew B. A., Shah, Nigam H.
The growing demand for machine learning in healthcare requires processing increasingly large electronic health record (EHR) datasets, but existing pipelines are not computationally efficient or scalable. In this paper, we introduce meds_reader, an op
Externí odkaz:
http://arxiv.org/abs/2409.09095
Autor:
Nigam, Dhruv
Deep neural network(DNN) based classifiers do extremely well in discriminating between observations, resulting in higher ROC AUC and accuracy metrics, but their outputs are often miscalibrated with respect to true event likelihoods. Post-hoc calibrat
Externí odkaz:
http://arxiv.org/abs/2409.02446
Autor:
Tandon, Abhishek, Sharma, Geetanjali, Jaswal, Gaurav, Nigam, Aditya, Ramachandra, Raghavendra
Recent studies have emphasized the potential of forehead-crease patterns as an alternative for face, iris, and periocular recognition, presenting contactless and convenient solutions, particularly in situations where faces are covered by surgical mas
Externí odkaz:
http://arxiv.org/abs/2408.15693
We revisit the phase diagram of the dimerized XXZ spin-$\frac{1}{2}$ chain with nearest-neighbor couplings which was studied numerically in Phys. Rev. B 106, L201106 (2022). The model has isotropic $XY$ couplings which have a uniform value and $ZZ$ c
Externí odkaz:
http://arxiv.org/abs/2408.14474
Autor:
Koprucu, Nursena, Nigam, Meher Shashwat, Xu, Shicheng, Abere, Biruk, Dominici, Gabriele, Rodriguez, Andrew, Vadgama, Sharvaree, Inal, Berfin, Tono, Alberto
Inspired by Geoffrey Hinton emphasis on generative modeling, To recognize shapes, first learn to generate them, we explore the use of 3D diffusion models for object classification. Leveraging the density estimates from these models, our approach, the
Externí odkaz:
http://arxiv.org/abs/2408.06693
We study a set of many-body wave-functions of Fermions that are naturally written using momentum space basis and allow for quantum superposition of Fermion occupancy, $\{n_{\bf k}\}$. This {enables} us to capture the fluctuations of the Fermi-surface
Externí odkaz:
http://arxiv.org/abs/2408.00834
Man\v{c}inska and Roberson~[FOCS'20] showed that two graphs are quantum isomorphic if and only if they are homomorphism indistinguishable over the class of planar graphs. Atserias et al.~[JCTB'19] proved that quantum isomorphism is undecidable in gen
Externí odkaz:
http://arxiv.org/abs/2407.10635
Autor:
Tan, Ting Fang, Elangovan, Kabilan, Ong, Jasmine, Shah, Nigam, Sung, Joseph, Wong, Tien Yin, Xue, Lan, Liu, Nan, Wang, Haibo, Kuo, Chang Fu, Chesterman, Simon, Yeong, Zee Kin, Ting, Daniel SW
A comprehensive qualitative evaluation framework for large language models (LLM) in healthcare that expands beyond traditional accuracy and quantitative metrics needed. We propose 5 key aspects for evaluation of LLMs: Safety, Consensus, Objectivity,
Externí odkaz:
http://arxiv.org/abs/2407.07666
Autor:
Low, Yen Sia, Jackson, Michael L., Hyde, Rebecca J., Brown, Robert E., Sanghavi, Neil M., Baldwin, Julian D., Pike, C. William, Muralidharan, Jananee, Hui, Gavin, Alexander, Natasha, Hassan, Hadeel, Nene, Rahul V., Pike, Morgan, Pokrzywa, Courtney J., Vedak, Shivam, Yan, Adam Paul, Yao, Dong-han, Zipursky, Amy R., Dinh, Christina, Ballentine, Philip, Derieg, Dan C., Polony, Vladimir, Chawdry, Rehan N., Davies, Jordan, Hyde, Brigham B., Shah, Nigam H., Gombar, Saurabh
Evidence to guide healthcare decisions is often limited by a lack of relevant and trustworthy literature as well as difficulty in contextualizing existing research for a specific patient. Large language models (LLMs) could potentially address both ch
Externí odkaz:
http://arxiv.org/abs/2407.00541