I've got the 'Answer'! Interpretation of LLMs Hidden States in Question Answering

Autor: Goloviznina, Valeriya, Kotelnikov, Evgeny

Interpretability and explainability of AI are becoming increasingly important in light of the rapid development of large language models (LLMs). This paper investigates the interpretation of LLMs in the context of the knowledge-based question answeri

Externí odkaz: http://arxiv.org/abs/2406.02060

TabR: Tabular Deep Learning Meets Nearest Neighbors in 2023

Autor: Gorishniy, Yury, Rubachev, Ivan, Kartashev, Nikolay, Shlenskii, Daniil, Kotelnikov, Akim, Babenko, Artem

Deep learning (DL) models for tabular data problems (e.g. classification, regression) are currently receiving increasingly more attention from researchers. However, despite the recent efforts, the non-DL algorithms based on gradient-boosted decision

Externí odkaz: http://arxiv.org/abs/2307.14338

Acinar cells of the pancreas as an independent predictor of the development of postoperative pancreatic fistula: A review

Autor: Danil V. Podluzhny, Alexey G. Kotelnikov, Igor V. Sagaydak, Alexander N. Polyakov, Nikolay E. Kudashkin, Peter P. Arkhiri, Bairamali I. Sakibov, Maryam R. Tamrazova, Omar A. Egenov

Publikováno v: Современная онкология, Vol 26, Iss 2, Pp 210-217 (2024)

Analysis of data published in the modern literature on the role of the number of functioning acinar cells of the pancreas as a prognostic marker of the development of pancreatic fistula. The search for sources was carried out in the systems Clinicalt

Externí odkaz: https://doaj.org/article/0f317f7194834aedb241e4fa2c57f719

Evolution of the first metatarsophalangeal joint replacement

Autor: Gennady P. Kotelnikov, Andrey N. Nikolaenko, Ivan O. Grankin, Viktor V. Ivanov, Pavel Yu. Isaykin, Svyatoslav O. Doroganov, Denis O. Zgirsky

Publikováno v: Гений oртопедии, Vol 30, Iss 2, Pp 309-319 (2024)

Introduction The diseases of the first metatarsophalangeal (1 MTP) joint that require surgical treatment include osteoarthritis (69 %), rheumatoid arthritis (26 %), tumors, tumor-like diseases and purulent arthritis (5 %). The treatment of arthriti

Externí odkaz: https://doaj.org/article/e16ba8b5a14b4e26917721c0fe82f14a

The Profiled Feldman-Cousins technique for confidence interval construction in the presence of nuisance parameters

Autor: Acero, M. A., Acharya, B., Adamson, P., Aliaga, L., Anfimov, N., Antoshkin, A., Arrieta-Diaz, E., Asquith, L., Aurisano, A., Back, A., Backhouse, C., Baird, M., Balashov, N., Baldi, P., Bambah, B. A., Bashar, S., Bat, A., Bays, K., Bernstein, R., Bhatnagar, V., Bhattarai, D., Bhuyan, B., Bian, J., Booth, A. C., Bowles, R., Brahma, B., Bromberg, C., Buchanan, N., Butkevich, A., Calvez, S., Carroll, T. J., Catano-Mur, E., Chatla, A., Chirco, R., Choudhary, B. C., Choudhary, S., Christensen, A., Coan, T. E., Colo, M., Cremonesi, L., Davies, G. S., Derwent, P. F., Ding, P., Djurcic, Z., Dolce, M., Doyle, D., Tonguino, D. Dueñas, Dukes, E. C., Dye, A., Ehrlich, R., Elkins, M., Ewart, E., Feldman, G. J., Filip, P., Franc, J., Frank, M. J., Gallagher, H. R., Gandrajula, R., Gao, F., Giri, A., Gomes, R. A., Goodman, M. C., Grichine, V., Groh, M., Group, R., Guo, B., Habig, A., Hakl, F., Hall, A., Hartnell, J., Hatcher, R., Hausner, H., He, M., Heller, K., Hewes, V, Himmel, A., Jargowsky, B., Jarosz, J., Jediny, F., Johnson, C., Judah, M., Kakorin, I., Kaplan, D. M., Kalitkina, A., Kleykamp, J., Klimov, O., Koerner, L. W., Kolupaeva, L., Kotelnikov, S., Kralik, R., Kullenberg, Ch., Kubu, M., Kumar, A., Kuruppu, C. D., Kus, V., Lackey, T., Lang, K., Lasorak, P., Lesmeister, J., Lin, S., Lister, A., Liu, J., Lokajicek, M., Lopez, J. M. C., Mahji, R., Magill, S., Plata, M. Manrique, Mann, W. A., Manoharan, M. T., Marshak, M. L., Martinez-Casales, M., Matveev, V., Mayes, B., Mehta, B., Messier, M. D., Meyer, H., Miao, T., Mikola, V., Miller, W. H., Mishra, S., Mishra, S. R., Mislivec, A., Mohanta, R., Moren, A., Morozova, A., Mu, W., Mualem, L., Muether, M., Mulder, K., Naples, D., Nath, A., Nayak, N., Nelleri, S., Nelson, J. K., Nichol, R., Niner, E., Norman, A., Norrick, A., Nosek, T., Oh, H., Olshevskiy, A., Olson, T., Ott, J., Pal, A., Paley, J., Panda, L., Patterson, R. B., Pawloski, G., Pershey, D., Petrova, O., Petti, R., Phan, D. D., Plunkett, R. K., Pobedimov, A., Porter, J. C. C., Rafique, A., Prais, L. R., Raj, V., Rajaoalisoa, M., Ramson, B., Rebel, B., Rojas, P., Roy, P., Ryabov, V., Samoylov, O., Sanchez, M. C., Falero, S. Sánchez, Shanahan, P., Sharma, P., Shukla, S., Sheshukov, A., Singh, I., Singh, P., Singh, V., Smith, E., Smolik, J., Snopok, P., Solomey, N., Sousa, A., Soustruznik, K., Strait, M., Suter, L., Sutton, A., Swain, S., Sweeney, C., Sztuc, A., Oregui, B. Tapia, Tas, P., Temizel, B. N., Thakore, T., Thayyullathil, R. B., Thomas, J., Tiras, E., Tripathi, J., Trokan-Tenorio, J., Torun, Y., Urheim, J., Vahle, P., Vallari, Z., Vasel, J., Vrba, T., Wallbank, M., Warburton, T. K., Wetstein, M., Whittington, D., Wickremasinghe, D. A., Wieber, T., Wolcott, J., Wrobel, M., Wu, W., Xiao, Y., Yaeggy, B., Dombara, A. Yallappa, Yankelevich, A., Yonehara, K., Yu, S., Yu, Y., Zadorozhnyy, S., Zalesak, J., Zhang, Y., Zwaska, R.

Measuring observables to constrain models using maximum-likelihood estimation is fundamental to many physics experiments. Wilks' theorem provides a simple way to construct confidence intervals on model parameters, but it only applies under certain co

Externí odkaz: http://arxiv.org/abs/2207.14353