Zobrazeno 1 - 10
of 14 289
pro vyhledávání: '"Panchenko, A. A."'
Autor:
Chekalina, Viktoriia, Rudenko, Anna, Mezentsev, Gleb, Mikhalev, Alexander, Panchenko, Alexander, Oseledets, Ivan
The performance of Transformer models has been enhanced by increasing the number of parameters and the length of the processed text. Consequently, fine-tuning the entire model becomes a memory-intensive process. High-performance methods for parameter
Externí odkaz:
http://arxiv.org/abs/2410.07383
Publikováno v:
International Conference on Applications of Natural Language to Information Systems, pages: 107-118, year: 2024, organization: Springer
While being one of the most popular question types, simple questions such as "Who is the author of Cinderella?", are still not completely solved. Surprisingly, even the most powerful modern Large Language Models are prone to errors when dealing with
Externí odkaz:
http://arxiv.org/abs/2409.15902
Autor:
Vazhentsev, Artem, Fadeeva, Ekaterina, Xing, Rui, Panchenko, Alexander, Nakov, Preslav, Baldwin, Timothy, Panov, Maxim, Shelmanov, Artem
Uncertainty quantification (UQ) is a perspective approach to detecting Large Language Model (LLM) hallucinations and low quality output. In this work, we address one of the challenges of UQ in generation tasks that arises from the conditional depende
Externí odkaz:
http://arxiv.org/abs/2408.10692
Autor:
Amaro, Rommie, Åqvist, Johan, Bahar, Ivet, Battistini, Federica, Bellaiche, Adam, Beltran, Daniel, Biggin, Philip C., Bonomi, Massimiliano, Bowman, Gregory R., Bryce, Richard, Bussi, Giovanni, Carloni, Paolo, Case, David, Cavalli, Andrea, Chang, Chie-En A., Cheatham III, Thomas E., Cheung, Margaret S., Chipot, Cris, Chong, Lillian T., Choudhary, Preeti, Cisneros, Gerardo Andres, Clementi, Cecilia, Collepardo-Guevara, Rosana, Coveney, Peter, Covino, Roberto, Crawford, T. Daniel, Peraro, Matteo Dal, de Groot, Bert, Delemotte, Lucie, De Vivo, Marco, Essex, Jonathan, Fraternali, Franca, Gao, Jiali, Gelpí, Josep Lluís, Gervasio, Francesco Luigi, Gonzalez-Nilo, Fernando Danilo, Grubmüller, Helmut, Guenza, Marina, Guzman, Horacio V., Harris, Sarah, Head-Gordon, Teresa, Hernandez, Rigoberto, Hospital, Adam, Huang, Niu, Huang, Xuhui, Hummer, Gerhard, Iglesias-Fernández, Javier, Jensen, Jan H., Jha, Shantenu, Jiao, Wanting, Jorgensen, William L., Kamerlin, Shina Caroline Lynn, Khalid, Syma, Laughton, Charles, Levitt, Michael, Limongelli, Vittorio, Lindahl, Erik, Lindorff-Larsen, Kresten, Loverde, Sharon, Lundborg, Magnus, Luo, Yun Lyna, Luque, Francisco Javier, Lynch, Charlotte I., MacKerell, Alexander, Magistrato, Alessandra, Marrink, Siewert J., Martin, Hugh, McCammon, J. Andrew, Merz, Kenneth, Moliner, Vicent, Mulholland, Adrian, Murad, Sohail, Naganathan, Athi N., Nangia, Shikha, Noe, Frank, Noy, Agnes, Oláh, Julianna, O'Mara, Megan, Ondrechen, Mary Jo, Onuchic, José N., Onufriev, Alexey, Osuna, Silvia, Panchenko, Anna R., Pantano, Sergio, Parish, Carol, Parrinello, Michele, Perez, Alberto, Perez-Acle, Tomas, Perilla, Juan R., Pettitt, B. Montgomery, Pietropalo, Adriana, Piquemal, Jean-Philip, Poma, Adolfo, Praprotnik, Matej, Ramos, Maria J., Ren, Pengyu, Reuter, Nathalie, Roitberg, Adrian, Rosta, Edina, Rovira, Carme, Roux, Benoit, Röthlisberger, Ursula, Sanbonmatsu, Karissa Y., Schlick, Tamar, Shaytan, Alexey K., Simmerling, Carlos, Smith, Jeremy C., Sugita, Yuji, Świderek, Katarzyna, Taiji, Makoto, Tao, Peng, Tikhonova, Irina G., Tirado-Rives, Julian, Tunón, Inaki, Van Der Kamp, Marc W., Van der Spoel, David, Velankar, Sameer, Voth, Gregory A., Wade, Rebecca, Warshel, Ariel, Welborn, Valerie Vaissier, Wetmore, Stacey, Wong, Chung F., Yang, Lee-Wei, Zacharias, Martin, Orozco, Modesto
This letter illustrates the opinion of the molecular dynamics (MD) community on the need to adopt a new FAIR paradigm for the use of molecular simulations. It highlights the necessity of a collaborative effort to create, establish, and sustain a data
Externí odkaz:
http://arxiv.org/abs/2407.16584
Autor:
Yimam, Seid Muhie, Dementieva, Daryna, Fischer, Tim, Moskovskiy, Daniil, Rizwan, Naquee, Saha, Punyajoy, Roy, Sarthak, Semmann, Martin, Panchenko, Alexander, Biemann, Chris, Mukherjee, Animesh
Despite regulations imposed by nations and social media platforms, such as recent EU regulations targeting digital violence, abusive content persists as a significant challenge. Existing approaches primarily rely on binary solutions, such as outright
Externí odkaz:
http://arxiv.org/abs/2406.19543
In this work, we present a conceptually simple yet powerful baseline for the multimodal dialog task, an S3 model, that achieves near state-of-the-art results on two compelling leaderboards: MMMU and AI Journey Contest 2023. The system is based on a p
Externí odkaz:
http://arxiv.org/abs/2406.18305
Autor:
Vashurin, Roman, Fadeeva, Ekaterina, Vazhentsev, Artem, Rvanova, Lyudmila, Tsvigun, Akim, Vasilev, Daniil, Xing, Rui, Sadallah, Abdelrahman Boda, Grishchenkov, Kirill, Petrakov, Sergey, Panchenko, Alexander, Baldwin, Timothy, Nakov, Preslav, Panov, Maxim, Shelmanov, Artem
Uncertainty quantification (UQ) is a critical component of machine learning (ML) applications. The rapid proliferation of large language models (LLMs) has stimulated researchers to seek efficient and effective approaches to UQ for text generation. As
Externí odkaz:
http://arxiv.org/abs/2406.15627
State-of-the-art trainable machine translation evaluation metrics like xCOMET achieve high correlation with human judgment but rely on large encoders (up to 10.7B parameters), making them computationally expensive and inaccessible to researchers with
Externí odkaz:
http://arxiv.org/abs/2406.14553
Autor:
Rykov, Elisei, Shishkina, Yana, Petrushina, Kseniia, Titova, Kseniia, Petrakov, Sergey, Panchenko, Alexander
In this paper, we present our novel systems developed for the SemEval-2024 hallucination detection task. Our investigation spans a range of strategies to compare model predictions with reference standards, encompassing diverse baselines, the refineme
Externí odkaz:
http://arxiv.org/abs/2404.06137
Text detoxification is a textual style transfer (TST) task where a text is paraphrased from a toxic surface form, e.g. featuring rude words, to the neutral register. Recently, text detoxification methods found their applications in various task such
Externí odkaz:
http://arxiv.org/abs/2404.02037