Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Ammanamanchi, Pawan Sasanka"'
Autor:
Biderman, Stella, Schoelkopf, Hailey, Sutawika, Lintang, Gao, Leo, Tow, Jonathan, Abbasi, Baber, Aji, Alham Fikri, Ammanamanchi, Pawan Sasanka, Black, Sidney, Clive, Jordan, DiPofi, Anthony, Etxaniz, Julen, Fattori, Benjamin, Forde, Jessica Zosa, Foster, Charles, Hsu, Jeffrey, Jaiswal, Mimansa, Lee, Wilson Y., Li, Haonan, Lovering, Charles, Muennighoff, Niklas, Pavlick, Ellie, Phang, Jason, Skowron, Aviya, Tan, Samson, Tang, Xiangru, Wang, Kevin A., Winata, Genta Indra, Yvon, François, Zou, Andy
Effective evaluation of language models remains an open challenge in NLP. Researchers and engineers face methodological issues such as the sensitivity of models to evaluation setup, difficulty of proper comparisons across methods, and the lack of rep
Externí odkaz:
http://arxiv.org/abs/2405.14782
Autor:
Sanchez, Guillaume, Fan, Honglu, Spangher, Alexander, Levi, Elad, Ammanamanchi, Pawan Sasanka, Biderman, Stella
Classifier-Free Guidance (CFG) has recently emerged in text-to-image generation as a lightweight technique to encourage prompt-adherence in generations. In this work, we demonstrate that CFG can be used broadly as an inference-time technique in pure
Externí odkaz:
http://arxiv.org/abs/2306.17806
Autor:
Workshop, BigScience, Scao, Teven Le, Fan, Angela, Akiki, Christopher, Pavlick, Ellie, Ilić, Suzana, Hesslow, Daniel, Castagné, Roman, Luccioni, Alexandra Sasha, Yvon, François, Gallé, Matthias, Tow, Jonathan, Rush, Alexander M., Biderman, Stella, Webson, Albert, Ammanamanchi, Pawan Sasanka, Wang, Thomas, Sagot, Benoît, Muennighoff, Niklas, del Moral, Albert Villanova, Ruwase, Olatunji, Bawden, Rachel, Bekman, Stas, McMillan-Major, Angelina, Beltagy, Iz, Nguyen, Huu, Saulnier, Lucile, Tan, Samson, Suarez, Pedro Ortiz, Sanh, Victor, Laurençon, Hugo, Jernite, Yacine, Launay, Julien, Mitchell, Margaret, Raffel, Colin, Gokaslan, Aaron, Simhi, Adi, Soroa, Aitor, Aji, Alham Fikri, Alfassy, Amit, Rogers, Anna, Nitzav, Ariel Kreisberg, Xu, Canwen, Mou, Chenghao, Emezue, Chris, Klamm, Christopher, Leong, Colin, van Strien, Daniel, Adelani, David Ifeoluwa, Radev, Dragomir, Ponferrada, Eduardo González, Levkovizh, Efrat, Kim, Ethan, Natan, Eyal Bar, De Toni, Francesco, Dupont, Gérard, Kruszewski, Germán, Pistilli, Giada, Elsahar, Hady, Benyamina, Hamza, Tran, Hieu, Yu, Ian, Abdulmumin, Idris, Johnson, Isaac, Gonzalez-Dios, Itziar, de la Rosa, Javier, Chim, Jenny, Dodge, Jesse, Zhu, Jian, Chang, Jonathan, Frohberg, Jörg, Tobing, Joseph, Bhattacharjee, Joydeep, Almubarak, Khalid, Chen, Kimbo, Lo, Kyle, Von Werra, Leandro, Weber, Leon, Phan, Long, allal, Loubna Ben, Tanguy, Ludovic, Dey, Manan, Muñoz, Manuel Romero, Masoud, Maraim, Grandury, María, Šaško, Mario, Huang, Max, Coavoux, Maximin, Singh, Mayank, Jiang, Mike Tian-Jian, Vu, Minh Chien, Jauhar, Mohammad A., Ghaleb, Mustafa, Subramani, Nishant, Kassner, Nora, Khamis, Nurulaqilla, Nguyen, Olivier, Espejel, Omar, de Gibert, Ona, Villegas, Paulo, Henderson, Peter, Colombo, Pierre, Amuok, Priscilla, Lhoest, Quentin, Harliman, Rheza, Bommasani, Rishi, López, Roberto Luis, Ribeiro, Rui, Osei, Salomey, Pyysalo, Sampo, Nagel, Sebastian, Bose, Shamik, Muhammad, Shamsuddeen Hassan, Sharma, Shanya, Longpre, Shayne, Nikpoor, Somaieh, Silberberg, Stanislav, Pai, Suhas, Zink, Sydney, Torrent, Tiago Timponi, Schick, Timo, Thrush, Tristan, Danchev, Valentin, Nikoulina, Vassilina, Laippala, Veronika, Lepercq, Violette, Prabhu, Vrinda, Alyafeai, Zaid, Talat, Zeerak, Raja, Arun, Heinzerling, Benjamin, Si, Chenglei, Taşar, Davut Emre, Salesky, Elizabeth, Mielke, Sabrina J., Lee, Wilson Y., Sharma, Abheesht, Santilli, Andrea, Chaffin, Antoine, Stiegler, Arnaud, Datta, Debajyoti, Szczechla, Eliza, Chhablani, Gunjan, Wang, Han, Pandey, Harshit, Strobelt, Hendrik, Fries, Jason Alan, Rozen, Jos, Gao, Leo, Sutawika, Lintang, Bari, M Saiful, Al-shaibani, Maged S., Manica, Matteo, Nayak, Nihal, Teehan, Ryan, Albanie, Samuel, Shen, Sheng, Ben-David, Srulik, Bach, Stephen H., Kim, Taewoon, Bers, Tali, Fevry, Thibault, Neeraj, Trishala, Thakker, Urmish, Raunak, Vikas, Tang, Xiangru, Yong, Zheng-Xin, Sun, Zhiqing, Brody, Shaked, Uri, Yallow, Tojarieh, Hadar, Roberts, Adam, Chung, Hyung Won, Tae, Jaesung, Phang, Jason, Press, Ofir, Li, Conglong, Narayanan, Deepak, Bourfoune, Hatim, Casper, Jared, Rasley, Jeff, Ryabinin, Max, Mishra, Mayank, Zhang, Minjia, Shoeybi, Mohammad, Peyrounette, Myriam, Patry, Nicolas, Tazi, Nouamane, Sanseviero, Omar, von Platen, Patrick, Cornette, Pierre, Lavallée, Pierre François, Lacroix, Rémi, Rajbhandari, Samyam, Gandhi, Sanchit, Smith, Shaden, Requena, Stéphane, Patil, Suraj, Dettmers, Tim, Baruwa, Ahmed, Singh, Amanpreet, Cheveleva, Anastasia, Ligozat, Anne-Laure, Subramonian, Arjun, Névéol, Aurélie, Lovering, Charles, Garrette, Dan, Tunuguntla, Deepak, Reiter, Ehud, Taktasheva, Ekaterina, Voloshina, Ekaterina, Bogdanov, Eli, Winata, Genta Indra, Schoelkopf, Hailey, Kalo, Jan-Christoph, Novikova, Jekaterina, Forde, Jessica Zosa, Clive, Jordan, Kasai, Jungo, Kawamura, Ken, Hazan, Liam, Carpuat, Marine, Clinciu, Miruna, Kim, Najoung, Cheng, Newton, Serikov, Oleg, Antverg, Omer, van der Wal, Oskar, Zhang, Rui, Zhang, Ruochen, Gehrmann, Sebastian, Mirkin, Shachar, Pais, Shani, Shavrina, Tatiana, Scialom, Thomas, Yun, Tian, Limisiewicz, Tomasz, Rieser, Verena, Protasov, Vitaly, Mikhailov, Vladislav, Pruksachatkun, Yada, Belinkov, Yonatan, Bamberger, Zachary, Kasner, Zdeněk, Rueda, Alice, Pestana, Amanda, Feizpour, Amir, Khan, Ammar, Faranak, Amy, Santos, Ana, Hevia, Anthony, Unldreaj, Antigona, Aghagol, Arash, Abdollahi, Arezoo, Tammour, Aycha, HajiHosseini, Azadeh, Behroozi, Bahareh, Ajibade, Benjamin, Saxena, Bharat, Ferrandis, Carlos Muñoz, McDuff, Daniel, Contractor, Danish, Lansky, David, David, Davis, Kiela, Douwe, Nguyen, Duong A., Tan, Edward, Baylor, Emi, Ozoani, Ezinwanne, Mirza, Fatima, Ononiwu, Frankline, Rezanejad, Habib, Jones, Hessie, Bhattacharya, Indrani, Solaiman, Irene, Sedenko, Irina, Nejadgholi, Isar, Passmore, Jesse, Seltzer, Josh, Sanz, Julio Bonis, Dutra, Livia, Samagaio, Mairon, Elbadri, Maraim, Mieskes, Margot, Gerchick, Marissa, Akinlolu, Martha, McKenna, Michael, Qiu, Mike, Ghauri, Muhammed, Burynok, Mykola, Abrar, Nafis, Rajani, Nazneen, Elkott, Nour, Fahmy, Nour, Samuel, Olanrewaju, An, Ran, Kromann, Rasmus, Hao, Ryan, Alizadeh, Samira, Shubber, Sarmad, Wang, Silas, Roy, Sourav, Viguier, Sylvain, Le, Thanh, Oyebade, Tobi, Le, Trieu, Yang, Yoyo, Nguyen, Zach, Kashyap, Abhinav Ramesh, Palasciano, Alfredo, Callahan, Alison, Shukla, Anima, Miranda-Escalada, Antonio, Singh, Ayush, Beilharz, Benjamin, Wang, Bo, Brito, Caio, Zhou, Chenxi, Jain, Chirag, Xu, Chuxin, Fourrier, Clémentine, Periñán, Daniel León, Molano, Daniel, Yu, Dian, Manjavacas, Enrique, Barth, Fabio, Fuhrimann, Florian, Altay, Gabriel, Bayrak, Giyaseddin, Burns, Gully, Vrabec, Helena U., Bello, Imane, Dash, Ishani, Kang, Jihyun, Giorgi, John, Golde, Jonas, Posada, Jose David, Sivaraman, Karthik Rangasai, Bulchandani, Lokesh, Liu, Lu, Shinzato, Luisa, de Bykhovetz, Madeleine Hahn, Takeuchi, Maiko, Pàmies, Marc, Castillo, Maria A, Nezhurina, Marianna, Sänger, Mario, Samwald, Matthias, Cullan, Michael, Weinberg, Michael, De Wolf, Michiel, Mihaljcic, Mina, Liu, Minna, Freidank, Moritz, Kang, Myungsun, Seelam, Natasha, Dahlberg, Nathan, Broad, Nicholas Michio, Muellner, Nikolaus, Fung, Pascale, Haller, Patrick, Chandrasekhar, Ramya, Eisenberg, Renata, Martin, Robert, Canalli, Rodrigo, Su, Rosaline, Su, Ruisi, Cahyawijaya, Samuel, Garda, Samuele, Deshmukh, Shlok S, Mishra, Shubhanshu, Kiblawi, Sid, Ott, Simon, Sang-aroonsiri, Sinee, Kumar, Srishti, Schweter, Stefan, Bharati, Sushil, Laud, Tanmay, Gigant, Théo, Kainuma, Tomoya, Kusa, Wojciech, Labrak, Yanis, Bajaj, Yash Shailesh, Venkatraman, Yash, Xu, Yifan, Xu, Yingxin, Xu, Yu, Tan, Zhe, Xie, Zhongli, Ye, Zifan, Bras, Mathilde, Belkada, Younes, Wolf, Thomas
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizati
Externí odkaz:
http://arxiv.org/abs/2211.05100
Autor:
Gehrmann, Sebastian, Bhattacharjee, Abhik, Mahendiran, Abinaya, Wang, Alex, Papangelis, Alexandros, Madaan, Aman, McMillan-Major, Angelina, Shvets, Anna, Upadhyay, Ashish, Yao, Bingsheng, Wilie, Bryan, Bhagavatula, Chandra, You, Chaobin, Thomson, Craig, Garbacea, Cristina, Wang, Dakuo, Deutsch, Daniel, Xiong, Deyi, Jin, Di, Gkatzia, Dimitra, Radev, Dragomir, Clark, Elizabeth, Durmus, Esin, Ladhak, Faisal, Ginter, Filip, Winata, Genta Indra, Strobelt, Hendrik, Hayashi, Hiroaki, Novikova, Jekaterina, Kanerva, Jenna, Chim, Jenny, Zhou, Jiawei, Clive, Jordan, Maynez, Joshua, Sedoc, João, Juraska, Juraj, Dhole, Kaustubh, Chandu, Khyathi Raghavi, Perez-Beltrachini, Laura, Ribeiro, Leonardo F. R., Tunstall, Lewis, Zhang, Li, Pushkarna, Mahima, Creutz, Mathias, White, Michael, Kale, Mihir Sanjay, Eddine, Moussa Kamal, Daheim, Nico, Subramani, Nishant, Dusek, Ondrej, Liang, Paul Pu, Ammanamanchi, Pawan Sasanka, Zhu, Qi, Puduppully, Ratish, Kriz, Reno, Shahriyar, Rifat, Cardenas, Ronald, Mahamood, Saad, Osei, Salomey, Cahyawijaya, Samuel, Štajner, Sanja, Montella, Sebastien, Shailza, Jolly, Shailza, Mille, Simon, Hasan, Tahmid, Shen, Tianhao, Adewumi, Tosin, Raunak, Vikas, Raheja, Vipul, Nikolaev, Vitaly, Tsai, Vivian, Jernite, Yacine, Xu, Ying, Sang, Yisi, Liu, Yixin, Hou, Yufang
Evaluation in machine learning is usually informed by past choices, for example which datasets or metrics to use. This standardization enables the comparison on equal footing using leaderboards, but the evaluation choices become sub-optimal as better
Externí odkaz:
http://arxiv.org/abs/2206.11249
Autor:
McMillan-Major, Angelina, Osei, Salomey, Rodriguez, Juan Diego, Ammanamanchi, Pawan Sasanka, Gehrmann, Sebastian, Jernite, Yacine
Developing documentation guidelines and easy-to-use templates for datasets and models is a challenging task, especially given the variety of backgrounds, skills, and incentives of the people involved in the building of natural language processing (NL
Externí odkaz:
http://arxiv.org/abs/2108.07374
Autor:
Gehrmann, Sebastian, Adewumi, Tosin, Aggarwal, Karmanya, Ammanamanchi, Pawan Sasanka, Anuoluwapo, Aremu, Bosselut, Antoine, Chandu, Khyathi Raghavi, Clinciu, Miruna, Das, Dipanjan, Dhole, Kaustubh D., Du, Wanyu, Durmus, Esin, Dušek, Ondřej, Emezue, Chris, Gangal, Varun, Garbacea, Cristina, Hashimoto, Tatsunori, Hou, Yufang, Jernite, Yacine, Jhamtani, Harsh, Ji, Yangfeng, Jolly, Shailza, Kale, Mihir, Kumar, Dhruv, Ladhak, Faisal, Madaan, Aman, Maddela, Mounica, Mahajan, Khyati, Mahamood, Saad, Majumder, Bodhisattwa Prasad, Martins, Pedro Henrique, McMillan-Major, Angelina, Mille, Simon, van Miltenburg, Emiel, Nadeem, Moin, Narayan, Shashi, Nikolaev, Vitaly, Niyongabo, Rubungo Andre, Osei, Salomey, Parikh, Ankur, Perez-Beltrachini, Laura, Rao, Niranjan Ramesh, Raunak, Vikas, Rodriguez, Juan Diego, Santhanam, Sashank, Sedoc, João, Sellam, Thibault, Shaikh, Samira, Shimorina, Anastasia, Cabezudo, Marco Antonio Sobrevilla, Strobelt, Hendrik, Subramani, Nishant, Xu, Wei, Yang, Diyi, Yerukola, Akhila, Zhou, Jiawei
We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics. Measuring progress in NLG relies on a constantly evolving ecosystem of automated metrics, datasets, and human evaluation standards. Due to this m
Externí odkaz:
http://arxiv.org/abs/2102.01672
This paper examines the relationship between Inverse Perpetual Swap contracts, a Bitcoin derivative akin to futures and the margin funding interest rates levied on BitMEX. This paper proves the Heteroskedastic nature of funding rates and goes onto es
Externí odkaz:
http://arxiv.org/abs/1912.03270