Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Winata, Genta Indra"'
Autor:
Yong, Zheng-Xin, Zhang, Ruochen, Forde, Jessica Zosa, Wang, Skyler, Cahyawijaya, Samuel, Lovenia, Holy, Winata, Genta Indra, Sutawika, Lintang, Cruz, Jan Christian Blaise, Phan, Long, Tan, Yin Lin, Aji, Alham Fikri
While code-mixing is a common linguistic practice in many parts of the world, collecting high-quality and low-cost code-mixed data remains a challenge for natural language processing (NLP) research. The proliferation of Large Language Models (LLMs) i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b954f483a5b51332d4ae8e03fc4f5a52
Autor:
Cahyawijaya, Samuel, Aji, Alham Fikri, Lovenia, Holy, Winata, Genta Indra, Wilie, Bryan, Mahendra, Rahmad, Koto, Fajri, Moeljadi, David, Vincentio, Karissa, Romadhony, Ade, Purwarianti, Ayu
At the center of the underlying issues that halt Indonesian natural language processing (NLP) research advancement, we find data scarcity. Resources in Indonesian languages, especially the local ones, are extremely scarce and underrepresented. Many I
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8cdefc3dabdbbc6fe0868d73eee680a8
http://arxiv.org/abs/2207.10524
http://arxiv.org/abs/2207.10524
Autor:
Srivastava, Aarohi, Rastogi, Abhinav, Rao, Abhishek, Shoeb, Abu Awal Md, Abid, Abubakar, Fisch, Adam, Brown, Adam R., Santoro, Adam, Gupta, Aditya, Garriga-Alonso, Adrià, Kluska, Agnieszka, Lewkowycz, Aitor, Agarwal, Akshat, Power, Alethea, Ray, Alex, Warstadt, Alex, Kocurek, Alexander W., Safaya, Ali, Tazarv, Ali, Xiang, Alice, Parrish, Alicia, Nie, Allen, Hussain, Aman, Askell, Amanda, Dsouza, Amanda, Slone, Ambrose, Rahane, Ameet, Iyer, Anantharaman S., Andreassen, Anders, Madotto, Andrea, Santilli, Andrea, Stuhlmüller, Andreas, Dai, Andrew, La, Andrew, Lampinen, Andrew, Zou, Andy, Jiang, Angela, Chen, Angelica, Vuong, Anh, Gupta, Animesh, Gottardi, Anna, Norelli, Antonio, Venkatesh, Anu, Gholamidavoodi, Arash, Tabassum, Arfa, Menezes, Arul, Kirubarajan, Arun, Mullokandov, Asher, Sabharwal, Ashish, Herrick, Austin, Efrat, Avia, Erdem, Aykut, Karakaş, Ayla, Roberts, B. Ryan, Loe, Bao Sheng, Zoph, Barret, Bojanowski, Bartłomiej, Özyurt, Batuhan, Hedayatnia, Behnam, Neyshabur, Behnam, Inden, Benjamin, Stein, Benno, Ekmekci, Berk, Lin, Bill Yuchen, Howald, Blake, Orinion, Bryan, Diao, Cameron, Dour, Cameron, Stinson, Catherine, Argueta, Cedrick, Ramírez, César Ferri, Singh, Chandan, Rathkopf, Charles, Meng, Chenlin, Baral, Chitta, Wu, Chiyu, Callison-Burch, Chris, Waites, Chris, Voigt, Christian, Manning, Christopher D., Potts, Christopher, Ramirez, Cindy, Rivera, Clara E., Siro, Clemencia, Raffel, Colin, Ashcraft, Courtney, Garbacea, Cristina, Sileo, Damien, Garrette, Dan, Hendrycks, Dan, Kilman, Dan, Roth, Dan, Freeman, Daniel, Khashabi, Daniel, Levy, Daniel, González, Daniel Moseguí, Perszyk, Danielle, Hernandez, Danny, Chen, Danqi, Ippolito, Daphne, Gilboa, Dar, Dohan, David, Drakard, David, Jurgens, David, Datta, Debajyoti, Ganguli, Deep, Emelin, Denis, Kleyko, Denis, Yuret, Deniz, Chen, Derek, Tam, Derek, Hupkes, Dieuwke, Misra, Diganta, Buzan, Dilyar, Mollo, Dimitri Coelho, Yang, Diyi, Lee, Dong-Ho, Schrader, Dylan, Shutova, Ekaterina, Cubuk, Ekin Dogus, Segal, Elad, Hagerman, Eleanor, Barnes, Elizabeth, Donoway, Elizabeth, Pavlick, Ellie, Rodola, Emanuele, Lam, Emma, Chu, Eric, Tang, Eric, Erdem, Erkut, Chang, Ernie, Chi, Ethan A., Dyer, Ethan, Jerzak, Ethan, Kim, Ethan, Manyasi, Eunice Engefu, Zheltonozhskii, Evgenii, Xia, Fanyue, Siar, Fatemeh, Martínez-Plumed, Fernando, Happé, Francesca, Chollet, Francois, Rong, Frieda, Mishra, Gaurav, Winata, Genta Indra, de Melo, Gerard, Kruszewski, Germán, Parascandolo, Giambattista, Mariani, Giorgio, Wang, Gloria, Jaimovitch-López, Gonzalo, Betz, Gregor, Gur-Ari, Guy, Galijasevic, Hana, Kim, Hannah, Rashkin, Hannah, Hajishirzi, Hannaneh, Mehta, Harsh, Bogar, Hayden, Shevlin, Henry, Schütze, Hinrich, Yakura, Hiromu, Zhang, Hongming, Wong, Hugh Mee, Ng, Ian, Noble, Isaac, Jumelet, Jaap, Geissinger, Jack, Kernion, Jackson, Hilton, Jacob, Lee, Jaehoon, Fisac, Jaime Fernández, Simon, James B., Koppel, James, Zheng, James, Zou, James, Kocoń, Jan, Thompson, Jana, Wingfield, Janelle, Kaplan, Jared, Radom, Jarema, Sohl-Dickstein, Jascha, Phang, Jason, Wei, Jason, Yosinski, Jason, Novikova, Jekaterina, Bosscher, Jelle, Marsh, Jennifer, Kim, Jeremy, Taal, Jeroen, Engel, Jesse, Alabi, Jesujoba, Xu, Jiacheng, Song, Jiaming, Tang, Jillian, Waweru, Joan, Burden, John, Miller, John, Balis, John U., Batchelder, Jonathan, Berant, Jonathan, Frohberg, Jörg, Rozen, Jos, Hernandez-Orallo, Jose, Boudeman, Joseph, Guerr, Joseph, Jones, Joseph, Tenenbaum, Joshua B., Rule, Joshua S., Chua, Joyce, Kanclerz, Kamil, Livescu, Karen, Krauth, Karl, Gopalakrishnan, Karthik, Ignatyeva, Katerina, Markert, Katja, Dhole, Kaustubh D., Gimpel, Kevin, Omondi, Kevin, Mathewson, Kory, Chiafullo, Kristen, Shkaruta, Ksenia, Shridhar, Kumar, McDonell, Kyle, Richardson, Kyle, Reynolds, Laria, Gao, Leo, Zhang, Li, Dugan, Liam, Qin, Lianhui, Contreras-Ochando, Lidia, Morency, Louis-Philippe, Moschella, Luca, Lam, Lucas, Noble, Lucy, Schmidt, Ludwig, He, Luheng, Colón, Luis Oliveros, Metz, Luke, Şenel, Lütfi Kerem, Bosma, Maarten, Sap, Maarten, ter Hoeve, Maartje, Farooqi, Maheen, Faruqui, Manaal, Mazeika, Mantas, Baturan, Marco, Marelli, Marco, Maru, Marco, Quintana, Maria Jose Ramírez, Tolkiehn, Marie, Giulianelli, Mario, Lewis, Martha, Potthast, Martin, Leavitt, Matthew L., Hagen, Matthias, Schubert, Mátyás, Baitemirova, Medina Orduna, Arnaud, Melody, McElrath, Melvin, Yee, Michael A., Cohen, Michael, Gu, Michael, Ivanitskiy, Michael, Starritt, Michael, Strube, Michael, Swędrowski, Michał, Bevilacqua, Michele, Yasunaga, Michihiro, Kale, Mihir, Cain, Mike, Xu, Mimee, Suzgun, Mirac, Walker, Mitch, Tiwari, Mo, Bansal, Mohit, Aminnaseri, Moin, Geva, Mor, Gheini, Mozhdeh, T, Mukund Varma, Peng, Nanyun, Chi, Nathan A., Lee, Nayeon, Krakover, Neta Gur-Ari, Cameron, Nicholas, Roberts, Nicholas, Doiron, Nick, Martinez, Nicole, Nangia, Nikita, Deckers, Niklas, Muennighoff, Niklas, Keskar, Nitish Shirish, Iyer, Niveditha S., Constant, Noah, Fiedel, Noah, Wen, Nuan, Zhang, Oliver, Agha, Omar, Elbaghdadi, Omar, Levy, Omer, Evans, Owain, Casares, Pablo Antonio Moreno, Doshi, Parth, Fung, Pascale, Liang, Paul Pu, Vicol, Paul, Alipoormolabashi, Pegah, Liao, Peiyuan, Liang, Percy, Chang, Peter, Eckersley, Peter, Htut, Phu Mon, Hwang, Pinyu, Miłkowski, Piotr, Patil, Piyush, Pezeshkpour, Pouya, Oli, Priti, Mei, Qiaozhu, Lyu, Qing, Chen, Qinlang, Banjade, Rabin, Rudolph, Rachel Etta, Gabriel, Raefer, Habacker, Rahel, Risco, Ramon, Millière, Raphaël, Garg, Rhythm, Barnes, Richard, Saurous, Rif A., Arakawa, Riku, Raymaekers, Robbe, Frank, Robert, Sikand, Rohan, Novak, Roman, Sitelew, Roman, LeBras, Ronan, Liu, Rosanne, Jacobs, Rowan, Zhang, Rui, Salakhutdinov, Ruslan, Chi, Ryan, Lee, Ryan, Stovall, Ryan, Teehan, Ryan, Yang, Rylan, Singh, Sahib, Mohammad, Saif M., Anand, Sajant, Dillavou, Sam, Shleifer, Sam, Wiseman, Sam, Gruetter, Samuel, Bowman, Samuel R., Schoenholz, Samuel S., Han, Sanghyun, Kwatra, Sanjeev, Rous, Sarah A., Ghazarian, Sarik, Ghosh, Sayan, Casey, Sean, Bischoff, Sebastian, Gehrmann, Sebastian, Schuster, Sebastian, Sadeghi, Sepideh, Hamdan, Shadi, Zhou, Sharon, Srivastava, Shashank, Shi, Sherry, Singh, Shikhar, Asaadi, Shima, Gu, Shixiang Shane, Pachchigar, Shubh, Toshniwal, Shubham, Upadhyay, Shyam, Shyamolima, Debnath, Shakeri, Siamak, Thormeyer, Simon, Melzi, Simone, Reddy, Siva, Makini, Sneha Priscilla, Lee, Soo-Hwan, Torene, Spencer, Hatwar, Sriharsha, Dehaene, Stanislas, Divic, Stefan, Ermon, Stefano, Biderman, Stella, Lin, Stephanie, Prasad, Stephen, Piantadosi, Steven T., Shieber, Stuart M., Misherghi, Summer, Kiritchenko, Svetlana, Mishra, Swaroop, Linzen, Tal, Schuster, Tal, Li, Tao, Yu, Tao, Ali, Tariq, Hashimoto, Tatsu, Wu, Te-Lin, Desbordes, Théo, Rothschild, Theodore, Phan, Thomas, Wang, Tianle, Nkinyili, Tiberius, Schick, Timo, Kornev, Timofei, Tunduny, Titus, Gerstenberg, Tobias, Chang, Trenton, Neeraj, Trishala, Khot, Tushar, Shultz, Tyler, Shaham, Uri, Misra, Vedant, Demberg, Vera, Nyamai, Victoria, Raunak, Vikas, Ramasesh, Vinay, Prabhu, Vinay Uday, Padmakumar, Vishakh, Srikumar, Vivek, Fedus, William, Saunders, William, Zhang, William, Vossen, Wout, Ren, Xiang, Tong, Xiaoyu, Zhao, Xinran, Wu, Xinyi, Shen, Xudong, Yaghoobzadeh, Yadollah, Lakretz, Yair, Song, Yangqiu, Bahri, Yasaman, Choi, Yejin, Yang, Yichi, Hao, Yiding, Chen, Yifu, Belinkov, Yonatan, Hou, Yu, Hou, Yufang, Bai, Yuntao, Seid, Zachary, Zhao, Zhuoye, Wang, Zijian, Wang, Zijie J., Wang, Zirui, Wu, Ziyi
Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabilities are as yet poorly characterized. In order to inform future resea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::372d397a08509d21a1d1e1325394e2c2
http://arxiv.org/abs/2206.04615
http://arxiv.org/abs/2206.04615
Autor:
Yong, Zheng-Xin, Schoelkopf, Hailey, Muennighoff, Niklas, Aji, Alham Fikri, Adelani, David Ifeoluwa, Almubarak, Khalid, Bari, M Saiful, Sutawika, Lintang, Kasai, Jungo, Baruwa, Ahmed, Winata, Genta Indra, Biderman, Stella, Raff, Edward, Radev, Dragomir, Nikoulina, Vassilina
The BLOOM model is a large publicly available multilingual language model, but its pretraining was limited to 46 languages. To extend the benefits of BLOOM to other languages without incurring prohibitively large costs, it is desirable to adapt BLOOM
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e34b5f6ddb59666a377b3992177e254e
Autor:
Gehrmann, Sebastian, Bhattacharjee, Abhik, Mahendiran, Abinaya, Wang, Alex, Papangelis, Alexandros, Madaan, Aman, McMillan-Major, Angelina, Shvets, Anna, Upadhyay, Ashish, Bohnet, Bernd, 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, Novikova, Jekaterina, Kanerva, Jenna, Chim, Jenny, Zhou, Jiawei, Clive, Jordan, Maynez, Joshua, Sedoc, João, Juraska, Juraj, Dhole, Kaustubh, Raghavi Chandu, Khyathi, Perez-Beltrachini, Laura, Ribeiro, Leonardo F. R., Tunstall, Lewis, Zhang, Li, Pushkarna, Mahima, Creutz, Mathias, White, Michael, Sanjay Kale, Mihir, Kamal Eddine, Moussa, Ammanamanch, Pawan Sasanka, Zhu, Qi, Puduppully, Ratish, Kriz, Reno, Shahriyar, Rifat, Mahamood, Saad, Osei, Salomey, Cahyawijaya, Samuel, Štajner, Sanja, Montella, Sebastien, Jolly, Shailza, Mille, Simon, Shen, Tianhao, Adewumi, Tosin, Raunak, Vikas, Raheja, Vipul, Nikolaev, Vitaly, Tsai, Vivian, Jernite, Yacine, Xu, Ying, Sang, Yisi, Liu, Yixin, Hou, Yufang, Hayashi, Hiroaki, Pu Liang, Paul, Dusek, Ondrej, Subramani, Nishant, Daheim, Nico, Hasan, Tahmid, Cardenas, Ronald
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:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db349df09004a2faa0351d3611c865f0
Autor:
Dai, Wenliang, Cahyawijaya, Samuel, Yu, Tiezheng, Barezi, Elham J., Xu, Peng, Yiu, Cheuk Tung Shadow, Frieske, Rita, Lovenia, Holy, Winata, Genta Indra, Chen, Qifeng, Ma, Xiaojuan, Shi, Bertram E., Fung, Pascale
With the rise of deep learning and intelligent vehicle, the smart assistant has become an essential in-car component to facilitate driving and provide extra functionalities. In-car smart assistants should be able to process general as well as car-rel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::daf68589490f6001739e4377cea5de0f
Autor:
Cahyawijaya, Samuel, Lovenia, Holy, Aji, Alham Fikri, Winata, Genta Indra, Wilie, Bryan, Mahendra, Rahmad, Wibisono, Christian, Romadhony, Ade, Vincentio, Karissa, Koto, Fajri, Santoso, Jennifer, Moeljadi, David, Wirawan, Cahya, Hudi, Frederikus, Parmonangan, Ivan Halim, Alfina, Ika, Wicaksono, Muhammad Satrio, Putra, Ilham Firdausi, Rahmadani, Samsul, Oenang, Yulianti, Septiandri, Ali Akbar, Jaya, James, Dhole, Kaustubh D., Suryani, Arie Ardiyanti, Putri, Rifki Afina, Su, Dan, Stevens, Keith, Nityasya, Made Nindyatama, Adilazuarda, Muhammad Farid, Ignatius, Ryan, Diandaru, Ryandito, Yu, Tiezheng, Ghifari, Vito, Dai, Wenliang, Xu, Yan, Damapuspita, Dyah, Tho, Cuk, Karo, Ichwanul Muslim Karo, Fatyanosa, Tirana Noor, Ji, Ziwei, Fung, Pascale, Neubig, Graham, Baldwin, Timothy, Ruder, Sebastian, Sujaini, Herry, Sakti, Sakriani, Purwarianti, Ayu
We present NusaCrowd, a collaborative initiative to collect and unify existing resources for Indonesian languages, including opening access to previously non-public resources. Through this initiative, we have brought together 137 datasets and 118 sta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::832ddf6c44bc7f224117505463aed02d
Autor:
Dhole, Kaustubh D., Gangal, Varun, Gehrmann, Sebastian, Gupta, Aadesh, Li, Zhenhao, Mahamood, Saad, Mahendiran, Abinaya, Mille, Simon, Shrivastava, Ashish, Tan, Samson, Wu, Tongshuang, Sohl-Dickstein, Jascha, Choi, Jinho D., Hovy, Eduard, Dusek, Ondrej, Ruder, Sebastian, Anand, Sajant, Aneja, Nagender, Banjade, Rabin, Barthe, Lisa, Behnke, Hanna, Berlot-Attwell, Ian, Boyle, Connor, Brun, Caroline, Cabezudo, Marco Antonio Sobrevilla, Cahyawijaya, Samuel, Chapuis, Emile, Che, Wanxiang, Choudhary, Mukund, Clauss, Christian, Colombo, Pierre, Cornell, Filip, Dagan, Gautier, Das, Mayukh, Dixit, Tanay, Dopierre, Thomas, Dray, Paul-Alexis, Dubey, Suchitra, Ekeinhor, Tatiana, Di Giovanni, Marco, Goyal, Tanya, Gupta, Rishabh, Hamla, Louanes, Han, Sang, Harel-Canada, Fabrice, Honore, Antoine, Jindal, Ishan, Joniak, Przemyslaw K., Kleyko, Denis, Kovatchev, Venelin, Krishna, Kalpesh, Kumar, Ashutosh, Langer, Stefan, Lee, Seungjae Ryan, Levinson, Corey James, Liang, Hualou, Liang, Kaizhao, Liu, Zhexiong, Lukyanenko, Andrey, Marivate, Vukosi, de Melo, Gerard, Meoni, Simon, Meyer, Maxime, Mir, Afnan, Moosavi, Nafise Sadat, Muennighoff, Niklas, Mun, Timothy Sum Hon, Murray, Kenton, Namysl, Marcin, Obedkova, Maria, Oli, Priti, Pasricha, Nivranshu, Pfister, Jan, Plant, Richard, Prabhu, Vinay, Pais, Vasile, Qin, Libo, Raji, Shahab, Rajpoot, Pawan Kumar, Raunak, Vikas, Rinberg, Roy, Roberts, Nicolas, Rodriguez, Juan Diego, Roux, Claude, S., Vasconcellos P. H., Sai, Ananya B., Schmidt, Robin M., Scialom, Thomas, Sefara, Tshephisho, Shamsi, Saqib N., Shen, Xudong, Shi, Haoyue, Shi, Yiwen, Shvets, Anna, Siegel, Nick, Sileo, Damien, Simon, Jamie, Singh, Chandan, Sitelew, Roman, Soni, Priyank, Sorensen, Taylor, Soto, William, Srivastava, Aman, Srivatsa, KV Aditya, Sun, Tony, T, Mukund Varma, Tabassum, A, Tan, Fiona Anting, Teehan, Ryan, Tiwari, Mo, Tolkiehn, Marie, Wang, Athena, Wang, Zijian, Wang, Gloria, Wang, Zijie J., Wei, Fuxuan, Wilie, Bryan, Winata, Genta Indra, Wu, Xinyi, Wydmański, Witold, Xie, Tianbao, Yaseen, Usama, Yee, Michael A., Zhang, Jing, Zhang, Yue
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained on. In this paper, we present NL-Augmenter, a new participatory Python
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5686d761c2fcfd73ec8183a98c7c1803
http://arxiv.org/abs/2112.02721
http://arxiv.org/abs/2112.02721
Autor:
Winata, Genta Indra, Madotto, Andrea, Lin, Zhaojiang, Liu, Rosanne, Yosinski, Jason, Fung, Pascale
General-purpose language models have demonstrated impressive capabilities, performing on par with state-of-the-art approaches on a range of downstream natural language processing (NLP) tasks and benchmarks when inferring instructions from very few ex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b960219a08a6027d6f09a03aa3c2ca9e
http://arxiv.org/abs/2109.07684
http://arxiv.org/abs/2109.07684
Autor:
Cahyawijaya, Samuel, Winata, Genta Indra, Lovenia, Holy, Wilie, Bryan, Dai, Wenliang, Ishii, Etsuko, Fung, Pascale
While the recent advances in deep neural networks (DNN) bring remarkable success, the computational cost also increases considerably. In this paper, we introduce Greenformer, a toolkit to accelerate the computation of neural networks through matrix f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e449bb7e907132286b13aef9026b3bd