Search Results - "Teehan, Ryan"

Are LLMs Prescient? A Continuous Evaluation using Daily News as the Oracle by Dai, Hui, Teehan, Ryan, Ren, Mengye

“…Many existing evaluation benchmarks for Large Language Models (LLMs) quickly become outdated due to the emergence of new models and training data. These…”
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ProCreate, Don't Reproduce! Propulsive Energy Diffusion for Creative Generation by Lu, Jack, Teehan, Ryan, Ren, Mengye

“…In this paper, we propose ProCreate, a simple and easy-to-implement method to improve sample diversity and creativity of diffusion-based image generative…”
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CoLLEGe: Concept Embedding Generation for Large Language Models by Teehan, Ryan, Lake, Brenden, Ren, Mengye

“…Current language models are unable to quickly learn new concepts on the fly, often requiring a more involved finetuning process to learn robustly. Prompting…”
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Can Language Models Employ the Socratic Method? Experiments with Code Debugging by Al-Hossami, Erfan, Bunescu, Razvan, Smith, Justin, Teehan, Ryan

“…When employing the Socratic method of teaching, instructors guide students toward solving a problem on their own rather than providing the solution directly…”
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Cut the CARP: Fishing for zero-shot story evaluation by Matiana, Shahbuland, Smith, JR, Teehan, Ryan, Castricato, Louis, Biderman, Stella, Gao, Leo, Frazier, Spencer

“…Recent advances in large-scale language models (Raffel et al., 2019; Brown et al., 2020) have brought significant qualitative and quantitative improvements in…”
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Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models by Shoeb, Abu Awal Md, Brown, Adam R, Garriga-Alonso, Adrià, Tazarv, Ali, Nie, Allen, Iyer, Anantharaman S, Madotto, Andrea, Norelli, Antonio, Gholamidavoodi, Arash, Loe, Bao Sheng, Hedayatnia, Behnam, Stinson, Catherine, Potts, Christopher, Siro, Clemencia, Garrette, Dan, Hendrycks, Dan, Gilboa, Dar, Ganguli, Deep, Yuret, Deniz, Chen, Derek, Barnes, Elizabeth, Chollet, Francois, Rong, Frieda, Gur-Ari, Guy, Hajishirzi, Hannaneh, Wong, Hugh Mee, Fisac, Jaime Fernández, Simon, James B, Zou, James, Radom, Jarema, Engel, Jesse, Xu, Jiacheng, Song, Jiaming, Frohberg, Jörg, Rozen, Jos, Boudeman, Joseph, Guerr, Joseph, Rule, Joshua S, Gimpel, Kevin, Omondi, Kevin, Mathewson, Kory, Chiafullo, Kristen, Shkaruta, Ksenia, McDonell, Kyle, Richardson, Kyle, Contreras-Ochando, Lidia, Moschella, Luca, Colón, Luis Oliveros, Bosma, Maarten, Faruqui, Manaal, Maru, Marco, Lewis, Martha, Arnaud, Melody, McElrath, Melvin, Yasunaga, Michihiro, Aminnaseri, Moin, Doiron, Nick, Muennighoff, Niklas, Evans, Owain, Casares, Pablo Antonio Moreno, Fung, Pascale, Miłkowski, Piotr, Pezeshkpour, Pouya, Mei, Qiaozhu, Chen, Qinlang, Banjade, Rabin, Millière, Raphaël, Barnes, Richard, Frank, Robert, Sitelew, Roman, Jacobs, Rowan, Zhang, Rui, Salakhutdinov, Ruslan, Lee, Ryan, Stovall, Ryan, Mohammad, Saif M, Anand, Sajant, Schoenholz, Samuel S, Han, Sanghyun, Ghosh, Sayan, Shi, Sherry, Upadhyay, Shyam, Shyamolima, Debnath, Makini, Sneha Priscilla, Hatwar, Sriharsha, Biderman, Stella, Lin, Stephanie, Shieber, Stuart M, Li, Tao, Hashimoto, Tatsu, Schick, Timo, Kornev, Timofei, Khot, Tushar, Demberg, Vera, Nyamai, Victoria, Wu, Xinyi, Lakretz, Yair, Song, Yangqiu, Hou, Yu

“…Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj Language models demonstrate both quantitative improvement and…”
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BLOOM: A 176B-Parameter Open-Access Multilingual Language Model by Scao, Teven Le, Fan, Angela, Gallé, Matthias, Webson, Albert, Wang, Thomas, Bekman, Stas, Laurençon, Hugo, Launay, Julien, Raffel, Colin, Simhi, Adi, Alfassy, Amit, Rogers, Anna, Leong, Colin, van Strien, Daniel, Ponferrada, Eduardo González, Levkovizh, Efrat, Benyamina, Hamza, Tran, Hieu, Yu, Ian, Johnson, Isaac, Bhattacharjee, Joydeep, Von Werra, Leandro, Dey, Manan, Jiang, Mike Tian-Jian, Jauhar, Mohammad A, Kassner, Nora, Pyysalo, Sampo, Pai, Suhas, Schick, Timo, Thrush, Tristan, Nikoulina, Vassilina, Laippala, Veronika, Heinzerling, Benjamin, Taşar, Davut Emre, Salesky, Elizabeth, Lee, Wilson Y, Szczechla, Eliza, Chhablani, Gunjan, Wang, Han, Rozen, Jos, Manica, Matteo, Nayak, Nihal, Teehan, Ryan, Albanie, Samuel, Shen, Sheng, Ben-David, Srulik, Kim, Taewoon, Neeraj, Trishala, Roberts, Adam, Tae, Jaesung, Phang, Jason, Press, Ofir, Ryabinin, Max, Peyrounette, Myriam, Patry, Nicolas, Cornette, Pierre, Dettmers, Tim, Ligozat, Anne-Laure, Névéol, Aurélie, Taktasheva, Ekaterina, Kalo, Jan-Christoph, Clive, Jordan, Kim, Najoung, Mirkin, Shachar, Pais, Shani, Pruksachatkun, Yada, Pestana, Amanda, Faranak, Amy, Santos, Ana, HajiHosseini, Azadeh, Ajibade, Benjamin, Saxena, Bharat, Nguyen, Duong A, Rezanejad, Habib, Bhattacharya, Indrani, Nejadgholi, Isar, McKenna, Michael, Burynok, Mykola, Rajani, Nazneen, Samuel, Olanrewaju, Kromann, Rasmus, Shubber, Sarmad, Viguier, Sylvain, Miranda-Escalada, Antonio, Singh, Ayush, Manjavacas, Enrique, Barth, Fabio, Bulchandani, Lokesh, Nezhurina, Marianna, Liu, Minna, Kang, Myungsun, Dahlberg, Nathan, Chandrasekhar, Ramya, Eisenberg, Renata, Canalli, Rodrigo, Schweter, Stefan, Laud, Tanmay, Kainuma, Tomoya, Venkatraman, Yash, Xu, Yingxin

“…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…”
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Multitask Prompted Training Enables Zero-Shot Task Generalization by Sanh, Victor, Webson, Albert, Raffel, Colin, Bach, Stephen H, Sutawika, Lintang, Alyafeai, Zaid, Chaffin, Antoine, Stiegler, Arnaud, Scao, Teven Le, Raja, Arun, Dey, Manan, Bari, M Saiful, Xu, Canwen, Thakker, Urmish, Sharma, Shanya Sharma, Szczechla, Eliza, Kim, Taewoon, Chhablani, Gunjan, Nayak, Nihal, Datta, Debajyoti, Chang, Jonathan, Jiang, Mike Tian-Jian, Wang, Han, Manica, Matteo, Shen, Sheng, Yong, Zheng Xin, Pandey, Harshit, Bawden, Rachel, Wang, Thomas, Neeraj, Trishala, Rozen, Jos, Sharma, Abheesht, Santilli, Andrea, Fevry, Thibault, Fries, Jason Alan, Teehan, Ryan, Bers, Tali, Biderman, Stella, Gao, Leo, Wolf, Thomas, Rush, Alexander M

“…Large language models have recently been shown to attain reasonable zero-shot generalization on a diverse set of tasks (Brown et al., 2020). It has been…”
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NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation by Dhole, Kaustubh D, Gangal, Varun, Gupta, Aadesh, Mahendiran, Abinaya, Mille, Simon, Shrivastava, Ashish, Tan, Samson, Wu, Tongshuang, Hovy, Eduard, Dusek, Ondrej, Ruder, Sebastian, Anand, Sajant, Aneja, Nagender, Barthe, Lisa, Boyle, Connor, Brun, Caroline, Cabezudo, Marco Antonio Sobrevilla, Cahyawijaya, Samuel, Chapuis, Emile, Che, Wanxiang, Choudhary, Mukund, Clauss, Christian, Colombo, Pierre, Cornell, Filip, Das, Mayukh, Dixit, Tanay, Dopierre, Thomas, Dray, Paul-Alexis, Dubey, Suchitra, Di Giovanni, Marco, Goyal, Tanya, Gupta, Rishabh, 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, Liang, Kaizhao, Liu, Zhexiong, Lukyanenko, Andrey, Marivate, Vukosi, de Melo, Gerard, Meoni, Simon, Meyer, Maxime, Mir, Afnan, Muennighoff, Niklas, Mun, Timothy Sum Hon, Murray, Kenton, Namysl, Marcin, Obedkova, Maria, Pfister, Jan, Plant, Richard, Prabhu, Vinay, Qin, Libo, Raji, Shahab, Rajpoot, Pawan Kumar, Rinberg, Roy, 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, Siegel, Nick, Sileo, Damien, Simon, Jamie, Singh, Chandan, Soni, Priyank, Sorensen, Taylor, Soto, William, Srivastava, Aman, Sun, Tony, 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, 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…”
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