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Timo Schick
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2020 – today
- 2024
- [c20]Abdullatif Köksal, Timo Schick, Anna Korhonen, Hinrich Schütze:
LongForm: Effective Instruction Tuning with Reverse Instructions. EMNLP (Findings) 2024: 7056-7078 - [c19]Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Omer Levy, Luke Zettlemoyer, Jason Weston, Mike Lewis:
Self-Alignment with Instruction Backtranslation. ICLR 2024 - [i29]Jane Dwivedi-Yu, Raaz Dwivedi, Timo Schick:
FairPair: A Robust Evaluation of Biases in Language Models through Paired Perturbations. CoRR abs/2404.06619 (2024) - 2023
- [j6]Gautier Izacard, Patrick S. H. Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, Edouard Grave:
Atlas: Few-shot Learning with Retrieval Augmented Language Models. J. Mach. Learn. Res. 24: 251:1-251:43 (2023) - [j5]Fabio Petroni
, Samuel Broscheit, Aleksandra Piktus, Patrick S. H. Lewis, Gautier Izacard, Lucas Hosseini, Jane Dwivedi-Yu, Maria Lomeli, Timo Schick, Michele Bevilacqua, Pierre-Emmanuel Mazaré, Armand Joulin, Edouard Grave, Sebastian Riedel:
Improving Wikipedia verifiability with AI. Nat. Mac. Intell. 5(10): 1142-1148 (2023) - [j4]Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ramakanth Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, Thomas Scialom:
Augmented Language Models: a Survey. Trans. Mach. Learn. Res. 2023 (2023) - [j3]Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ambrose Slone, Ameet Rahane, Anantharaman S. Iyer, Anders Andreassen, Andrea Madotto, Andrea Santilli, Andreas Stuhlmüller, Andrew M. Dai, Andrew La, Andrew K. Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakas, B. Ryan Roberts, Bao Sheng Loe, Barret Zoph, Bartlomiej Bojanowski, Batuhan Özyurt, Behnam Hedayatnia, Behnam Neyshabur, Benjamin Inden, Benno Stein, Berk Ekmekci, Bill Yuchen Lin, Blake Howald, Bryan Orinion, Cameron Diao, Cameron Dour, Catherine Stinson, Cedrick Argueta, Cèsar Ferri Ramírez, Chandan Singh, Charles Rathkopf, Chenlin Meng, Chitta Baral, Chiyu Wu, Chris Callison-Burch, Chris Waites, Christian Voigt, Christopher D. Manning, Christopher Potts, Cindy Ramirez, Clara E. Rivera, Clemencia Siro, Colin Raffel, Courtney Ashcraft, Cristina Garbacea, Damien Sileo, Dan Garrette, Dan Hendrycks, Dan Kilman, Dan Roth, Daniel Freeman, Daniel Khashabi, Daniel Levy, Daniel Moseguí González, Danielle Perszyk, Danny Hernandez, Danqi Chen, Daphne Ippolito, Dar Gilboa, David Dohan, David Drakard, David Jurgens, Debajyoti Datta, Deep Ganguli, Denis Emelin, Denis Kleyko, Deniz Yuret, Derek Chen, Derek Tam, Dieuwke Hupkes, Diganta Misra, Dilyar Buzan, Dimitri Coelho Mollo, Diyi Yang, Dong-Ho Lee, Dylan Schrader, Ekaterina Shutova, Ekin Dogus Cubuk, Elad Segal, Eleanor Hagerman, Elizabeth Barnes, Elizabeth Donoway, Ellie Pavlick, Emanuele Rodolà, Emma Lam, Eric Chu, Eric Tang, Erkut Erdem, Ernie Chang, Ethan A. Chi, Ethan Dyer, Ethan J. Jerzak, Ethan Kim, Eunice Engefu Manyasi, Evgenii Zheltonozhskii, Fanyue Xia, Fatemeh Siar, Fernando Martínez-Plumed, Francesca Happé, François Chollet, Frieda Rong, Gaurav Mishra, Genta Indra Winata, Gerard de Melo, Germán Kruszewski, Giambattista Parascandolo, Giorgio Mariani, Gloria Wang, Gonzalo Jaimovitch-López, Gregor Betz, Guy Gur-Ari, Hana Galijasevic, Hannah Kim, Hannah Rashkin, Hannaneh Hajishirzi, Harsh Mehta, Hayden Bogar, Henry Shevlin, Hinrich Schütze, Hiromu Yakura, Hongming Zhang, Hugh Mee Wong, Ian Ng, Isaac Noble, Jaap Jumelet, Jack Geissinger, Jackson Kernion, Jacob Hilton, Jaehoon Lee, Jaime Fernández Fisac, James B. Simon, James Koppel, James Zheng, James Zou, Jan Kocon, Jana Thompson, Janelle Wingfield, Jared Kaplan, Jarema Radom, Jascha Sohl-Dickstein, Jason Phang, Jason Wei, Jason Yosinski, Jekaterina Novikova, Jelle Bosscher, Jennifer Marsh, Jeremy Kim, Jeroen Taal, Jesse H. Engel, Jesujoba Alabi, Jiacheng Xu, Jiaming Song, Jillian Tang, Joan Waweru, John Burden, John Miller, John U. Balis, Jonathan Batchelder, Jonathan Berant, Jörg Frohberg, Jos Rozen, José Hernández-Orallo, Joseph Boudeman, Joseph Guerr, Joseph Jones, Joshua B. Tenenbaum, Joshua S. Rule, Joyce Chua, Kamil Kanclerz, Karen Livescu, Karl Krauth, Karthik Gopalakrishnan, Katerina Ignatyeva, Katja Markert, Kaustubh D. Dhole, Kevin Gimpel, Kevin Omondi, Kory Mathewson, Kristen Chiafullo, Ksenia Shkaruta, Kumar Shridhar, Kyle McDonell, Kyle Richardson, Laria Reynolds, Leo Gao, Li Zhang, Liam Dugan, Lianhui Qin, Lidia Contreras Ochando, Louis-Philippe Morency, Luca Moschella, Lucas Lam, Lucy Noble, Ludwig Schmidt, Luheng He, Luis Oliveros Colón, Luke Metz, Lütfi Kerem Senel, Maarten Bosma, Maarten Sap, Maartje ter Hoeve, Maheen Farooqi, Manaal Faruqui, Mantas Mazeika, Marco Baturan, Marco Marelli, Marco Maru, María José Ramírez-Quintana, Marie Tolkiehn, Mario Giulianelli, Martha Lewis, Martin Potthast, Matthew L. Leavitt, Matthias Hagen, Mátyás Schubert, Medina Baitemirova, Melody Arnaud, Melvin McElrath, Michael A. Yee, Michael Cohen, Michael Gu, Michael I. Ivanitskiy, Michael Starritt, Michael Strube, Michal Swedrowski, Michele Bevilacqua, Michihiro Yasunaga, Mihir Kale, Mike Cain, Mimee Xu, Mirac Suzgun, Mitch Walker, Mo Tiwari, Mohit Bansal, Moin Aminnaseri, Mor Geva, Mozhdeh Gheini, Mukund Varma T., Nanyun Peng, Nathan A. Chi, Nayeon Lee, Neta Gur-Ari Krakover, Nicholas Cameron, Nicholas Roberts, Nick Doiron, Nicole Martinez, Nikita Nangia, Niklas Deckers, Niklas Muennighoff, Nitish Shirish Keskar, Niveditha Iyer, Noah Constant, Noah Fiedel, Nuan Wen, Oliver Zhang, Omar Agha, Omar Elbaghdadi, Omer Levy, Owain Evans, Pablo Antonio Moreno Casares, Parth Doshi, Pascale Fung, Paul Pu Liang, Paul Vicol, Pegah Alipoormolabashi, Peiyuan Liao, Percy Liang, Peter Chang, Peter Eckersley, Phu Mon Htut, Pinyu Hwang, Piotr Milkowski, Piyush Patil, Pouya Pezeshkpour, Priti Oli, Qiaozhu Mei, Qing Lyu, Qinlang Chen, Rabin Banjade, Rachel Etta Rudolph, Raefer Gabriel, Rahel Habacker, Ramon Risco, Raphaël Millière, Rhythm Garg, Richard Barnes, Rif A. Saurous, Riku Arakawa, Robbe Raymaekers, Robert Frank, Rohan Sikand, Roman Novak, Roman Sitelew, Ronan LeBras, Rosanne Liu, Rowan Jacobs, Rui Zhang, Ruslan Salakhutdinov, Ryan Chi, Ryan Lee, Ryan Stovall, Ryan Teehan, Rylan Yang, Sahib Singh, Saif M. Mohammad, Sajant Anand, Sam Dillavou, Sam Shleifer, Sam Wiseman, Samuel Gruetter, Samuel R. Bowman, Samuel S. Schoenholz, Sanghyun Han, Sanjeev Kwatra, Sarah A. Rous, Sarik Ghazarian, Sayan Ghosh, Sean Casey, Sebastian Bischoff, Sebastian Gehrmann, Sebastian Schuster, Sepideh Sadeghi, Shadi Hamdan, Sharon Zhou, Shashank Srivastava, Sherry Shi, Shikhar Singh, Shima Asaadi, Shixiang Shane Gu, Shubh Pachchigar, Shubham Toshniwal, Shyam Upadhyay, Shyamolima (Shammie) Debnath, Siamak Shakeri, Simon Thormeyer, Simone Melzi, Siva Reddy, Sneha Priscilla Makini, Soo-Hwan Lee, Spencer Torene, Sriharsha Hatwar, Stanislas Dehaene, Stefan Divic, Stefano Ermon, Stella Biderman, Stephanie Lin, Stephen Prasad, Steven T. Piantadosi, Stuart M. Shieber, Summer Misherghi, Svetlana Kiritchenko, Swaroop Mishra, Tal Linzen, Tal Schuster, Tao Li, Tao Yu, Tariq Ali, Tatsu Hashimoto, Te-Lin Wu, Théo Desbordes, Theodore Rothschild, Thomas Phan, Tianle Wang, Tiberius Nkinyili, Timo Schick, Timofei Kornev, Titus Tunduny, Tobias Gerstenberg, Trenton Chang, Trishala Neeraj, Tushar Khot, Tyler Shultz, Uri Shaham, Vedant Misra, Vera Demberg, Victoria Nyamai, Vikas Raunak, Vinay V. Ramasesh, Vinay Uday Prabhu, Vishakh Padmakumar, Vivek Srikumar, William Fedus, William Saunders, William Zhang, Wout Vossen, Xiang Ren, Xiaoyu Tong, Xinran Zhao, Xinyi Wu, Xudong Shen, Yadollah Yaghoobzadeh, Yair Lakretz, Yangqiu Song, Yasaman Bahri, Yejin Choi, Yichi Yang, Yiding Hao, Yifu Chen, Yonatan Belinkov, Yu Hou, Yufang Hou, Yuntao Bai, Zachary Seid, Zhuoye Zhao, Zijian Wang, Zijie J. Wang, Zirui Wang, Ziyi Wu:
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. Trans. Mach. Learn. Res. 2023 (2023) - [c18]Akari Asai, Timo Schick, Patrick S. H. Lewis, Xilun Chen, Gautier Izacard, Sebastian Riedel, Hannaneh Hajishirzi, Wen-tau Yih:
Task-aware Retrieval with Instructions. ACL (Findings) 2023: 3650-3675 - [c17]Or Honovich, Thomas Scialom, Omer Levy, Timo Schick:
Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor. ACL (1) 2023: 14409-14428 - [c16]Abdullatif Köksal, Timo Schick, Hinrich Schütze:
MEAL: Stable and Active Learning for Few-Shot Prompting. EMNLP (Findings) 2023: 506-517 - [c15]Katerina Margatina, Timo Schick, Nikolaos Aletras, Jane Dwivedi-Yu:
Active Learning Principles for In-Context Learning with Large Language Models. EMNLP (Findings) 2023: 5011-5034 - [c14]Timo Schick, Jane A. Yu, Zhengbao Jiang, Fabio Petroni, Patrick S. H. Lewis, Gautier Izacard, Qingfei You, Christoforos Nalmpantis, Edouard Grave, Sebastian Riedel:
PEER: A Collaborative Language Model. ICLR 2023 - [c13]Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, Thomas Scialom:
Toolformer: Language Models Can Teach Themselves to Use Tools. NeurIPS 2023 - [c12]Yanchen Liu, Timo Schick, Hinrich Schütze:
Semantic-Oriented Unlabeled Priming for Large-Scale Language Models. SustaiNLP 2023: 32-38 - [i28]Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, Thomas Scialom:
Toolformer: Language Models Can Teach Themselves to Use Tools. CoRR abs/2302.04761 (2023) - [i27]Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ramakanth Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, Thomas Scialom:
Augmented Language Models: a Survey. CoRR abs/2302.07842 (2023) - [i26]Abdullatif Köksal, Timo Schick, Anna Korhonen, Hinrich Schütze:
LongForm: Optimizing Instruction Tuning for Long Text Generation with Corpus Extraction. CoRR abs/2304.08460 (2023) - [i25]Katerina Margatina, Timo Schick, Nikolaos Aletras, Jane Dwivedi-Yu:
Active Learning Principles for In-Context Learning with Large Language Models. CoRR abs/2305.14264 (2023) - [i24]Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Luke Zettlemoyer, Omer Levy, Jason Weston, Mike Lewis:
Self-Alignment with Instruction Backtranslation. CoRR abs/2308.06259 (2023) - [i23]Anirudh Mittal, Timo Schick, Mikel Artetxe, Jane Dwivedi-Yu:
Evaluation of Faithfulness Using the Longest Supported Subsequence. CoRR abs/2308.12157 (2023) - 2022
- [j2]Timo Schick, Hinrich Schütze:
True Few-Shot Learning With Prompts - A Real-World Perspective. Trans. Assoc. Comput. Linguistics 10: 716-731 (2022) - [c11]Lütfi Kerem Senel, Timo Schick, Hinrich Schütze:
CoDA21: Evaluating Language Understanding Capabilities of NLP Models With Context-Definition Alignment. ACL (2) 2022: 815-824 - [c10]Dheeraj Mekala, Tu Vu, Timo Schick, Jingbo Shang:
Leveraging QA Datasets to Improve Generative Data Augmentation. EMNLP 2022: 9737-9750 - [p1]Timo Schick:
Few-Shot Learning mit Sprachmodellen. Ausgezeichnete Informatikdissertationen 2022: 251-260 - [i22]Yanchen Liu, Timo Schick, Hinrich Schütze:
Semantic-Oriented Unlabeled Priming for Large-Scale Language Models. CoRR abs/2202.06133 (2022) - [i21]Lütfi Kerem Senel, Timo Schick, Hinrich Schütze:
CoDA21: Evaluating Language Understanding Capabilities of NLP Models With Context-Definition Alignment. CoRR abs/2203.06228 (2022) - [i20]Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. CoRR abs/2206.04615 (2022) - [i19]Fabio Petroni, Samuel Broscheit, Aleksandra Piktus, Patrick S. H. Lewis, Gautier Izacard, Lucas Hosseini, Jane Dwivedi-Yu, Maria Lomeli, Timo Schick, Pierre-Emmanuel Mazaré, Armand Joulin, Edouard Grave, Sebastian Riedel:
Improving Wikipedia Verifiability with AI. CoRR abs/2207.06220 (2022) - [i18]Gautier Izacard, Patrick S. H. Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, Edouard Grave:
Few-shot Learning with Retrieval Augmented Language Models. CoRR abs/2208.03299 (2022) - [i17]Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang, Fabio Petroni, Patrick S. H. Lewis, Gautier Izacard, Qingfei You, Christoforos Nalmpantis, Edouard Grave, Sebastian Riedel:
PEER: A Collaborative Language Model. CoRR abs/2208.11663 (2022) - [i16]Jane Dwivedi-Yu, Timo Schick, Zhengbao Jiang, Maria Lomeli, Patrick S. H. Lewis, Gautier Izacard, Edouard Grave, Sebastian Riedel, Fabio Petroni:
EditEval: An Instruction-Based Benchmark for Text Improvements. CoRR abs/2209.13331 (2022) - [i15]Abdullatif Köksal, Timo Schick, Hinrich Schütze:
MEAL: Stable and Active Learning for Few-Shot Prompting. CoRR abs/2211.08358 (2022) - [i14]Akari Asai, Timo Schick, Patrick S. H. Lewis, Xilun Chen, Gautier Izacard, Sebastian Riedel, Hannaneh Hajishirzi, Wen-tau Yih:
Task-aware Retrieval with Instructions. CoRR abs/2211.09260 (2022) - [i13]Or Honovich, Thomas Scialom, Omer Levy, Timo Schick:
Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor. CoRR abs/2212.09689 (2022) - 2021
- [j1]Timo Schick, Sahana Udupa, Hinrich Schütze:
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP. Trans. Assoc. Comput. Linguistics 9: 1408-1424 (2021) - [c9]Timo Schick, Hinrich Schütze:
Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference. EACL 2021: 255-269 - [c8]Timo Schick, Hinrich Schütze:
Few-Shot Text Generation with Natural Language Instructions. EMNLP (1) 2021: 390-402 - [c7]Timo Schick, Hinrich Schütze:
Generating Datasets with Pretrained Language Models. EMNLP (1) 2021: 6943-6951 - [c6]Timo Schick, Hinrich Schütze:
It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners. NAACL-HLT 2021: 2339-2352 - [i12]Timo Schick, Sahana Udupa, Hinrich Schütze:
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP. CoRR abs/2103.00453 (2021) - [i11]Timo Schick, Hinrich Schütze:
Generating Datasets with Pretrained Language Models. CoRR abs/2104.07540 (2021) - [i10]Timo Schick, Hinrich Schütze:
True Few-Shot Learning with Prompts - A Real-World Perspective. CoRR abs/2111.13440 (2021) - 2020
- [c5]Timo Schick, Hinrich Schütze:
Rare Words: A Major Problem for Contextualized Embeddings and How to Fix it by Attentive Mimicking. AAAI 2020: 8766-8774 - [c4]Timo Schick, Hinrich Schütze:
BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance. ACL 2020: 3996-4007 - [c3]Timo Schick, Helmut Schmid, Hinrich Schütze:
Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification. COLING 2020: 5569-5578 - [i9]Timo Schick, Hinrich Schütze:
Exploiting Cloze Questions for Few-Shot Text Classification and Natural Language Inference. CoRR abs/2001.07676 (2020) - [i8]Timo Schick, Hinrich Schütze:
It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners. CoRR abs/2009.07118 (2020) - [i7]Timo Schick, Helmut Schmid, Hinrich Schütze:
Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification. CoRR abs/2010.13641 (2020) - [i6]Timo Schick, Hinrich Schütze:
Few-Shot Text Generation with Pattern-Exploiting Training. CoRR abs/2012.11926 (2020)
2010 – 2019
- 2019
- [c2]Timo Schick, Hinrich Schütze:
Learning Semantic Representations for Novel Words: Leveraging Both Form and Context. AAAI 2019: 6965-6973 - [c1]Timo Schick, Hinrich Schütze:
Attentive Mimicking: Better Word Embeddings by Attending to Informative Contexts. NAACL-HLT (1) 2019: 489-494 - [i5]Timo Schick, Hinrich Schütze:
Attentive Mimicking: Better Word Embeddings by Attending to Informative Contexts. CoRR abs/1904.01617 (2019) - [i4]Timo Schick, Hinrich Schütze:
Rare Words: A Major Problem for Contextualized Embeddings And How to Fix it by Attentive Mimicking. CoRR abs/1904.06707 (2019) - [i3]Timo Schick, Hinrich Schütze:
BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance. CoRR abs/1910.07181 (2019) - 2018
- [i2]Timo Schick, Hinrich Schütze:
Learning Semantic Representations for Novel Words: Leveraging Both Form and Context. CoRR abs/1811.03866 (2018) - 2017
- [i1]Timo Schick:
Transition-Based Generation from Abstract Meaning Representations. CoRR abs/1707.07591 (2017)
Coauthor Index
Jane Dwivedi-Yu
aka: Jane A. Yu
aka: Jane A. Yu
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