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Luke S. Zettlemoyer
Person information
- affiliation: University of Washington, School of Computer Science & Engineering, Seattle, WA, USA
- award (2016): Presidential Early Career Award for Scientists and Engineers
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2020 – today
- 2023
[j11]Siddharth Dalmia
, Dmytro Okhonko, Mike Lewis, Sergey Edunov, Shinji Watanabe, Florian Metze, Luke Zettlemoyer, Abdelrahman Mohamed:
LegoNN: Building Modular Encoder-Decoder Models. IEEE ACM Trans. Audio Speech Lang. Process. 31: 3112-3126 (2023)- [c189]Suzanna Sia, Anton Belyy, Amjad Almahairi, Madian Khabsa, Luke Zettlemoyer, Lambert Mathias:
Logical Satisfiability of Counterfactuals for Faithful Explanations in NLI. AAAI 2023: 9837-9845 - [c188]Hongjin Su, Weijia Shi, Jungo Kasai, Yizhong Wang, Yushi Hu, Mari Ostendorf, Wen-tau Yih, Noah A. Smith, Luke Zettlemoyer, Tao Yu:
One Embedder, Any Task: Instruction-Finetuned Text Embeddings. ACL (Findings) 2023: 1102-1121 - [c187]Sewon Min, Weijia Shi, Mike Lewis, Xilun Chen, Wen-tau Yih, Hannaneh Hajishirzi, Luke Zettlemoyer:
Nonparametric Masked Language Modeling. ACL (Findings) 2023: 2097-2118 - [c186]Xinxi Lyu, Sewon Min, Iz Beltagy, Luke Zettlemoyer, Hannaneh Hajishirzi:
Z-ICL: Zero-Shot In-Context Learning with Pseudo-Demonstrations. ACL (1) 2023: 2304-2317 - [c185]Boshi Wang, Sewon Min, Xiang Deng, Jiaming Shen, You Wu, Luke Zettlemoyer, Huan Sun:
Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters. ACL (1) 2023: 2717-2739 - [c184]Terra Blevins, Hila Gonen, Luke Zettlemoyer:
Prompting Language Models for Linguistic Structure. ACL (1) 2023: 6649-6663 - [c183]Sweta Agrawal, Chunting Zhou, Mike Lewis, Luke Zettlemoyer, Marjan Ghazvininejad:
In-context Examples Selection for Machine Translation. ACL (Findings) 2023: 8857-8873 - [c182]Xinyan Yu, Sewon Min, Luke Zettlemoyer, Hannaneh Hajishirzi:
CREPE: Open-Domain Question Answering with False Presuppositions. ACL (1) 2023: 10457-10480 - [c181]Xiang Lisa Li, Ari Holtzman, Daniel Fried, Percy Liang, Jason Eisner, Tatsunori Hashimoto, Luke Zettlemoyer, Mike Lewis:
Contrastive Decoding: Open-ended Text Generation as Optimization. ACL (1) 2023: 12286-12312 - [c180]Mengzhou Xia, Mikel Artetxe, Chunting Zhou, Xi Victoria Lin, Ramakanth Pasunuru, Danqi Chen, Luke Zettlemoyer, Veselin Stoyanov:
Training Trajectories of Language Models Across Scales. ACL (1) 2023: 13711-13738 - [c179]Zhoujun Cheng, Tianbao Xie, Peng Shi, Chengzu Li, Rahul Nadkarni, Yushi Hu, Caiming Xiong, Dragomir Radev, Mari Ostendorf, Luke Zettlemoyer, Noah A. Smith, Tao Yu:
Binding Language Models in Symbolic Languages. ICLR 2023 - [c178]Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Scott Yih, Luke Zettlemoyer, Mike Lewis:
InCoder: A Generative Model for Code Infilling and Synthesis. ICLR 2023 - [c177]Olga Golovneva, Moya Chen, Spencer Poff, Martin Corredor, Luke Zettlemoyer, Maryam Fazel-Zarandi, Asli Celikyilmaz:
ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning. ICLR 2023 - [c176]Xuezhe Ma, Chunting Zhou, Xiang Kong, Junxian He, Liangke Gui, Graham Neubig, Jonathan May, Luke Zettlemoyer:
Mega: Moving Average Equipped Gated Attention. ICLR 2023 - [c175]Bhargavi Paranjape, Pradeep Dasigi, Vivek Srikumar, Luke Zettlemoyer, Hannaneh Hajishirzi:
AGRO: Adversarial discovery of error-prone Groups for Robust Optimization. ICLR 2023 - [c174]Hongjin Su, Jungo Kasai, Chen Henry Wu, Weijia Shi, Tianlu Wang, Jiayi Xin, Rui Zhang, Mari Ostendorf, Luke Zettlemoyer, Noah A. Smith, Tao Yu:
Selective Annotation Makes Language Models Better Few-Shot Learners. ICLR 2023 - [c173]Armen Aghajanyan, Lili Yu, Alexis Conneau, Wei-Ning Hsu, Karen Hambardzumyan, Susan Zhang, Stephen Roller, Naman Goyal, Omer Levy, Luke Zettlemoyer:
Scaling Laws for Generative Mixed-Modal Language Models. ICML 2023: 265-279 - [c172]Tim Dettmers, Luke Zettlemoyer:
The case for 4-bit precision: k-bit Inference Scaling Laws. ICML 2023: 7750-7774 - [c171]Yuhang Lai, Chengxi Li, Yiming Wang, Tianyi Zhang, Ruiqi Zhong, Luke Zettlemoyer, Wen-Tau Yih, Daniel Fried, Sida I. Wang, Tao Yu:
DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation. ICML 2023: 18319-18345 - [c170]Michihiro Yasunaga, Armen Aghajanyan, Weijia Shi, Richard James, Jure Leskovec, Percy Liang, Mike Lewis, Luke Zettlemoyer, Wen-Tau Yih:
Retrieval-Augmented Multimodal Language Modeling. ICML 2023: 39755-39769 - [i179]Hu Xu, Saining Xie, Po-Yao Huang, Licheng Yu, Russell Howes, Gargi Ghosh, Luke Zettlemoyer, Christoph Feichtenhofer:
CiT: Curation in Training for Effective Vision-Language Data. CoRR abs/2301.02241 (2023) - [i178]Armen Aghajanyan, Lili Yu, Alexis Conneau, Wei-Ning Hsu, Karen Hambardzumyan, Susan Zhang, Stephen Roller, Naman Goyal, Omer Levy, Luke Zettlemoyer:
Scaling Laws for Generative Mixed-Modal Language Models. CoRR abs/2301.03728 (2023) - [i177]Davis Liang, Hila Gonen, Yuning Mao, Rui Hou, Naman Goyal, Marjan Ghazvininejad, Luke Zettlemoyer, Madian Khabsa:
XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models. CoRR abs/2301.10472 (2023) - [i176]Weijia Shi, Sewon Min, Michihiro Yasunaga, Minjoon Seo, Rich James, Mike Lewis, Luke Zettlemoyer, Wen-tau Yih:
REPLUG: Retrieval-Augmented Black-Box Language Models. CoRR abs/2301.12652 (2023) - [i175]Yu Meng, Jitin Krishnan, Sinong Wang, Qifan Wang, Yuning Mao, Han Fang, Marjan Ghazvininejad, Jiawei Han, Luke Zettlemoyer:
Representation Deficiency in Masked Language Modeling. CoRR abs/2302.02060 (2023) - [i174]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) - [i173]Marjan Ghazvininejad, Hila Gonen, Luke Zettlemoyer:
Dictionary-based Phrase-level Prompting of Large Language Models for Machine Translation. CoRR abs/2302.07856 (2023) - [i172]Bhargavi Paranjape, Scott M. Lundberg, Sameer Singh, Hannaneh Hajishirzi, Luke Zettlemoyer, Marco Túlio Ribeiro:
ART: Automatic multi-step reasoning and tool-use for large language models. CoRR abs/2303.09014 (2023) - [i171]Suchin Gururangan, Margaret Li, Mike Lewis, Weijia Shi, Tim Althoff, Noah A. Smith, Luke Zettlemoyer:
Scaling Expert Language Models with Unsupervised Domain Discovery. CoRR abs/2303.14177 (2023) - [i170]Mitchell Wortsman, Tim Dettmers, Luke Zettlemoyer, Ari Morcos, Ali Farhadi, Ludwig Schmidt:
Stable and low-precision training for large-scale vision-language models. CoRR abs/2304.13013 (2023) - [i169]Haoqiang Kang, Terra Blevins, Luke Zettlemoyer:
Translate to Disambiguate: Zero-shot Multilingual Word Sense Disambiguation with Pretrained Language Models. CoRR abs/2304.13803 (2023) - [i168]Lili Yu, Daniel Simig, Colin Flaherty, Armen Aghajanyan, Luke Zettlemoyer, Mike Lewis:
MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers. CoRR abs/2305.07185 (2023) - [i167]Chunting Zhou, Pengfei Liu, Puxin Xu, Srini Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, Susan Zhang, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, Omer Levy:
LIMA: Less Is More for Alignment. CoRR abs/2305.11206 (2023) - [i166]Mikel Artetxe, Vedanuj Goswami, Shruti Bhosale, Angela Fan, Luke Zettlemoyer:
Revisiting Machine Translation for Cross-lingual Classification. CoRR abs/2305.14240 (2023) - [i165]Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Wei Koh, Mohit Iyyer, Luke Zettlemoyer, Hannaneh Hajishirzi:
FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation. CoRR abs/2305.14251 (2023) - [i164]Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, Luke Zettlemoyer:
QLoRA: Efficient Finetuning of Quantized LLMs. CoRR abs/2305.14314 (2023) - [i163]Chenglei Si, Weijia Shi, Chen Zhao, Luke Zettlemoyer, Jordan L. Boyd-Graber:
Mixture of Prompt Experts for Generalizable and Interpretable Question Answering. CoRR abs/2305.14628 (2023) - [i162]Weijia Shi, Xiaochuang Han, Mike Lewis, Yulia Tsvetkov, Luke Zettlemoyer, Scott Wen-tau Yih:
Trusting Your Evidence: Hallucinate Less with Context-aware Decoding. CoRR abs/2305.14739 (2023) - [i161]Ari Holtzman, Peter West, Luke Zettlemoyer:
Generative Models as a Complex Systems Science: How can we make sense of large language model behavior? CoRR abs/2308.00189 (2023) - [i160]Sewon Min, Suchin Gururangan, Eric Wallace, Hannaneh Hajishirzi, Noah A. Smith, Luke Zettlemoyer:
SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore. CoRR abs/2308.04430 (2023) - [i159]Tianlu Wang, Ping Yu, Xiaoqing Ellen Tan, Sean O'Brien, Ramakanth Pasunuru, Jane Dwivedi-Yu, Olga Golovneva, Luke Zettlemoyer, Maryam Fazel-Zarandi, Asli Celikyilmaz:
Shepherd: A Critic for Language Model Generation. CoRR abs/2308.04592 (2023) - [i158]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) - [i157]Benjamin Muller, Belen Alastruey, Prangthip Hansanti, Elahe Kalbassi, Christophe Ropers, Eric Michael Smith, Adina Williams, Luke Zettlemoyer, Pierre Andrews, Marta R. Costa-jussà:
The Gender-GAP Pipeline: A Gender-Aware Polyglot Pipeline for Gender Characterisation in 55 Languages. CoRR abs/2308.16871 (2023) - [i156]Lucas Bandarkar, Davis Liang, Benjamin Muller, Mikel Artetxe, Satya Narayan Shukla, Donald Husa, Naman Goyal, Abhinandan Krishnan, Luke Zettlemoyer, Madian Khabsa:
The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants. CoRR abs/2308.16884 (2023) - [i155]Lili Yu, Bowen Shi, Ramakanth Pasunuru, Benjamin Muller, Olga Golovneva, Tianlu Wang, Arun Babu, Binh Tang, Brian Karrer, Shelly Sheynin, Candace Ross, Adam Polyak, Russell Howes, Vasu Sharma, Puxin Xu, Hovhannes Tamoyan, Oron Ashual, Uriel Singer, Shang-Wen Li, Susan Zhang, Richard James, Gargi Ghosh, Yaniv Taigman, Maryam Fazel-Zarandi, Asli Celikyilmaz, Luke Zettlemoyer, Armen Aghajanyan:
Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning. CoRR abs/2309.02591 (2023) - [i154]Hu Xu, Saining Xie, Xiaoqing Ellen Tan, Po-Yao Huang, Russell Howes, Vasu Sharma, Shang-Wen Li, Gargi Ghosh, Luke Zettlemoyer, Christoph Feichtenhofer:
Demystifying CLIP Data. CoRR abs/2309.16671 (2023) - [i153]Xi Victoria Lin, Xilun Chen, Mingda Chen, Weijia Shi, Maria Lomeli, Rich James, Pedro Rodriguez, Jacob Kahn, Gergely Szilvasy, Mike Lewis, Luke Zettlemoyer, Scott Yih:
RA-DIT: Retrieval-Augmented Dual Instruction Tuning. CoRR abs/2310.01352 (2023) - [i152]Weijia Shi, Sewon Min, Maria Lomeli, Chunting Zhou, Margaret Li, Xi Victoria Lin, Noah A. Smith, Luke Zettlemoyer, Scott Yih, Mike Lewis:
In-Context Pretraining: Language Modeling Beyond Document Boundaries. CoRR abs/2310.10638 (2023) - [i151]Joel Jang, Seungone Kim, Bill Yuchen Lin, Yizhong Wang, Jack Hessel, Luke Zettlemoyer, Hannaneh Hajishirzi, Yejin Choi, Prithviraj Ammanabrolu:
Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging. CoRR abs/2310.11564 (2023) - [i150]Weijia Shi, Anirudh Ajith, Mengzhou Xia, Yangsibo Huang, Daogao Liu, Terra Blevins, Danqi Chen, Luke Zettlemoyer:
Detecting Pretraining Data from Large Language Models. CoRR abs/2310.16789 (2023) - 2022
- [j10]Nicola De Cao, Ledell Wu, Kashyap Popat, Mikel Artetxe, Naman Goyal, Mikhail Plekhanov, Luke Zettlemoyer, Nicola Cancedda, Sebastian Riedel, Fabio Petroni:
Multilingual Autoregressive Entity Linking. Trans. Assoc. Comput. Linguistics 10: 274-290 (2022) - [c169]Robin Jia, Mike Lewis, Luke Zettlemoyer:
Question Answering Infused Pre-training of General-Purpose Contextualized Representations. ACL (Findings) 2022: 711-728 - [c168]Rabeeh Karimi Mahabadi, Luke Zettlemoyer, James Henderson, Lambert Mathias, Marzieh Saeidi, Veselin Stoyanov, Majid Yazdani:
Prompt-free and Efficient Few-shot Learning with Language Models. ACL (1) 2022: 3638-3652 - [c167]Jungsoo Park, Sewon Min, Jaewoo Kang, Luke Zettlemoyer, Hannaneh Hajishirzi:
FaVIQ: FAct Verification from Information-seeking Questions. ACL (1) 2022: 5154-5166 - [c166]Sewon Min, Mike Lewis, Hannaneh Hajishirzi, Luke Zettlemoyer:
Noisy Channel Language Model Prompting for Few-Shot Text Classification. ACL (1) 2022: 5316-5330 - [c165]Tianbao Xie, Chen Henry Wu, Peng Shi, Ruiqi Zhong, Torsten Scholak, Michihiro Yasunaga, Chien-Sheng Wu, Ming Zhong, Pengcheng Yin, Sida I. Wang, Victor Zhong, Bailin Wang, Chengzu Li, Connor Boyle, Ansong Ni, Ziyu Yao, Dragomir Radev, Caiming Xiong, Lingpeng Kong, Rui Zhang, Noah A. Smith, Luke Zettlemoyer, Tao Yu:
UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models. EMNLP 2022: 602-631 - [c164]Machel Reid, Victor Zhong, Suchin Gururangan, Luke Zettlemoyer:
M2D2: A Massively Multi-Domain Language Modeling Dataset. EMNLP 2022: 964-975 - [c163]Suchin Gururangan, Dallas Card, Sarah K. Dreier, Emily K. Gade, Leroy Z. Wang, Zeyu Wang, Luke Zettlemoyer, Noah A. Smith:
Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection. EMNLP 2022: 2562-2580 - [c162]Tanay Dixit, Bhargavi Paranjape, Hannaneh Hajishirzi, Luke Zettlemoyer:
CORE: A Retrieve-then-Edit Framework for Counterfactual Data Generation. EMNLP (Findings) 2022: 2964-2984 - [c161]Weijia Shi, Julian Michael, Suchin Gururangan, Luke Zettlemoyer:
Nearest Neighbor Zero-Shot Inference. EMNLP 2022: 3254-3265 - [c160]Freda Shi, Daniel Fried, Marjan Ghazvininejad, Luke Zettlemoyer, Sida I. Wang:
Natural Language to Code Translation with Execution. EMNLP 2022: 3533-3546 - [c159]Terra Blevins, Luke Zettlemoyer:
Language Contamination Helps Explains the Cross-lingual Capabilities of English Pretrained Models. EMNLP 2022: 3563-3574 - [c158]Terra Blevins, Hila Gonen, Luke Zettlemoyer:
Analyzing the Mono- and Cross-Lingual Pretraining Dynamics of Multilingual Language Models. EMNLP 2022: 3575-3590 - [c157]Devendra Singh Sachan, Mike Lewis, Mandar Joshi, Armen Aghajanyan, Wen-tau Yih, Joelle Pineau, Luke Zettlemoyer:
Improving Passage Retrieval with Zero-Shot Question Generation. EMNLP 2022: 3781-3797 - [c156]Mikel Artetxe, Jingfei Du, Naman Goyal, Luke Zettlemoyer, Veselin Stoyanov:
On the Role of Bidirectionality in Language Model Pre-Training. EMNLP (Findings) 2022: 3973-3985 - [c155]Xi Victoria Lin, Todor Mihaylov, Mikel Artetxe, Tianlu Wang, Shuohui Chen, Daniel Simig, Myle Ott, Naman Goyal, Shruti Bhosale, Jingfei Du, Ramakanth Pasunuru, Sam Shleifer, Punit Singh Koura, Vishrav Chaudhary, Brian O'Horo, Jeff Wang, Luke Zettlemoyer, Zornitsa Kozareva, Mona T. Diab, Veselin Stoyanov, Xian Li:
Few-shot Learning with Multilingual Generative Language Models. EMNLP 2022: 9019-9052 - [c154]Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, Luke Zettlemoyer:
Rethinking the Role of Demonstrations: What Makes In-Context Learning Work? EMNLP 2022: 11048-11064 - [c153]Mikel Artetxe, Shruti Bhosale, Naman Goyal, Todor Mihaylov, Myle Ott, Sam Shleifer, Xi Victoria Lin, Jingfei Du, Srinivasan Iyer, Ramakanth Pasunuru, Giridharan Anantharaman, Xian Li, Shuohui Chen, Halil Akin, Mandeep Baines, Louis Martin, Xing Zhou, Punit Singh Koura, Brian O'Horo, Jeffrey Wang, Luke Zettlemoyer, Mona T. Diab, Zornitsa Kozareva, Veselin Stoyanov:
Efficient Large Scale Language Modeling with Mixtures of Experts. EMNLP 2022: 11699-11732 - [c152]Armen Aghajanyan, Dmytro Okhonko, Mike Lewis, Mandar Joshi, Hu Xu, Gargi Ghosh, Luke Zettlemoyer:
HTLM: Hyper-Text Pre-Training and Prompting of Language Models. ICLR 2022 - [c151]Tim Dettmers, Mike Lewis, Sam Shleifer, Luke Zettlemoyer:
8-bit Optimizers via Block-wise Quantization. ICLR 2022 - [c150]Eleftheria Briakou, Sida I. Wang, Luke Zettlemoyer, Marjan Ghazvininejad:
BitextEdit: Automatic Bitext Editing for Improved Low-Resource Machine Translation. NAACL-HLT (Findings) 2022: 1469-1485 - [c149]Sewon Min, Mike Lewis, Luke Zettlemoyer, Hannaneh Hajishirzi:
MetaICL: Learning to Learn In Context. NAACL-HLT 2022: 2791-2809 - [c148]Belinda Z. Li, Jane A. Yu, Madian Khabsa, Luke Zettlemoyer, Alon Y. Halevy, Jacob Andreas:
Quantifying Adaptability in Pre-trained Language Models with 500 Tasks. NAACL-HLT 2022: 4696-4715 - [c147]Suchin Gururangan, Mike Lewis, Ari Holtzman, Noah A. Smith, Luke Zettlemoyer:
DEMix Layers: Disentangling Domains for Modular Language Modeling. NAACL-HLT 2022: 5557-5576 - [c146]Tim Dettmers, Mike Lewis, Younes Belkada, Luke Zettlemoyer:
GPT3.int8(): 8-bit Matrix Multiplication for Transformers at Scale. NeurIPS 2022 - [c145]Kushal Tirumala, Aram H. Markosyan, Luke Zettlemoyer, Armen Aghajanyan:
Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models. NeurIPS 2022 - [c144]Victor Zhong, Jesse Mu, Luke Zettlemoyer, Edward Grefenstette, Tim Rocktäschel:
Improving Policy Learning via Language Dynamics Distillation. NeurIPS 2022 - [c143]Paden Tomasello, Akshat Shrivastava, Daniel Lazar, Po-Chun Hsu, Duc Le, Adithya Sagar, Ali Elkahky, Jade Copet, Wei-Ning Hsu, Yossi Adi, Robin Algayres, Tu Ahn Nguyen, Emmanuel Dupoux, Luke Zettlemoyer, Abdelrahman Mohamed:
Stop: A Dataset for Spoken Task Oriented Semantic Parsing. SLT 2022: 991-998 - [i149]Tianbao Xie, Chen Henry Wu, Peng Shi, Ruiqi Zhong, Torsten Scholak, Michihiro Yasunaga, Chien-Sheng Wu, Ming Zhong, Pengcheng Yin, Sida I. Wang, Victor Zhong, Bailin Wang, Chengzu Li, Connor Boyle, Ansong Ni, Ziyu Yao, Dragomir R. Radev, Caiming Xiong, Lingpeng Kong, Rui Zhang, Noah A. Smith, Luke Zettlemoyer, Tao Yu:
UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models. CoRR abs/2201.05966 (2022) - [i148]Armen Aghajanyan, Bernie Huang, Candace Ross, Vladimir Karpukhin, Hu Xu, Naman Goyal, Dmytro Okhonko, Mandar Joshi, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer:
CM3: A Causal Masked Multimodal Model of the Internet. CoRR abs/2201.07520 (2022) - [i147]Suchin Gururangan, Dallas Card, Sarah K. Dreier, Emily K. Gade, Leroy Z. Wang, Zeyu Wang, Luke Zettlemoyer, Noah A. Smith:
Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection. CoRR abs/2201.10474 (2022) - [i146]Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, Luke Zettlemoyer:
Rethinking the Role of Demonstrations: What Makes In-Context Learning Work? CoRR abs/2202.12837 (2022) - [i145]Rabeeh Karimi Mahabadi, Luke Zettlemoyer, James Henderson, Marzieh Saeidi, Lambert Mathias, Veselin Stoyanov, Majid Yazdani:
PERFECT: Prompt-free and Efficient Few-shot Learning with Language Models. CoRR abs/2204.01172 (2022) - [i144]Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Wen-tau Yih, Luke Zettlemoyer, Mike Lewis:
InCoder: A Generative Model for Code Infilling and Synthesis. CoRR abs/2204.05999 (2022) - [i143]Devendra Singh Sachan, Mike Lewis, Mandar Joshi, Armen Aghajanyan, Wen-tau Yih, Joelle Pineau, Luke Zettlemoyer:
Improving Passage Retrieval with Zero-Shot Question Generation. CoRR abs/2204.07496 (2022) - [i142]Terra Blevins, Luke Zettlemoyer:
Language Contamination Explains the Cross-lingual Capabilities of English Pretrained Models. CoRR abs/2204.08110 (2022) - [i141]Freda Shi, Daniel Fried, Marjan Ghazvininejad, Luke Zettlemoyer, Sida I. Wang:
Natural Language to Code Translation with Execution. CoRR abs/2204.11454 (2022) - [i140]Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona T. Diab, Xian Li, Xi Victoria Lin, Todor Mihaylov, Myle Ott, Sam Shleifer, Kurt Shuster, Daniel Simig, Punit Singh Koura, Anjali Sridhar, Tianlu Wang, Luke Zettlemoyer:
OPT: Open Pre-trained Transformer Language Models. CoRR abs/2205.01068 (2022) - [i139]Mandar Joshi, Terra Blevins, Mike Lewis, Daniel S. Weld, Luke Zettlemoyer:
Few-shot Mining of Naturally Occurring Inputs and Outputs. CoRR abs/2205.04050 (2022) - [i138]Kushal Tirumala, Aram H. Markosyan, Luke Zettlemoyer, Armen Aghajanyan:
Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models. CoRR abs/2205.10770 (2022) - [i137]Mikel Artetxe, Jingfei Du, Naman Goyal, Luke Zettlemoyer, Ves Stoyanov:
On the Role of Bidirectionality in Language Model Pre-Training. CoRR abs/2205.11726 (2022) - [i136]Terra Blevins, Hila Gonen, Luke Zettlemoyer:
Analyzing the Mono- and Cross-Lingual Pretraining Dynamics of Multilingual Language Models. CoRR abs/2205.11758 (2022) - [i135]Suzanna Sia, Anton Belyy, Amjad Almahairi, Madian Khabsa, Luke Zettlemoyer, Lambert Mathias:
Logical Satisfiability of Counterfactuals for Faithful Explanations in NLI. CoRR abs/2205.12469 (2022) - [i134]Weijia Shi, Julian Michael, Suchin Gururangan, Luke Zettlemoyer:
Nearest Neighbor Zero-Shot Inference. CoRR abs/2205.13792 (2022) - [i133]Siddharth Dalmia, Dmytro Okhonko, Mike Lewis, Sergey Edunov, Shinji Watanabe, Florian Metze, Luke Zettlemoyer, Abdelrahman Mohamed:
LegoNN: Building Modular Encoder-Decoder Models. CoRR abs/2206.03318 (2022) - [i132]Devendra Singh Sachan, Mike Lewis, Dani Yogatama, Luke Zettlemoyer, Joelle Pineau, Manzil Zaheer:
Questions Are All You Need to Train a Dense Passage Retriever. CoRR abs/2206.10658 (2022) - [i131]Paden Tomasello, Akshat Shrivastava, Daniel Lazar, Po-Chun Hsu, Duc Le, Adithya Sagar, Ali Elkahky, Jade Copet, Wei-Ning Hsu, Yossef Mordechay, Robin Algayres, Tu Anh Nguyen, Emmanuel Dupoux, Luke Zettlemoyer, Abdelrahman Mohamed:
STOP: A dataset for Spoken Task Oriented Semantic Parsing. CoRR abs/2207.10643 (2022) - [i130]Margaret Li, Suchin Gururangan, Tim Dettmers, Mike Lewis, Tim Althoff, Noah A. Smith, Luke Zettlemoyer:
Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Models. CoRR abs/2208.03306 (2022) - [i129]Tim Dettmers, Mike Lewis, Younes Belkada, Luke Zettlemoyer:
LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale. CoRR abs/2208.07339 (2022) - [i128]Hongjin Su, Jungo Kasai, Chen Henry Wu, Weijia Shi, Tianlu Wang, Jiayi Xin, Rui Zhang, Mari Ostendorf, Luke Zettlemoyer, Noah A. Smith, Tao Yu:
Selective Annotation Makes Language Models Better Few-Shot Learners. CoRR abs/2209.01975 (2022) - [i127]Xuezhe Ma, Chunting Zhou, Xiang Kong, Junxian He, Liangke Gui, Graham Neubig, Jonathan May, Luke Zettlemoyer:
Mega: Moving Average Equipped Gated Attention. CoRR abs/2209.10655 (2022) - [i126]Victor Zhong, Jesse Mu, Luke Zettlemoyer, Edward Grefenstette, Tim Rocktäschel:
Improving Policy Learning via Language Dynamics Distillation. CoRR abs/2210.00066 (2022) - [i125]Zhoujun Cheng, Tianbao Xie, Peng Shi, Chengzu Li, Rahul Nadkarni, Yushi Hu, Caiming Xiong, Dragomir Radev, Mari Ostendorf, Luke Zettlemoyer, Noah A. Smith, Tao Yu:
Binding Language Models in Symbolic Languages. CoRR abs/2210.02875 (2022) - [i124]Tanay Dixit, Bhargavi Paranjape, Hannaneh Hajishirzi, Luke Zettlemoyer:
CORE: A Retrieve-then-Edit Framework for Counterfactual Data Generation. CoRR abs/2210.04873 (2022) - [i123]Machel Reid, Victor Zhong, Suchin Gururangan, Luke Zettlemoyer:
M2D2: A Massively Multi-domain Language Modeling Dataset. CoRR abs/2210.07370 (2022) - [i122]Victor Zhong, Weijia Shi, Wen-tau Yih, Luke Zettlemoyer:
RoMQA: A Benchmark for Robust, Multi-evidence, Multi-answer Question Answering. CoRR abs/2210.14353 (2022) - [i121]