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2020 – today
- 2023
[c6]Xiaochuang Han, Daniel Simig, Todor Mihaylov, Yulia Tsvetkov, Asli Celikyilmaz, Tianlu Wang:
Understanding In-Context Learning via Supportive Pretraining Data. ACL (1) 2023: 12660-12673- [c5]Kushal Tirumala, Daniel Simig, Armen Aghajanyan, Ari Morcos:
D4: Improving LLM Pretraining via Document De-Duplication and Diversification. NeurIPS 2023 - [c4]Lili Yu, Daniel Simig, Colin Flaherty, Armen Aghajanyan, Luke Zettlemoyer, Mike Lewis:
MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers. NeurIPS 2023 - [i10]Amro Abbas, Kushal Tirumala, Daniel Simig, Surya Ganguli, Ari S. Morcos:
SemDeDup: Data-efficient learning at web-scale through semantic deduplication. CoRR abs/2303.09540 (2023) - [i9]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) - [i8]Sebastian Cadavid-Sanchez, Khalil Kacem, Rafael Aparecido Martins Frade, Johannes Boehm, Thomas Chaney, Danial Lashkari, Daniel Simig:
Evaluating end-to-end entity linking on domain-specific knowledge bases: Learning about ancient technologies from museum collections. CoRR abs/2305.14588 (2023) - [i7]Xiaochuang Han, Daniel Simig, Todor Mihaylov, Yulia Tsvetkov, Asli Celikyilmaz, Tianlu Wang:
Understanding In-Context Learning via Supportive Pretraining Data. CoRR abs/2306.15091 (2023) - [i6]Kushal Tirumala, Daniel Simig, Armen Aghajanyan, Ari S. Morcos:
D4: Improving LLM Pretraining via Document De-Duplication and Diversification. CoRR abs/2308.12284 (2023) - 2022
- [c3]Daniel Simig, Fabio Petroni, Pouya Yanki, Kashyap Popat, Christina Du, Sebastian Riedel, Majid Yazdani:
Open Vocabulary Extreme Classification Using Generative Models. ACL (Findings) 2022: 1561-1583 - [c2]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 - [c1]Daniel Simig, Tianlu Wang, Verna Dankers, Peter Henderson, Khuyagbaatar Batsuren, Dieuwke Hupkes, Mona T. Diab:
Text Characterization Toolkit (TCT). AACL/IJCNLP (System Demonstrations) 2022: 72-87 - [i5]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) - [i4]Daniel Simig, Fabio Petroni, Pouya Yanki, Kashyap Popat, Christina Du, Sebastian Riedel, Majid Yazdani:
Open Vocabulary Extreme Classification Using Generative Models. CoRR abs/2205.05812 (2022) - [i3]Daniel Simig, Tianlu Wang, Verna Dankers, Peter Henderson, Khuyagbaatar Batsuren, Dieuwke Hupkes, Mona T. Diab:
Text Characterization Toolkit. CoRR abs/2210.01734 (2022) - [i2]Srinivasan Iyer, Xi Victoria Lin, Ramakanth Pasunuru, Todor Mihaylov, Daniel Simig, Ping Yu, Kurt Shuster, Tianlu Wang, Qing Liu, Punit Singh Koura, Xian Li, Brian O'Horo, Gabriel Pereyra, Jeff Wang, Christopher Dewan, Asli Celikyilmaz, Luke Zettlemoyer, Ves Stoyanov:
OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization. CoRR abs/2212.12017 (2022) - 2021
- [i1]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 Language Models. CoRR abs/2112.10668 (2021)
Coauthor Index
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