Daniel Simig

According to our database, Daniel Simig authored at least 12 papers between 2021 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Evaluating end-to-end entity linking on domain-specific knowledge bases: Learning about ancient technologies from museum collections.

Sebastian Cadavid-Sanchez, Khalil Kacem, Rafael Aparecido Martins Frade, Johannes Boehm, Thomas Chaney, Danial Lashkari, Daniel Simig

CoRR, 2023

SemDeDup: Data-efficient learning at web-scale through semantic deduplication.

Amro Abbas, Kushal Tirumala, Daniel Simig, Surya Ganguli, Ari S. Morcos

CoRR, 2023

MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers.

Lili Yu, Daniel Simig, Colin Flaherty, Armen Aghajanyan, Luke Zettlemoyer, Mike Lewis

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

D4: Improving LLM Pretraining via Document De-Duplication and Diversification.

Kushal Tirumala, Daniel Simig, Armen Aghajanyan, Ari Morcos

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Understanding In-Context Learning via Supportive Pretraining Data.

Xiaochuang Han, Daniel Simig, Todor Mihaylov, Yulia Tsvetkov, Asli Celikyilmaz, Tianlu Wang

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization.

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

CoRR, 2022

Text Characterization Toolkit.

Daniel Simig, Tianlu Wang, Verna Dankers, Peter Henderson, Khuyagbaatar Batsuren, Dieuwke Hupkes, Mona T. Diab

CoRR, 2022

OPT: Open Pre-trained Transformer Language Models.

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

CoRR, 2022

Text Characterization Toolkit (TCT).

Daniel Simig, Tianlu Wang, Verna Dankers, Peter Henderson, Khuyagbaatar Batsuren, Dieuwke Hupkes, Mona T. Diab

Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, 2022

Few-shot Learning with Multilingual Generative Language Models.

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

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Open Vocabulary Extreme Classification Using Generative Models.

Daniel Simig, Fabio Petroni, Pouya Yanki, Kashyap Popat, Christina Du, Sebastian Riedel, Majid Yazdani

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021

Few-shot Learning with Multilingual Language Models.

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

CoRR, 2021