ACL Research Papers

Explore groundbreaking research from the Association for Computational Linguistics.

Pioneering ACL Research

"Attention Is All You Need"

Introduuces the Transformer architecture, revolutionizing NLP with self-attention mechanisms.

Vaswani et al. (2017)

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"BERT: Pre-training of Deep Bidirectional Transformers"

Establishes bidirectional pre-training, enabling significant improvements in language understanding.

Devlin et al. (2018)

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"Language Models are Unsupervised Multitask Learners"

Introduues the GPT model, demonstrating the power of large-scale unsupervised learning.

Radford et al. (2018)

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"Robustly Optimized BERT Pretraining"

Improves BERT through robust training with more data and training iterations.

Zhang et al. (2019)

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Historical ACL Contributions

1960s-1980s

Early rule-based systems and foundational statistical methods for language analysis.

1990s-2010s

Emergence of machine learning techniques and large-scale statistical models.

2020s-Present

Transformer architectures and foundation models revolutionize NLP capabilities.