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Transformer Language Models without Positional Encodings Still Learn Positional Information.

, , , , and . EMNLP (Findings), page 1382-1390. Association for Computational Linguistics, (2022)

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Can Latent Alignments Improve Autoregressive Machine Translation?, , and . NAACL-HLT, page 2637-2641. Association for Computational Linguistics, (2021)Understanding Transformer Memorization Recall Through Idioms., , , , , and . EACL, page 248-264. Association for Computational Linguistics, (2023)Transformer Language Models without Positional Encodings Still Learn Positional Information., , , , and . EMNLP (Findings), page 1382-1390. Association for Computational Linguistics, (2022)Understanding Transformer Memorization Recall Through Idioms., , , , , and . CoRR, (2022)BERTese: Learning to Speak to BERT., , and . EACL, page 3618-3623. Association for Computational Linguistics, (2021)Not All Similarities Are Created Equal: Leveraging Data-Driven Biases to Inform GenAI Copyright Disputes., , , , , , and . CoRR, (2024)OMG-Attack: Self-Supervised On-Manifold Generation of Transferable Evasion Attacks., , and . ICCV (Workshops), page 3698-3708. IEEE, (2023)SCROLLS: Standardized CompaRison Over Long Language Sequences., , , , , , , , , and 1 other author(s). EMNLP, page 12007-12021. Association for Computational Linguistics, (2022)