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Demystifying Prompts in Language Models via Perplexity Estimation.

, , , , and . EMNLP (Findings), page 10136-10148. Association for Computational Linguistics, (2023)

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Deep RNNs Encode Soft Hierarchical Syntax., , and . ACL (2), page 14-19. Association for Computational Linguistics, (2018)Prompting Language Models for Linguistic Structure., , and . ACL (1), page 6649-6663. Association for Computational Linguistics, (2023)MYTE: Morphology-Driven Byte Encoding for Better and Fairer Multilingual Language Modeling., , , , and . CoRR, (2024)Detecting Pretraining Data from Large Language Models., , , , , , , and . CoRR, (2023)Universal NER: A Gold-Standard Multilingual Named Entity Recognition Benchmark., , , , , , , , , and 3 other author(s). CoRR, (2023)Automatically Processing Tweets from Gang-Involved Youth: Towards Detecting Loss and Aggression., , , , , and . COLING, page 2196-2206. ACL, (2016)Translate to Disambiguate: Zero-shot Multilingual Word Sense Disambiguation with Pretrained Language Models., , and . EACL (1), page 1562-1575. Association for Computational Linguistics, (2024)Language Contamination Helps Explains the Cross-lingual Capabilities of English Pretrained Models., and . EMNLP, page 3563-3574. Association for Computational Linguistics, (2022)Mining Paraphrasal Typed Templates from a Plain Text Corpus., , and . ACL (1), The Association for Computer Linguistics, (2016)Better Character Language Modeling through Morphology., and . ACL (1), page 1606-1613. Association for Computational Linguistics, (2019)