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DiffQG: Generating Questions to Summarize Factual Changes.

, , , , , and . EACL, page 3080-3093. Association for Computational Linguistics, (2023)

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WinoDict: Probing language models for in-context word acquisition., , , and . EACL, page 94-102. Association for Computational Linguistics, (2023)DiffQG: Generating Questions to Summarize Factual Changes., , , , , and . EACL, page 3080-3093. Association for Computational Linguistics, (2023)Graph-Based Decoding for Task Oriented Semantic Parsing., , , , and . EMNLP (Findings), page 4057-4065. Association for Computational Linguistics, (2021)Selectively Answering Ambiguous Questions., , , , , and . EMNLP, page 530-543. Association for Computational Linguistics, (2023)Word Adoption in Online Communities., , and . IEEE Trans. Comput. Social Systems, 6 (1): 178-188 (2019)Surprisal Predicts Code-Switching in Chinese-English Bilingual Text., , , and . EMNLP (1), page 4029-4039. Association for Computational Linguistics, (2020)NAIL: Lexical Retrieval Indices with Efficient Non-Autoregressive Decoders., , , and . EMNLP, page 2574-2589. Association for Computational Linguistics, (2023)Time-Aware Language Models as Temporal Knowledge Bases., , , , , and . CoRR, (2021)Not that much power: Linguistic alignment is influenced more by low-level linguistic features rather than social power., , and . ACL (1), page 601-610. Association for Computational Linguistics, (2018)WinoDict: Probing language models for in-context word acquisition., , , and . CoRR, (2022)