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How Large Language Models are Transforming Machine-Paraphrase Plagiarism.

, , , and . EMNLP, page 952-963. Association for Computational Linguistics, (2022)

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How Large Language Models are Transforming Machine-Paraphrased Plagiarism., , , and . CoRR, (2022)Introducing MBIB - The First Media Bias Identification Benchmark Task and Dataset Collection., , , , , and . SIGIR, page 2765-2774. ACM, (2023)Paraphrase Types for Generation and Detection., , and . EMNLP, page 12148-12164. Association for Computational Linguistics, (2023)Paraphrase Detection: Human vs. Machine Content., , , and . CoRR, (2023)Analyzing Multi-Task Learning for Abstractive Text Summarization., , , and . CoRR, (2022)Enhanced word embeddings using multi-semantic representation through lexical chains., , , , and . CoRR, (2021)Are Neural Language Models Good Plagiarists? A Benchmark for Neural Paraphrase Detection., , , and . JCDL, page 226-229. IEEE, (2021)A domain-adaptive pre-training approach for language bias detection in news., , , , and . JCDL, page 3. ACM, (2022)Aspect-based Document Similarity for Research Papers., , , , and . COLING, page 6194-6206. International Committee on Computational Linguistics, (2020)How Large Language Models are Transforming Machine-Paraphrase Plagiarism., , , and . EMNLP, page 952-963. Association for Computational Linguistics, (2022)