What’s Mine becomes Yours: Defining, Annotating and Detecting Context-Dependent Paraphrases in News Interview Dialogs (2024.emnlp-main)
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| Challenge: | a dataset of utterance pairs from NPR and CNN is used to classify paraphrases in dialog. |
| Approach: | They propose a dataset annotated for context-dependent paraphrases and develop a training for crowd-workers to classify paraphrase in dialog. |
| Outcome: | The proposed dataset contains 5,581 annotations on 600 utterance pairs. |
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| Challenge: | a new adversarial method of paraphrase identification is being used to identify paraphrases based on word overlap and syntax . authors propose a dataset that generates semantically equivalent but lexically and syntactically disparate paraphrase pairs . |
| Approach: | They propose an adversarial method for paraphrase identification that uses word overlap and syntax to identify paraphrases. |
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Using Paraphrases to Study Properties of Contextual Embeddings (2022.naacl-main)
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| Challenge: | Previously, paraphrases have been used to probe whether compositionality is accurately captured by BERT, but we believe they can be used to explore many other questions. |
| Approach: | They propose to use paraphrases as a unique source of data to analyze contextualized embeddings, with a particular focus on BERT. |
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| Challenge: | Paraphrasing is an important aspect of natural-language generation that can produce more variety in the way specific content is presented. |
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Don’t Change Me! User-Controllable Selective Paraphrase Generation (2021.eacl-main)
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| Challenge: | a new technique allows paraphrase generation to be user-controlled . a user looking for cheap hotels in New York would not find the other answer helpful . |
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Polly Want a Cracker: Analyzing Performance of Parroting on Paraphrase Generation Datasets (D19-1)
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| Challenge: | Paraphrase generation is an interesting and challenging task which has numerous practical applications. |
| Approach: | They analyze datasets commonly used for paraphrase generation research and show that simply parroting input sentences surpasses state-of-the-art models when evaluated on standard metrics. |
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| Challenge: | Current paraphrase evaluations of language models use binary approaches, offering limited interpretability of specific text changes. |
| Approach: | They introduce a dataset of 800 sentence-level and word-level annotations by 15 annotators and a human preference ranking of paraphrases with different types. |
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Essentia: Mining Domain-specific Paraphrases with Word-Alignment Graphs (D19-53)
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| Challenge: | Existing methods for mining general-purpose paraphrases are often based on statistical methods, but domain-specific corpora are too small to fit statistical methods. |
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ConRPG: Paraphrase Generation using Contexts as Regularizer (2021.emnlp-main)
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| Challenge: | Existing methods for paraphrase generation lack reliable supervision signals. |
| Approach: | They propose an unsupervised paradigm for paraphrase generation based on contextual language models, candidate filtering and paraphrase model training based upon the selected candidates. |
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Leveraging User Paraphrasing Behavior In Dialog Systems To Automatically Collect Annotations For Long-Tail Utterances (2020.coling-industry)
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| Challenge: | In large-scale commercial dialog systems, users express the same request in a wide variety of alternative ways with a long tail of less frequent alternatives. |
| Approach: | They propose a method to leverage this feedback by creating annotated training examples from it. |
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ParaTag: A Dataset of Paraphrase Tagging for Fine-Grained Labels, NLG Evaluation, and Data Augmentation (2022.emnlp-main)
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| Challenge: | Existing datasets only annotate a binary label for each sentence pair. Existing models only annnotate binary labels for each phrase pair. |
| Approach: | They propose a novel binary paraphrase classification task that annotates the degree of paraphrase between sentences and a new annotation schema that labels the minimum spans of tokens in a sentence that don't have the corresponding paraphrases in the other sentence. |
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