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The Benefits of Bad Advice: Autocontrastive Decoding across Model Layers.

, , , , , , and . ACL (1), page 10406-10420. Association for Computational Linguistics, (2023)

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Automatic Argument Quality Assessment - New Datasets and Methods., , , , , , , , and . EMNLP/IJCNLP (1), page 5624-5634. Association for Computational Linguistics, (2019)The Benefits of Bad Advice: Autocontrastive Decoding across Model Layers., , , , , , and . ACL (1), page 10406-10420. Association for Computational Linguistics, (2023)Every Bite Is an Experience: Key Point Analysis of Business Reviews., , , , and . ACL/IJCNLP (1), page 3376-3386. Association for Computational Linguistics, (2021)From Arguments to Key Points: Towards Automatic Argument Summarization., , , , , and . ACL, page 4029-4039. Association for Computational Linguistics, (2020)A Large-scale Dataset for Argument Quality Ranking: Construction and Analysis., , , , , , and . CoRR, (2019)VIRATrustData: A Trust-Annotated Corpus of Human-Chatbot Conversations About COVID-19 Vaccines., , , , , , , and . CoRR, (2022)Overview of the 2021 Key Point Analysis Shared Task., , , , , and . ArgMining@EMNLP, page 154-164. Association for Computational Linguistics, (2021)Quantitative argument summarization and beyond: Cross-domain key point analysis., , , , , and . EMNLP (1), page 39-49. Association for Computational Linguistics, (2020)Benchmark Data and Evaluation Framework for Intent Discovery Around COVID-19 Vaccine Hesitancy., , , , , , , , , and . CoRR, (2022)A Large-Scale Dataset for Argument Quality Ranking: Construction and Analysis., , , , , , and . AAAI, page 7805-7813. AAAI Press, (2020)