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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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Argument Invention from First Principles., , , , , , , , and . ACL (1), page 1013-1026. Association for Computational Linguistics, (2019)Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours., , , , , , , , , and . EMNLP (Demos), page 159-168. Association for Computational Linguistics, (2022)Zero-Shot Text Classification with Self-Training., , , , , and . EMNLP, page 1107-1119. Association for Computational Linguistics, (2022)Active Learning for BERT: An Empirical Study., , , , , , , , , and . EMNLP (1), page 7949-7962. Association for Computational Linguistics, (2020)Benchmark Agreement Testing Done Right: A Guide for LLM Benchmark Evaluation., , , , , , , and . CoRR, (2024)Efficient Benchmarking (of Language Models)., , , , , , , , and . NAACL-HLT, page 2519-2536. Association for Computational Linguistics, (2024)A Dataset of General-Purpose Rebuttal., , , , , , , , , and 1 other author(s). EMNLP/IJCNLP (1), page 5590-5600. 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)Cluster & Tune: Boost Cold Start Performance in Text Classification., , , , , , and . ACL (1), page 7639-7653. Association for Computational Linguistics, (2022)Active Learning for Natural Language Generation., , , , , and . EMNLP, page 9862-9877. Association for Computational Linguistics, (2023)