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NaturalAdversaries: Can Naturalistic Adversaries Be as Effective as Artificial Adversaries?

, , and . EMNLP (Findings), page 5635-5645. Association for Computational Linguistics, (2022)

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Distributed Compressive Sensing: A Deep Learning Approach., , and . CoRR, (2015)An Empirical Study of Metrics to Measure Representational Harms in Pre-Trained Language Models., , and . CoRR, (2023)Orca 2: Teaching Small Language Models How to Reason., , , , , , , , , and 5 other author(s). CoRR, (2023)Teaching Language Models to Hallucinate Less with Synthetic Tasks., , , , , , , and . CoRR, (2023)Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness., , , , , and . AAAI, page 14593-14601. AAAI Press, (2023)NICE: Neural Image Commenting with Empathy., , , , , , , and . EMNLP (Findings), page 4456-4472. Association for Computational Linguistics, (2021)Enriching Transformers with Structured Tensor-Product Representations for Abstractive Summarization., , , , , , , , , and . NAACL-HLT, page 4780-4793. Association for Computational Linguistics, (2021)Compositional processing emerges in neural networks solving math problems., , , , , , and . CogSci, cognitivesciencesociety.org, (2021)A Large-Scale Robustness Analysis of Video Action Recognition Models., , , , , , and . CVPR, page 14698-14708. IEEE, (2023)ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection., , , , , and . ACL (1), page 3309-3326. Association for Computational Linguistics, (2022)