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Pseudo Outlier Exposure for Out-of-Distribution Detection using Pretrained Transformers.

, , , , , and . ACL (Findings), page 1469-1482. Association for Computational Linguistics, (2023)

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HOD: A Benchmark Dataset for Harmful Object Detection., , , and . CoRR, (2023)Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection., , , and . AAAI, page 8246-8254. AAAI Press, (2023)Pseudo Outlier Exposure for Out-of-Distribution Detection using Pretrained Transformers., , , , , and . ACL (Findings), page 1469-1482. Association for Computational Linguistics, (2023)Problem-Solving Guide: Predicting the Algorithm Tags and Difficulty for Competitive Programming Problems., , , and . CoRR, (2023)CAPTCHAs Are Still in Danger: An Efficient Scheme to Bypass Adversarial CAPTCHAs., , , and . WISA, volume 12583 of Lecture Notes in Computer Science, page 31-44. Springer, (2020)Large-Scale Korean Text Dataset for Classifying Biased Speech in Real-World Online Services., , , , , and . CoRR, (2023)A Neural Pre-Conditioning Active Learning Algorithm to Reduce Label Complexity., , , , , and . NeurIPS, (2022)Bag of Tricks for In-Distribution Calibration of Pretrained Transformers., , , and . EACL (Findings), page 551. Association for Computational Linguistics, (2023)Unrestricted Black-Box Adversarial Attack Using GAN with Limited Queries., , and . ECCV Workshops (1), volume 13801 of Lecture Notes in Computer Science, page 467-482. Springer, (2022)New Benchmarks for Asian Facial Recognition Tasks: Face Classification with Large Foundation Models., , , , and . CoRR, (2023)