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A Close Look into the Calibration of Pre-trained Language Models., , , , и . ACL (1), стр. 1343-1367. Association for Computational Linguistics, (2023)From Adversarial Arms Race to Model-centric Evaluation: Motivating a Unified Automatic Robustness Evaluation Framework., , , , , , , , , и 3 other автор(ы). ACL (Findings), стр. 9607-9632. Association for Computational Linguistics, (2023)Bridge the Gap Between CV and NLP! A Gradient-based Textual Adversarial Attack Framework., , , и . ACL (Findings), стр. 7132-7146. Association for Computational Linguistics, (2023)CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets., , , , , и . CoRR, (2023)Prudent Silence or Foolish Babble? Examining Large Language Models' Responses to the Unknown., , , , и . CoRR, (2023)A Single Transformer for Scalable Vision-Language Modeling., , , и . CoRR, (2024)Executable Code Actions Elicit Better LLM Agents., , , , , , и . ICML, OpenReview.net, (2024)DRESS: Instructing Large Vision-Language Models to Align and Interact with Humans via Natural Language Feedback., , , , и . CoRR, (2023)Multi-granularity Textual Adversarial Attack with Behavior Cloning., , и . EMNLP (1), стр. 4511-4526. Association for Computational Linguistics, (2021)Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer., , , , , и . EMNLP (1), стр. 4569-4580. Association for Computational Linguistics, (2021)