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MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions.

, , , , and . EMNLP, page 15686-15702. Association for Computational Linguistics, (2023)

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Robustra: Training Provable Robust Neural Networks over Reference Adversarial Space., , , and . IJCAI, page 4711-4717. ijcai.org, (2019)Generating Regular Expressions from Natural Language Specifications: Are We There Yet?, , , , , , and . AAAI Workshops, volume WS-18 of AAAI Technical Report, page 791-794. AAAI Press, (2018)Retrieval-based Language Models and Applications., , , and . ACL (tutorial), page 41-46. Association for Computational Linguistics, (2023)Poisoning Retrieval Corpora by Injecting Adversarial Passages., , , and . EMNLP, page 13764-13775. Association for Computational Linguistics, (2023)A Frustratingly Easy Approach for Joint Entity and Relation Extraction., and . CoRR, (2020)A Frustratingly Easy Approach for Entity and Relation Extraction., and . NAACL-HLT, page 50-61. Association for Computational Linguistics, (2021)Recovering Private Text in Federated Learning of Language Models., , , , , and . NeurIPS, (2022)Learning Food Quality and Safety from Wireless Stickers., , , , and . HotNets, page 106-112. ACM, (2018)Should You Mask 15% in Masked Language Modeling?, , , and . EACL, page 2977-2992. Association for Computational Linguistics, (2023)Simple Entity-Centric Questions Challenge Dense Retrievers., , , and . EMNLP (1), page 6138-6148. Association for Computational Linguistics, (2021)