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Instructed Language Models with Retrievers Are Powerful Entity Linkers.

, , , , , and . EMNLP, page 2267-2282. Association for Computational Linguistics, (2023)

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Pre-training Text Representations as Meta Learning., , , , , , , , , and 3 other author(s). CoRR, (2020)Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering., , , , , , , , , and . CoRR, (2019)Coherent Entity Disambiguation via Modeling Topic and Categorical Dependency., , , , , , and . CoRR, (2023)TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs., , , , , , , , , and 4 other author(s). CoRR, (2023)Bridge the Gap between Language models and Tabular Understanding., , , , , , , and . CoRR, (2023)Tiger: Transferable Interest Graph Embedding for Domain-Level Zero-Shot Recommendation., , , , , , , and . CIKM, page 2806-2816. ACM, (2022)WIERT: Web Information Extraction via Render Tree., , , , , and . AAAI, page 13166-13173. AAAI Press, (2023)Typos-aware Bottlenecked Pre-Training for Robust Dense Retrieval., , , , , , and . SIGIR-AP, page 212-222. ACM, (2023)NeuronBlocks: Building Your NLP DNN Models Like Playing Lego., , , , , , , and . EMNLP/IJCNLP (3), page 163-168. Association for Computational Linguistics, (2019)Learning from Multiple Noisy Augmented Data Sets for Better Cross-Lingual Spoken Language Understanding., , , , , , and . EMNLP (1), page 3226-3237. Association for Computational Linguistics, (2021)