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UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation., , , , , , , , , и . CoRR, (2023)Towards Better Entity Linking with Multi-View Enhanced Distillation., , , , , , , , , и . CoRR, (2023)PromptBERT: Improving BERT Sentence Embeddings with Prompts., , , , , , , , , и . EMNLP, стр. 8826-8837. Association for Computational Linguistics, (2022)Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings., , , , , , , , , и 3 other автор(ы). CoRR, (2022)Progressively Optimized Bi-Granular Document Representation for Scalable Embedding Based Retrieval., , , , , , , , , и 2 other автор(ы). WWW, стр. 286-296. ACM, (2022)Uni-Retriever: Towards Learning The Unified Embedding Based Retriever in Bing Sponsored Search., , , , , , , , , и 2 other автор(ы). CoRR, (2022)Snapshot-Guided Domain Adaptation for ELECTRA., , , , , , , и . EMNLP (Findings), стр. 2226-2232. Association for Computational Linguistics, (2022)RAPO: An Adaptive Ranking Paradigm for Bilingual Lexicon Induction., , , , , , , , , и 1 other автор(ы). EMNLP, стр. 8870-8883. Association for Computational Linguistics, (2022)