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2020年7月12日 — BERT (Bidirectional Encoder Representations from Transformers) is a recent paper published by researchers at Google AI Language. BERT's key ...

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2019年10月25日 — But you'll still stump Google from time to time. Even with BERT, we don't always get it right. If you search for “what state is south of ...
作者:X Chen2021被引用次数:2 — BERT-based text ranking models have dramatically advanced the state-of-the-art in ad-hoc retrieval, wherein most models tend to consider ...
作者:AA Deshmukh2020被引用次数:4 — ... on building an effective search query by combining weighted keywords extracted from the query document and uses BM25 for retrieval.
作者:WC Chang2020被引用次数:86 — We consider the large-scale query-document retrieval problem: given a query ... BERT-style pre-training tasks on cross-attention models, the retrieval phase ...
Universidade Nova de Lisboa - ‪‪引用: 127 件‬‬ - ‪Cross-modal Retrieval‬ - ‪Deep Learning‬ ... BERT Embeddings Can Track Context in Conversational Search.
Rethinking query expansion for bert reranking. R Padaki, Z Dai, J Callan. Advances in Information Retrieval 12036, 297, 2020.
2020年8月12日 — Posted by Ming-Wei Chang and Kelvin Guu, Research Scientists, Google Research. Recent advances in natural language processing have largely ...
2018年11月2日 — Posted by Jacob Devlin and Ming-Wei Chang, Research Scientists, Google AI Language One of the biggest challenges in natural language ...
作者:A Esteva2021被引用次数:1 — model (Siamese-BERT) that encodes query-level meaning, along with two keyword-based models (BM25, TF-IDF) that emphasize the most important words of a query ...

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