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Simple Local Attentions Remain Competitive for Long-Context Tasks.

, , , , , , , и . CoRR, (2021)

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Chen Chen

Chen Chen

Shih Chen Chen

Yi-Chen Chen

Chen-Loung Chen

 

Другие публикации лиц с тем же именем

SIMDMS: Data Management and Analysis to Support Decision Making through Large Simulation Ensembles., , , , , , , , , и . EDBT, стр. 582-585. OpenProceedings.org, (2017)DataStorm: Coupled, Continuous Simulations for Complex Urban Environments., , , , , , , , , и 1 other автор(ы). Trans. Data Sci., 2 (3): 19:1-19:37 (2021)Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One?, , , , , , , , и . CoRR, (2021)Simple Local Attentions Remain Competitive for Long-Context Tasks., , , , , , , и . CoRR, (2021)Unified Open-Domain Question Answering with Structured and Unstructured Knowledge., , , , , , , , и . CoRR, (2020)Domain-matched Pre-training Tasks for Dense Retrieval., , , , , , , , , и 1 other автор(ы). CoRR, (2021)Multi-Source Cross-Lingual Model Transfer: Learning What to Share., , , , и . CoRR, (2018)Task-aware Retrieval with Instructions., , , , , , , и . CoRR, (2022)Simple Local Attentions Remain Competitive for Long-Context Tasks., , , , , , , и . NAACL-HLT, стр. 1975-1986. Association for Computational Linguistics, (2022)Efficient Incremental Model Learning on Data Streams.. Arizona State University, Tempe, USA, (2019)base-search.net (ftarizonastateun:item:54791).