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In this work, we explore a Multilingual Information Retrieval (MLIR) task, where the collection includes documents in multiple languages.
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Robust Document Representations for Cross-Lingual Information Retrieval in Low-Resource Settings. In Proceedings of Machine Translation Summit XVII Volume 1: Research Track . European Association for Machine Translation, Dublin, Ireland, 12–20
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Training effective neural CLIR by bridging the translation gap. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval . 9–18
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The Power of Scale for Parameter-Efficient Prompt Tuning
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In-Batch Negatives for Knowledge Distillation with Tightly-Coupled Teachers for Dense Retrieval. In Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP-2021) . Association for Computational Linguistics, Online, 163–173
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Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. 2020 · 2020
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Overview of the TREC 2019 deep learning track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, and Ellen M Voorhees. 2020 · 2020
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CCAligned: A Massive Collection of Cross-lingual Web-Document Pairs. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020)
Ahmed El-Kishky, Vishrav Chaudhary, Francisco Guzmán, and Philipp Koehn. 2020 · 2020
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Improving efficient neural ranking models with cross-architecture knowledge distillation
Sebastian Hofstätter, Sophia Althammer, Michael Schröder, Mete Sertkan, and Allan Hanbury. 2020 · 2020
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Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
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Colbert: Efficient and effective passage search via contextualized late interaction over bert. In Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval . 39–48
Omar Khattab and Matei Zaharia. 2020 · 2020
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Twinbert: Distilling knowledge to twin-structured compressed bert models for large-scale retrieval. In Proceedings of the 29th ACM International Conference on Information & Knowledge Management
Wenhao Lu, Jian Jiao, and Ruofei Zhang. 2020 · 2020
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Teaching a new dog old tricks: Resurrecting multilingual retrieval using zero-shot learning. In Advances in Information Retrieval: 42nd European Conference on IR Research, ECIR 2020, Lisbon, Portugal, April 14–17, 2020, Proceedings, Part II 42 . Springer, 246–254
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An axiomatic approach to corpus-based cross-language information retrieval
Razieh Rahimi, Ali Montazeralghaem, and Azadeh Shakery. 2020 · 2020
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Sparse, dense, and attentional representations for text retrieval
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Multitask Prompted Training Enables Zero-Shot Task Generalization
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ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction. In North American Chapter of the Association for Computational Linguistics
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Puxuan Yu, Hongliang Fei, and Ping Li. 2021 · 2021
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Mr. TyDi: A multi-lingual benchmark for dense retrieval
Xinyu Zhang, Xueguang Ma, Peng Shi, and Jimmy Lin. 2021 · 2021
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Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections. In Conference on Empirical Methods in Natural Language Processing
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ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts
Akari Asai, Mohammadreza Salehi, Matthew E. Peters, and Hannaneh Hajishirzi. 2022 · 2022
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Bitext mining using distilled sentence representations for low-resource languages
Kevin Heffernan, Onur Çelebi, and Holger Schwenk. 2022 · 2022
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HC4: A new suite of test collections for ad hoc CLIR. In Advances in Information Retrieval: 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part I . Springer, 351–366
Dawn Lawrie, James Mayfield, Douglas W Oard, and Eugene Yang. 2022 · 2022
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Learning Cross-Lingual IR from an English Retriever. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . Association for Computational Linguistics, Seattle, United States, 4428–4436
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Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning
Haokun Liu, Derek Tam, Mohammed Muqeeth, Jay Mohta, Tenghao Huang, Mohit Bansal, and Colin Raffel. 2022 · 2022
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Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation. In Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
Rongrong Ma, Guansong Pang, Ling Chen, and Anton van den Hengel. 2022 · 2022
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Transfer learning approaches for building cross-language dense retrieval models. In European Conference on Information Retrieval . Springer, 382–396
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On transferability of prompt tuning for natural language processing. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . 3949–3969
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Bitext Mining for Low-Resource Languages via Contrastive Learning
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Benchmarking Generalization via In-Context Instructions on 1, 600+ Language Tasks
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Parameter-efficient Zero-shot Transfer for Cross-Language Dense Retrieval with Adapters
Eugene Yang, Suraj Nair, Dawn Lawrie, James Mayfield, and Douglas W Oard. 2022b · 2022
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Curriculum Learning for Dense Retrieval Distillation
Hansi Zeng, Hamed Zamani, and Vishwa Vinay. 2022 · 2022
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Improving Cross-lingual Information Retrieval on Low-Resource Languages via Optimal Transport Distillation. In The 16th ACM International Conferenceon Web Search and Data Mining (WSDM), 2023
Zhiqi Huang, Puxuan Yu, and James Allan. 2022 · 2023
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Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning. In The Eleventh International Conference on Learning Representations
Zhen Wang, Rameswar Panda, Leonid Karlinsky, Rogerio Feris, Huan Sun, and Yoon Kim. 2023 · 2023
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