new

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Learning Diverse Document Representations with Deep Query Interactions for Dense Retrieval（2022，多向量） Topic-Grained Text Representation-based Model for Document Retrieval（2022，多向量）

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pretraining for retrieval

• [ ] ConTextual Mask Auto-Encoder for Dense Passage Retrieval（预训练 for dense retrieval）
• [ ] Retromae: Pre-training retrieval-oriented transformers via masked auto-encoder（预训练 for dense retrieval）
• [ ] Simlm: Pre-training with representation bottleneck for dense passage retrieval.（预训练 for dense retrieval）
• [ ] LexMAE: Lexicon-Bottlenecked Pretraining for Large-Scale Retrieval（预训练 for dense retrieval）
• [ ] A Contrastive Pre-training Approach to Learn Discriminative Autoencoder for Dense Retrieval（预训练 for dense retrieval）

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prompt learning

• [ ] Scattered or Connected? An Optimized Parameter-efficient Tuning Approach for Information Retrieval
• [ ] DPTDR: Deep Prompt Tuning for Dense Passage Retrieval

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LED: Lexicon-Enlightened Dense Retriever for Large-Scale Retrieval （dense） Aggretriever: A Simple Approach to Aggregate Textual Representation for Robust Dense Passage Retrieval（dense）

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hybrid retrieval UnifieR: A Unified Retriever for Large-Scale Retrieval

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domain adaption： Disentangled Modeling of Domain and Relevance for Adaptable Dense Retrieval

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Isotropic Representation Can Improve Dense Retrieval（other） Towards Robust Dense Retrieval via Local Ranking Alignment（other）

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SpaDE: Improving Sparse Representations using a Dual Document Encoder for First-stage Retrieval（Expansion + Term Re-weighting）

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zero-shot: Promptagator: Few-shot Dense Retrieval From 8 Examples