Semanlink - NLP based IR

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NLP based IR

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Neural Search
- BEIR
- Cherche (Raphaël)
- ColBERT
- Dense Passage Retrieval
  - Dual encoders (IR)
- Embeddings in Information Retrieval
  - DSSM (Deep Semantic Similarity Model)
- Extractive Search
  - SPIKE-KBC
- Haystack
  - Haystack Annotation Tool
- Hybrid Search
  - Vespa
- Multi-Vector Retrieval
  - ColBERT
    [2211.01267] Multi-Vector Retrieval as Sparse Alignment
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    Arxiv Doc
    Multi-Vector Retrieval
    2023-04-07 About
    [2304.01982] Rethinking the Role of Token Retrieval in Multi-Vector Retrieval
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    Arxiv Doc
    ColBERT
    Multi-Vector Retrieval
    Neural Search
    NLP@Google
    > Multi-vector retrievers like [ColBERT](tag:colbert) are powerful, but they come at the cost of complicated inference. In this paper, we ask: "can token retrieval alone achieve great performance in multi-vector retrieval?" [tweet](https://twitter.com/leejnhk/status/1643632578824396805?s=20) > The key insight of XTR is that the token-retrieval in multi-vector models should be **trained to retrieve the most salient and informative document tokens**, so that the score between a query and document can be computed using only the retrieved information, just like how single-vector retrieval models work > This is an *amazing* way to re-engineer the scoring mechanism of late interaction / ColBERT retrievers! [src: ColBERT's author Omar Khattab](https://twitter.com/lateinteraction/status/1643439889902637056?s=20) - scoring using only retrieved document terms - imputing missing token scores using their upper bound
    
    2023-04-05 About
- Neural Ranking Models
- Pinecone
- REALM
- txtai
- Vespa
- Weaviate