Semanlink - Neural Search ; Retrieval augmented LM ; Not Encoding Factual Knowledge in Language Model AND Arxiv Doc

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Arxiv Doc - ColBERT - Discuté avec Raphaël - Domain specific corpora - Knowledge-augmented Language Models - Knowledge distillation - Michael Glass - Multi-Vector Retrieval - Neural Search - NLP@Google - Not Encoding Factual Knowledge in Language Model - Question Answering - Retrieval augmented LM - Retriever-Reader - Slot filling - Sparse retrieval - Zero shot -

Neural Search ; Retrieval augmented LM ; Not Encoding Factual Knowledge in Language Model AND Arxiv Doc

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8 Documents

[2404.13950] SPLATE: Sparse Late Interaction Retrieval

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2024-04-23 About

[2304.01982] Rethinking the Role of Token Retrieval in Multi-Vector Retrieval

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2023-04-05 About

[2207.06300] Re2G: Retrieve, Rerank, Generate

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2022-07-14 About

[2203.13088] Introducing Neural Bag of Whole-Words with ColBERTer: Contextualized Late Interactions using Enhanced Reduction

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2022-03-30 About

[2004.12832] ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT

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2022-01-12 About

[2007.00814] Relevance-guided Supervision for OpenQA with ColBERT

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2022-01-07 About

[2112.01488] ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction

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2021-12-05 About

[2002.08909] REALM: Retrieval-Augmented Language Model Pre-Training

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**Augment language model pre-training with a retriever module**, which
is trained using the masked language modeling objective.

> To capture knowledge in a more modular and interpretable way, we augment language model pre-training with a latent knowledge retriever, which allows the model to retrieve and attend over documents from a large corpus such as Wikipedia, used during pre-training, fine-tuning and inference. **For the first time, we show how to pre-train such a knowledge retriever in an unsupervised manner**, using masked language modeling as the learning signal and backpropagating through a retrieval step that considers millions of documents

Hum, #TODO: parallel to be drawn with techniques in [KG-augmented Language Models](tag:knowledge_graph_augmented_language_models) which focus "on the problem of capturing declarative knowledge in the learned parameters of a language model."

[Google AI Blog Post](doc:2020/08/google_ai_blog_realm_integrat)

[Summary](https://joeddav.github.io/blog/2020/03/03/REALM.html) for the [Hugging Face awesome-papers reading group](doc:2021/03/huggingface_awesome_papers_pap)

2020-12-12 About