Semanlink - Arxiv Doc ; AI + Knowledge Bases AND Retrieval augmented LM

Impression

Recherche de Mot-clé

Recherche de Doc

Préférences...

Arxiv Doc ; AI + Knowledge Bases AND Retrieval augmented LM

Descendants partagés

14 Documents

[2404.13950] SPLATE: Sparse Late Interaction Retrieval

Tags:

2024-04-23 A propos

[2310.03025] Retrieval meets Long Context Large Language Models

Tags:

2023-10-07 A propos

[2310.01352] RA-DIT: Retrieval-Augmented Dual Instruction Tuning

Tags:

2023-10-07 A propos

[2212.14024] Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP

Tags:

2023-06-23 A propos

[2305.15294] Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy

Tags:

2023-05-26 A propos

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

Tags:

2023-04-05 A propos

[2208.03299] Few-shot Learning with Retrieval Augmented Language Model

Tags:

2022-08-08 A propos

[2207.06300] Re2G: Retrieve, Rerank, Generate

Tags:

2022-07-14 A propos

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

Tags:

2022-03-30 A propos

[2108.13934] Robust Retrieval Augmented Generation for Zero-shot Slot Filling

Tags:

2022-01-19 A propos

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

Tags:

2022-01-12 A propos

[2007.00814] Relevance-guided Supervision for OpenQA with ColBERT

Tags:

2022-01-07 A propos

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

Tags:

2021-12-05 A propos

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

Tags:

**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 A propos