Semanlink - Facebook AND Deep Learning

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Mots-clés liés

AI@Facebook - Arxiv Doc - Attention mechanism - BERT - CamemBERT - Connectionist vs symbolic debate - Cross-lingual NLP - Dan Jurafsky - Deep Learning - Discuté avec Raphaël - Entity Retrieval - Explainable AI - Facebook - Facebook FAIR - France is AI 2018 - Generalization - GitHub project - Graph Embeddings - Guillaume Lample - Identification of similar documents - Job matching - Knowledge distillation - Knowledge Graph + Deep Learning - Knowledge-Intensive NLP Tasks - Language Model - Locality Sensitive Hashing - Ludovic Denoyer - Mathématiques - Memory in deep learning - Minimum Description Length Principle - Nearest neighbor search - NLP: French - NLP@ENS - NLP@Facebook - NLP@Stanford - NLP and Search - NLP sample code - Occam's razor - Overfitting/Generalization - Paris NLP meetup - Pre-Trained Language Models - Ranking (information retrieval) - Recommender Systems - Retriever-Reader - Siamese networks - Transformers - Tweet -

Facebook AND Deep Learning

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CamemBERT

22 Documents

Sentence Embedding Fine-tuning for the French Language | by La Javaness R&D | Feb, 2022 | Medium

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2022-03-31 A propos

[2005.11401] Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

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2022-01-19 A propos

Sahajtomar/french_semantic · Hugging Face

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2021-10-14 A propos

[1901.04085] Passage Re-ranking with BERT

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2021-03-26 A propos

Hugging Face sur Twitter : "Transformers release of the Retrieval-Augmented Generation model in collaboration with @facebookai!"

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2021-02-23 A propos

Guillaume Lample sur Twitter : "Last year, we showed that you can outperform a 24-layer transformer in language modeling with just...

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2020-10-10 A propos

Finding similar documents with transformers · Codegram

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2020-07-10 A propos

facebookresearch/faiss: A library for efficient similarity search and clustering of dense vectors.

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2020-06-09 A propos

[1912.08422] Distilling Structured Knowledge into Embeddings for Explainable and Accurate Recommendation

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2020-05-12 A propos

[1911.03814] Scalable Zero-shot Entity Linking with Dense Entity Retrieval

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2020-05-02 A propos

Paris NLP Season 4 Meetup #3 – Paris NLP (2020)

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2020-01-23 A propos

[1911.00172] Generalization through Memorization: Nearest Neighbor Language Models

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2019-12-20 A propos

[1912.01412] Deep Learning for Symbolic Mathematics

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2019-12-09 A propos

[1905.11852] EDUCE: Explaining model Decisions through Unsupervised Concepts Extraction

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2019-12-05 A propos

CamemBERT

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CamemBERT

2019-11-10 A propos

[1911.01464] Emerging Cross-lingual Structure in Pretrained Language Models

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2019-11-06 A propos

[1802.07044] The Description Length of Deep Learning Models

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2019-10-11 A propos

[1909.01066] Language Models as Knowledge Bases?

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2019-09-05 A propos

[1907.05242] Large Memory Layers with Product Keys

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> **a structured memory which can be easily integrated into a neural network.** The memory is very large by design and therefore significantly increases the capacity of the architecture, by up to a billion parameters with a negligible computational overhead. Its design and access pattern is based on **product keys**, which enable fast and exact nearest neighbor search. The ability to increase the number of parameters while keeping the same computational budget lets the overall system strike a better trade-off between prediction accuracy and computation efficiency both at training and test time.

> a key-value memory layer that can increase model capacity for a negligible computational cost. A 12-layer transformer with a memory outperforms a 24-layer transformer, and is 2x faster!

[Implementation](/doc/2019/08/product_key_memory_pkm_minima)

TODO: compare with [[2007.00849] Facts as Experts: Adaptable and Interpretable Neural Memory over Symbolic Knowledge](doc:2020/07/2007_00849_facts_as_experts_)

2019-07-13 A propos

PyTorch-BigGraph: Faster embeddings of large graphs - Facebook Code

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2019-05-12 A propos

[1503.08895] End-To-End Memory Networks

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2018-10-23 A propos

Facebook’s open-sourcing of AI hardware is the start of the deep-learning revolution | Ars Technica

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2015-12-22 A propos