Semanlink - Embeddings AND Information retrieval: techniques

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Embeddings AND Information retrieval: techniques

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43 Documents

LlamaIndex sur X : "Save Memory (and Money) in RAG pipeline with @Cohere 's Int8 and Binary Embeddings..."

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2024-03-30 A propos

Nils Reimers sur X : "Embeddings can store only 1 aspect/topic per embedding well."

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2024-03-13 A propos

[2103.05256] CEQE: Contextualized Embeddings for Query Expansion

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2023-10-28 A propos

Fine-Tuning Your Embedding Model to Maximize Relevance Retrieval in RAG Pipeline | by Wenqi Glantz | Sep, 2023 | Better Programming

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2023-09-13 A propos

Jerry Liu sur X : "One major way to improve your RAG system is to fine-tune your embedding model"

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2023-08-25 A propos

SparseEmbed: Learning Sparse Lexical Representations with Contextual Embeddings for Retrieval

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2023-07-26 A propos

[2305.12517] Retrieving Texts based on Abstract Descriptions

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2023-06-15 A propos

Integrate LLM workflows with Knowledge Graph using Neo4j and APOC | by Tomaz Bratanic | Jun, 2023 | Towards Data Science

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2023-06-09 A propos

[2205.11498] Domain Adaptation for Memory-Efficient Dense Retrieval

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2022-09-26 A propos

Semantic search through a vectorized Wikipedia (SentenceBERT) with the Weaviate vector search engine

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2021-12-05 A propos

Building a sentence embedding index with fastText and BM25 | by David Mezzetti | Towards Data Science

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2021-09-30 A propos

[2007.12603] IR-BERT: Leveraging BERT for Semantic Search in Background Linking for News Articles

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2021-04-12 A propos

[1910.04126] Scalable Nearest Neighbor Search for Optimal Transport

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2020-02-20 A propos

Text similarity search in Elasticsearch using vector fields | Elastic Blog

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2020-01-10 A propos

[1910.03524] Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs

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2019-10-09 A propos

[1908.10084] Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

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2019-08-28 A propos

[1602.01137] A Dual Embedding Space Model for Document Ranking

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2019-07-17 A propos

Sent2Vec: An unsupervised approach towards learning sentence embeddings | RARE Technologies

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2019-03-25 A propos

SIGIR 2018 Tutorial - Knowledge Extraction and Inference from Text: Shallow, Deep, and Everything in Between

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2018-07-09 A propos

A Tri-Partite Neural Document Language Model for Semantic Information Retrieval (2018 - ESWC conference)

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2018-06-08 A propos

A Theoretical Approach to Semantic Coding and Hashing | Simons Institute for the Theory of Computing (2016)

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2018-05-26 A propos

Tutorial on Poincaré Embeddings (Jupyter Notebook )

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2018-05-20 A propos

Implementing Poincaré Embeddings | RARE Technologies

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2018-05-20 A propos

[1710.04099] Wembedder: Wikidata entity embedding web service

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2018-02-13 A propos

Modèle Neuronal de Recherche d'Information Augmenté par une Ressource Sémantique (2017)

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2018-02-12 A propos

Evaluating the Impact of Word Embeddings on Similarity Scoring in Practical Information Retrieval (2017)

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> Transferring the success of word embeddings to Information Retrieval (IR) task is currently an active research topic. While embedding-based retrieval models could tackle the vocabulary mismatch problem by making use of the embedding’s inherent similarity between distinct words, most of them struggle to compete with the prevalent strong baselines such as TF-IDF and BM25.

Considering a practical ad-hoc IR task composed of two steps, matching and scoring, compares the performance of several techniques that leverage word embeddings in the retrieval models to compute the similarity between the query and the documents (namely word centroid similarity, paragraph vectors, Word Mover’s distance, as well as a novel inverse document frequency (IDF) re-weighted word centroid similarity).

> We confirm that word embeddings can be successfully employed in a practical information retrieval setting. The proposed cosine similarity of IDF re-weighted, aggregated word vectors is competitive to the TF-IDF baseline.

2018-01-28 A propos

Learning Deep Structured Semantic Models for Web Search using Clickthrough Data - Microsoft Research (2013)

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2017-12-30 A propos

DSSM ("Deep Semantic Similarity Model") - Microsoft Research

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DSSM (Deep Semantic Similarity Model)

2017-12-30 A propos

gensim/WMD_tutorial.ipynb

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2017-12-23 A propos

(fastText) Euclidean distance instead of cosine-similarity?

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2017-12-07 A propos

How to use pre-trained word vectors from Facebook’s fastText

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2017-11-25 A propos

Semantics with Dense Vectors

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2017-11-11 A propos

Using Gensim Word2Vec Embeddings in Keras | Ben Bolte's Blog

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2017-10-23 A propos

Distributed Word Representations for Information Retrieval

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2017-10-01 A propos

Vectorland: Brief Notes from Using Text Embeddings for Search

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2017-09-18 A propos

Using Text Embeddings for Information Retrieval

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2017-09-18 A propos

gensim/FastText_Tutorial.ipynb

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2017-06-28 A propos

An Intuitive Understanding of Word Embeddings: From Count Vectors to Word2Vec

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2017-06-09 A propos

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2017-06-09 A propos

[1607.00570] Representation learning for very short texts using weighted word embedding aggregation

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2017-06-09 A propos

[1512.00765] Learning Semantic Similarity for Very Short Texts

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2017-06-09 A propos

gensim: models.word2vec – Deep learning with word2vec

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2017-06-01 A propos

Word2vec in gensim Tutorial | RaRe Technologies

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2017-06-01 A propos