Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-semantic-search
A curated list of awesome resources related to Semantic Search🔎 and Semantic Similarity tasks.
https://github.com/Agrover112/awesome-semantic-search
Last synced: 5 days ago
JSON representation
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Libraries and Tools
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2023
- weaviate
- embeddinghub
- fastText
- SBERT
- Relevance AI - Vector Platform From Experimentation To Deployment
- Jina.AI
- pinecone
- BEIR :Benchmarking IR
- RELiC: Retrieving Evidence for Literary Claims Dataset
- Which Frame?
- lexica.art
- milvus
- NeuroNLP++
- weaviate
- same.energy
- ann benchmarks
- scaNN
- REALM
- opensemanticsearch.org
- GPT3 Semantic Search
- Universal Sentence Encoder
- LaBSE
- ELECTRA
- LASER
- SentEval Toolkit
- ranx
- matchzoo-py
- deep_text_matching
- emoji semantic search
- PySerini
- BERTSimilarity
- natural-language-youtube-search
- annoy
- pynndescent
- nsg
- FALCONN
- redis HNSW
- autofaiss
- DPR
- rank_BM25
- FlashRank
- milvus
- Which Frame?
- semantic-search-through-wikipedia-with-weaviate
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Papers
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2010
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2015
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2016
- Bag of Tricks for Efficient Text Classification
- Enriching Word Vectors with Subword Information
- Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs
- On Approximately Searching for Similar Word Embeddings
- Learning Distributed Representations of Sentences from Unlabelled Data
- Approximate Nearest Neighbor Search on High Dimensional Data --- Experiments, Analyses, and Improvement
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2017
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2018
- Universal Sentence Encoder
- Learning Semantic Textual Similarity from Conversations
- Speech2Vec: A Sequence-to-Sequence Framework for Learning Word Embeddings from Speech
- Optimization of Indexing Based on k-Nearest Neighbor Graph for Proximity Search in High-dimensional Data
- The Case for Learned Index Structures
- Google AI Blog: Advances in Semantic Textual Similarity
- The Case for Learned Index Structures
- Universal Sentence Encoder
- Learning Semantic Textual Similarity from Conversations
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2019
- LASER: Language Agnostic Sentence Representations
- Document Expansion by Query Prediction
- Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
- Multi-Stage Document Ranking with BERT
- Latent Retrieval for Weakly Supervised Open Domain Question Answering
- End-to-End Open-Domain Question Answering with BERTserini
- BioBERT: a pre-trained biomedical language representation model for biomedical text mining
- Analyzing and Improving Representations with the Soft Nearest Neighbor Loss
- Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
- Analyzing and Improving Representations with the Soft Nearest Neighbor Loss
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2020
- Rapidly Deploying a Neural Search Engine for the COVID-19 Open Research Dataset: Preliminary Thoughts and Lessons Learned
- PASSAGE RE-RANKING WITH BERT
- CO-Search: COVID-19 Information Retrieval with Semantic Search, Question Answering, and Abstractive Summarization
- LaBSE:Language-agnostic BERT Sentence Embedding
- Covidex: Neural Ranking Models and Keyword Search Infrastructure for the COVID-19 Open Research Dataset
- DeText: A deep NLP framework for intelligent text understanding
- Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation
- Pretrained Transformers for Text Ranking: BERT and Beyond
- REALM: Retrieval-Augmented Language Model Pre-Training
- ELECTRA: PRE-TRAINING TEXT ENCODERS AS DISCRIMINATORS RATHER THAN GENERATORS
- Improving Deep Learning For Airbnb Search
- Managing Diversity in Airbnb Search
- Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
- Unsupervised Image Style Embeddings for Retrieval and Recognition Tasks
- DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations
- Improving Deep Learning For Airbnb Search
- CO-Search: COVID-19 Information Retrieval with Semantic Search, Question Answering, and Abstractive Summarization
- Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation
- PASSAGE RE-RANKING WITH BERT
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2021
- Hybrid approach for semantic similarity calculation between Tamil words
- Augmented SBERT
- BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
- Compatibility-aware Heterogeneous Visual Search
- Learning Personal Style from Few Examples
- TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning
- A Survey of Transformers
- SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking
- High Quality Related Search Query Suggestions using Deep Reinforcement Learning
- Embedding-based Product Retrieval in Taobao Search
- TPRM: A Topic-based Personalized Ranking Model for Web Search
- mMARCO: A Multilingual Version of MS MARCO Passage Ranking Dataset
- Database Reasoning Over Text
- How Does Adversarial Fine-Tuning Benefit BERT?
- Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation
- Primer: Searching for Efficient Transformers for Language Modeling
- SimCSE: Simple Contrastive Learning of Sentence Embeddings
- Compositional Attention: Disentangling Search and Retrieval
- SPANN: Highly-efficient Billion-scale Approximate Nearest Neighbor Search
- GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval
- Generative Search Engines: Initial Experiments
- Rethinking Search: Making Domain Experts out of Dilettantes
- WhiteningBERT: An Easy Unsupervised Sentence Embedding Approach
- Augmented SBERT
- Embedding-based Product Retrieval in Taobao Search
- SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking
- Rethinking Search: Making Domain Experts out of Dilettantes
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2022
- Text and Code Embeddings by Contrastive Pre-Training
- RELIC: Retrieving Evidence for Literary Claims
- Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
- SAMU-XLSR: Semantically-Aligned Multimodal Utterance-level Cross-Lingual Speech Representation
- An Analysis of Fusion Functions for Hybrid Retrieval
- Out-of-distribution Detection with Deep Nearest Neighbors
- ESB: A Benchmark For Multi-Domain End-to-End Speech Recognition
- Analyzing Acoustic Word Embeddings From Pre-Trained Self-Supervised Speech Models
- Rethinking with Retrieval: Faithful Large Language Model Inference
- Precise Zero-Shot Dense Retrieval without Relevance Labels
- Transformer Memory as a Differentiable Search Index
- Analyzing Acoustic Word Embeddings From Pre-Trained Self-Supervised Speech Models
- Precise Zero-Shot Dense Retrieval without Relevance Labels
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2023
- FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search
- SparseEmbed: Learning Sparse Lexical Representations with Contextual Embeddings for Retrieval
- “Low-Resource” Text Classification: A Parameter-Free Classification Method with Compressors
- FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search
- SparseEmbed: Learning Sparse Lexical Representations with Contextual Embeddings for Retrieval
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Articles
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2023
- Introducing the hybrid index to enable keyword-aware semantic search
- Argilla Semantic Search
- Simplify Search woth Multilingual Embedding Models
- Tackling Semantic Search
- Semantic search in Azure Cognitive Search
- How we used semantic search to make our search 10x smarter
- Stanford AI Blog : Building Scalable, Explainable, and Adaptive NLP Models with Retrieval
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Some observations about similarity search thresholds
- Near Duplicate Image Search using Locality Sensitive Hashing
- Comprehensive Guide To Approximate Nearest Neighbors Algorithms
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Billion-scale semantic similarity search with FAISS+SBERT
- Billion-scale semantic similarity search with FAISS+SBERT
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Free Course on Vector Similarity Search and Faiss
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Billion-scale semantic similarity search with FAISS+SBERT
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Co:here's Multilingual Text Understanding Model
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Billion-scale semantic similarity search with FAISS+SBERT
- Introducing the hybrid index to enable keyword-aware semantic search
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
- Billion-scale semantic similarity search with FAISS+SBERT
- Building a semantic search engine with dual space word embeddings
- Building a semantic search engine with dual space word embeddings
- Billion-scale semantic similarity search with FAISS+SBERT
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Datasets
Programming Languages
Categories
Keywords
approximate-nearest-neighbor-search
3
information-retrieval
3
nearest-neighbor-search
3
python
3
deep-learning
2
nlp
2
tensorflow
2
ranking
2
locality-sensitive-hashing
2
natural-language-processing
1
neural-network
1
pytorch
1
text
1
text-matching
1
bert
1
semantic
1
similarity
1
clip
1
computer-vision
1
machine-learning
1
matching
1
score-fusion
1
recommender-systems
1
ranking-metrics
1
rank-fusion
1
numba
1
metasearch
1
information-retrieval-metrics
1
information-retrieval-evaluation
1
evaluation-metrics
1
evaluation
1
data-fusion
1
vector-search
1
vector-database
1
semantic-search
1
retrieval-augmented-generation
1
reranking
1
rag
1
lexical-search
1
hybrid-search
1
full-text-search
1
cross-encoder
1
bm25
1
algorithm
1
rust
1
redis-module
1
redis
1
knn
1
hnsw
1
sketches
1