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elasticsearch-learning-to-rank
Plugin to integrate Learning to Rank (aka machine learning for better relevance) with Elasticsearch
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similarity
TensorFlow Similarity is a python package focused on making similarity learning quick and easy.
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InfluxDB
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ColBERT
ColBERT: state-of-the-art neural search (SIGIR'20, TACL'21, NeurIPS'21, NAACL'22, CIKM'22, ACL'23, EMNLP'23)
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haystack
:mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
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A curated list of awesome resources related to Semantic Search🔎 and Semantic Similarity tasks.
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qdrant
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WorkOS
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I worked on a learning-to-rank problem at a previous job (which unfortunately never got deployed womp, womp). This was early days, so at the time I was looking at using LambdaMART with solr or elasticsearch for reranking with a Bayesian click model to get pseudo-labels for relevance.
Tensorflow Ranking and Tensorflow similarity (maybe relevant/irrelevant contrastive learning?) look like they could be useful.
ColBERT and successors for retrieval.
Some cool tools like HayStack that would be useful in putting some of these together.
And of course could do some sort of vector search engine like Milvus with nearest neighbors on embeddings.
Some good papers here.
https://github.com/qdrant/qdrant oh nice, very cool that it's open source and all in Rust. Milvus is I think mostly Go, but it has some parts in C++.