Mastodawn

long US weekend — great time to catch up on some #jinaAI papers about rerankers and code / multilingual / multimodal embeddings:
* jina-reranker-v3
* jina-code-embeddings
* jina-embeddings-v4
* ReaderLM-v2
* jina-clip-v2

Philipp Krenn Dec 13

I spy a #JinaAI model on elastic cloud 🙃

Reddit Tech VN Bot Dec 8

Jina-VLM-2.4B đạt SOTA cho câu hỏi đa ngôn ngữ với encoder SigLIP2 và decoder Qwen3, cho điểm trung bình 72.3 trên 8 benchmark VQA, cùng 78.8 (MMMB) & 74.3 (Multilingual MMBench). Đào tạo từ 5M dữ liệu đa phương tiện & 12B tokens 29 ngôn ngữ. #AI #MachineLearning #JinaAI #TienTien #TríTuNhanTạo

*(Translated and summarized with key stats, no URLs included)*

https://www.reddit.com/r/LocalLLaMA/comments/1ph9pg9/new_jinavlm24b_reaches_sota_for_multilingual/

Philipp Krenn Oct 9

kicking off #ElasticON NYC. I‘ll put the most relevant context (😉) in this thread — it will be a busy day
starting with joining forces with #JinaAI https://www.elastic.co/blog/elastic-jina-ai 🤗

Qiita - 人気の記事 Apr 6, 2025

DeepSearchの精度改善手法：URL Rankingについて
https://qiita.com/xxyc/items/094f889879ce8e9ec7e0?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items

#qiita #ChatGPT #Rerank #DeepResearch #DeepSearch #JinaAI

DeepSearchの精度改善手法：URL Rankingについて - Qiita

最近、DeepSearchの精度向上に非常に興味を持ち、さまざまな論文や各社の研究レポートを調べてみました。そんな中、jina.aiという企業が提案する、rerankを参考にした精度向上アプローチが…

Qiita

bitcrowd Nov 7, 2024

Ready to bring the power of Jina AI embeddings to your next Elixir project? While most projects settle for Python's RAG setups, we know Elixir offers a robust, scalable, and maintainable solution—and we're here to show you how!
Check out the blogpost here: https://bitcrowd.dev/how-to-run-jina-embeddings-in-elixir

#MachineLearning #JinaAI #Elixir

How to use Jina embeddings in Elixir with Bumblebee | bitcrowd blog

When directly compared with OpenAI's 8K model text-embedding-ada-002, the jina-embeddings-v2 stand out in terms of quality. Their long context length is a game changer. Don't let a missing model implementation stop you from realizing your awesome AI project in Elixir. Instead, follow three steps to convert a Python model to Elixir.

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Philipp Krenn Sep 23, 2024

better context seems to be a popular topic right now. "Late Chunking in Long-Context Embedding Models" from #JinaAI works very differently but seems to tackle a similar problem: https://jina.ai/news/late-chunking-in-long-context-embedding-models/
though the results there look less clear

Late Chunking in Long-Context Embedding Models

Chunking long documents while preserving contextual information is challenging. We introduce the "Late Chunking" that leverages long-context embedding models to generate contextual chunk embeddings for better retrieval applications.