PinnedThanks for the appreciation, Its surreal for me to get acknowledged from the author itself.Feb 1Feb 1
Papers Explained 271: Spreadsheet LLMSpreadsheet LLM introduces an efficient encoding method designed to unleash and optimize LLMs’ powerful understanding and reasoning…13h ago13h ago
Papers Explained 270: OLMoEOLMoE is a sparse Mixture-of-Experts based Language Model with 7B parameters, out of which only 1B parameters are active per input token…1d ago11d ago1
Papers Explained 269: EagleThis work systematically investigates the mixture-of-vision-encoders design space for improved MLLM perception and leads to several…2d ago2d ago
Paper Explained 268: PaliGemma2PaliGemma 2 is an upgrade of PaliGemma by replacing its language model component with the more recent and more capable language models from…3d ago3d ago
Papers Explained 267: Jina RerankerJina Reranker is a neural reranking model designed to tackle this critical issue of relevancy. It enhances search and RAG system by…6d ago16d ago1
Papers Explained 266: Jina Embeddings v3Jina Embeddings V3 is a text embedding model with 570 million parameters. It is trained on multilingual data and is designed for…Dec 5Dec 5
Papers Explained 265: Jina Bilingual EmbeddingsThis paper presents a novel suite of state-of-the-art bilingual text embedding models that are designed to support English and another…Dec 4Dec 4
Papers Explained 264: Jina Embeddings v2The current open-source text embedding models struggle to represent lengthy documents and often resort to truncation, requiring splitting…Dec 3Dec 3
Papers Explained 263: Jina Embeddings v1Jina Embeddings are a set of sentence embedding models ranging from 35M to 6B parameters that translate textual inputs into numerical…Dec 2Dec 2
