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A curated list of papers in the multimodal and LLM fields maintained by Yangyi-Chen, systematically tracking the latest research developments on arXiv, covering cutting-edge directions such as vision-language models and cross-modal learning.
Section 01
A curated list of papers in the multimodal and LLM fields maintained by Yangyi-Chen, systematically tracking the latest research developments on arXiv, covering cutting-edge directions such as vision-language models and cross-modal learning.
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Splinter is a minimalist, high-performance key-value (KV) and vector storage system enabling zero-latency inter-process communication via shared memory and atomic operations. With only 766 lines of core code, it supports millions of operations per second and 768-dimensional vector storage, offering a new architectural approach for local LLM inference and data-intensive applications.
LiteMind is a Python framework that provides developers with a unified API to integrate mainstream LLM providers such as OpenAI, Anthropic, Google Gemini, and Ollama. It supports multimodal input/output, tool calling, RAG enhancement, and agent construction.
OmniRoute is an open-source AI gateway that integrates over 67 large model providers through a single OpenAI-compatible endpoint. It offers intelligent routing, load balancing, automatic degradation, and quota management, helping developers get the most available AI services at the lowest cost.
This article introduces an open-source multimodal RAG framework based on Google Gemini Embedding 2, which can uniformly handle embedding and retrieval of four media types: text, images, videos, and audio. Combined with Supabase pgvector vector database and OpenRouter large language models, it provides a complete production-level retrieval-augmented generation pipeline.